In turn, what is meant by data peer review is far from defined; standards and processes encompass the full range employed in reviewing the literature, plus some novel variations. Basic data citation is a point of consensus, but the general agreement on the core elements of a dataset citation frays if the data is dynamic or part of a larger set. Even as data publication is being defined, some are looking past publication to other metaphors, notably “data as software,” for solutions to the more stubborn problems.The movement to bring datasets into the scholarly record as first class research products  has been inching forward for some time, but now the pace is quickening. As data publication venues proliferate, significant debate continues over formats, processes, and terminology. Here, we present an overview of data publication initiatives underway and the current conversation, highlighting points of consensus and issues still in contention. Data publication implementations differ in a variety of factors, including the kind of documentation, the location of the documentation relative to the data, and how the data is validated. Publishers may present data as supplemental material to a journal article, with a descriptive “data paper,” or independently. Complicating the situation, different initiatives and communities use the same terms to refer to distinct but overlapping concepts. For instance, the term This shift in language stems from the conviction that datasets should join the scholarly record and be afforded the same first-class status as traditional research products like journal articles5. While many in the scholarly communication community share this goal, different people and organizations often refer to different things with the phrasedata publication.The idea that researchers should share data to advance knowledge and promote the common good is an old one, but in recent years the conversation has shifted from sharing data toet al. (2011) define formal data Publication (upper-case “P”) as making data as permanently available as possible following “a process which means it can appear along with easily digestible information as to its trustworthiness, reliability, format and content”3. Callaghanet al. (2012) draw an explicit distinction between Published and published data:published data is at least available, whilePublished data is persistent, documented, and peer-reviewed5.Publication refers to the scholarly literature, whilepublication is used in the sense of any kind of printed and distributed material. Actual usage is considerably more complicated.Data publication overlaps with terms likedata sharing,data release, andopen data. A data publication might be a spreadsheet on a website, a set of images in an institutional archive, a stream of readings from a weather station transmitted over the internet, or a peer-reviewed article describing a dataset; a data publisher might be a data journal publisher, archive, database, or repository.Lawrence5. First, published data is publiclyavailable now and for the indefinite future; access might demand payment of fees or acceptance of a legal agreement, but is not subject to the whims of the author. Second, published data must be adequatelydocumented such that, at a minimum, a researcher in the same field could reproduce or reuse it. Third, like a book or journal article, a data publication can be formallycited. Data citation maintains the integrity of the expanded scholarly record and offers a reward– in the currency of academic prestige– to encourage researchers to publish data. Open questions flock around a fourth property: how and to what extent a published dataset must bevalidated. Here, we will consider data that is persistently available, documented, and citable to be published, whatever the level of validation.Despite uncertainty over precisely what qualifies, the scholarly communication community largely agrees on three essential properties of a data publication 2,5. Fireproduced and data to bereused. Hidden primary data exacerbates science’s very public “reproducibility crisis”10, recently illustrated by the collapse of a pair of irreproducibleNature articles describing a simple method to transform any cell into a stem cell12. Psychology’s “closed data culture”13 enabled Diederik Stapel to invent data for an astonishing 55 papers, prompting calls for routine psychology data publication15. Widespread publication of the data underlying research papers could help expose honest errors as well as fraud16. The leaders of the US National Institutes of Health (NIH) recently suggested “greater transparency of the data that are the basis of published manuscripts” as one way to improve scientific reproducibility17.The underlying goals of data publication are to enable research to beet al. found that 88% of high-impact journals required a statement regarding the availability of underlying data, and half of those made willingness to provide data a condition of publication18. However, authors of 59% of the papers examined in the study failed to adhere to the availability instructions. Vineset al. (2014) could only obtain underlying data from 101 of 516 papers published from 1991 to 201119. Availability dropped off sharply with time; out of the 62 oldest papers, data was available from only two. Now, some journals require that underlying data be published simultaneously with the article. In 2010, a coalition of Ecology and Evolutionary Biology journals began to require that the data underlying articles be archived with a maximum embargo of one year21.F1000Research has had a similar policy (without an embargo period) since its inception, and thePublic Library of Science (PLOS) journals followed suit earlier this year22.Journals already frequently require authors to supply underlying data on request. In 2011, Alsheikh-AliOpen Context published archaeological data from a site in eastern Turkey at the substantial cost of $10,000–15,000, but this expense is minor compared to $800,000 spent to collect the data23. Piwowar (2011) contrasted the impact of $100,000 in National Science Foundation (NSF) grants, which generates an average of three to four papers, with an estimate that the same investment in curating, archiving, and publishing data could contribute to over 1,000 publications24. Furthermore, while some data is merely expensive to replace, time-dependent or ephemeral data,  can never be recreated for any price25.Although there can be no substitute for funding new experiments and data collection, appropriate data reuse lowers costs and accelerates research. Documenting, publishing, and archiving data is time consuming and costly, but usually far less so than repeating the data collection.27. As in print publication, published data need not be free or legally unencumbered, and data use agreements constrain many published datasets. If access is limited, it should be contingent on clear and objective criteria; writing a request to the creator for permission should not be part of the process. For example, before granting access to restricted data,The interuniversity Consortium for Political and Social Research (ICPSR) evaluates the applicant’s ability to handle the data securely, but not the merit of the research. The most common source of access restrictions is the need to protect the privacy of human research subjects. In the United States, the Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule severely limits the disclosure of medical information28.Fundamentally, to publish is to make public, and to publish data is to make data publicly available. Present availability requires mechanisms for access; future availability also requires preservation Center for Research Libraries (CRL) published the most extensive scheme: the Trusted Repository Audit Checklist (TRAC)29. Many repositories consult TRAC for self-assessment, but only four (listed by the CRL) have completed the lengthy and rigorous process to be officially certified. That same year, DANS released theData Seal of Approval (DSA) guidelines; 31 repositories have been stamped with the DSA since then. TheTrusted Digital Repository framework incorporates the DSA, a TRAC-derived standard, and a third standard from theGerman Institute for Standardization (DIN) to give repositories flexibility in the processes and standards by which they are to be certified. Repositories seeking to join theWorld Data System (WDS) are certified to perform particular role  based on a self-description and possibly a site visit; the WDS currently boasts 56 regular members.As a practical matter, publishing a dataset usually includes depositing it in a trustworthy repository. What constitutes “trustworthy” is somewhat subjective and there are a handful of certification schemes to choose from. In 2007, TheDatabib or the 609 atre3data.org). In practice, the perceived trustworthiness of a repository often derives from the reputation of its managing organization. For instance, repositories run by governments or large universities are likely to be considered trustworthy .Even taken together, these standards certify only a fraction of the hundreds of repositories in operation  project elaborated Jim Gray’s pyramidal model of online scientific data31 into five classes of relationship between data and the literature: ‘desk-drawer’ data and four forms of publication4. Similarly, five classes of data publication described by Lawrenceet al. (2011) have recognizably different kinds of documentation3. Note, however, that a single dataset may have relationships with multiple articles or other documentation, and an article may use or describe multiple datasets. Here, we will discuss three non-mutually-exclusive relationships with the literature: a dataset maysupplement a traditional research paper, be thesubject of a “data paper”, or beindependently documented by its publisher.To be useful or reproducible, a dataset must be accompanied by descriptive information The Journal of Neuroscience stopped publishing supplemental material in 2010; the announcement promotes disciplinary repositories as “vastly superior to supplemental material as a mechanism for disseminating data”32. Data underlying any peer-reviewed or otherwise “reputable” publication can be deposited in theDryad repository. Dryad makes data available and citable, but the publisher of the article must manage any assessment of scientific validity.Research Compendia compiles published articles together with all the underlying code and data. Beyond repositories like these specifically for paper-related data, many more publishers that do not require such a relationship are nevertheless pleased to publish data underlying or described by a paper.The most familiar kind of data publication is a traditional journal article accompanied by underlying data. That data can be hosted by the journal as supplementary material or deposited in a third-party repository. The trend is away from supplemental material because repositories are considered to be better suited to ensure long-term preservation and access to the data. For instance,PLOS data policy requires publication of only the data needed to reproduce the article’s finding. Consequently, not all of the data collected must be published, and the documentation need not support reuse for an unrelated purpose.This kind of data publication supports reproduction of an analysis, but not necessarily reuse. For example, thedata paper describes a dataset with thoroughly detailed rationale and collection methods, but lacks any analysis or conclusions33. Data papers are flourishing as a new article type in journals such asF1000Research,Internet Archaeology, andGigaScience, as well as in dedicated journals likeEarth System Science Data34,Geoscience Data Journal, Nature Publishing Group’sScientific Data, and a trio of “metajournals” from Ubiquity Press. The strength of a data paper is in providing rich documentation, which is especially useful for unique and heterogeneous “long-tail”35 research data.AInternet Archaeology, andOpen Health Data). Some journals supplement this general framework with field-specific sections. . Data papers are most sharply defined not by the presence of any particular information, but by the absence of analysis or conclusions. A crisp distinction from other article types is important because many journals do not consider a data paper to be prior publication if the authors seek to publish an analysis of the same dataset .Data paper length and structure varies between journals, but the tendency is toward a short, tightly structured format. All journals require an abstract, collection methods, and a description of the dataset; a few encourage authors to suggest potential uses for the data  calldata publication by proxy, in which a paper providing a general description of a database or dataset serves as a citable proxy3. Proxy publications are distinguished from data papers in that they may contain analysis or conclusions drawn from the dataset and they may not contain all of the information needed to use the data. For example, theClimatic Research Unit of the University of East Anglia asks dataset users cite to papers associated with a dataset instead of the data itself. In the biosciences,Nucleic Acids Research (NAR) annually publishes a massive issue devoted to such articles; the 2014 database issue featured 58 papers describing new databases and 123 updates on existing resources36. Participating databases typically ask users to cite the most recentNAR paper. Proxy publication or data paper citation serves to award scholarly credit, but fails at other functions of citation and should be supplemented with direct citation of the data.Data papers are predated by an approach that LawrenceDataset documentation need not take the form of a journal article. Together with data, repositories and databases publish documentation– minimal or rich, structured or freeform– that sometimes fulfills the needs of reproducibility and reuse without reference to the literature. Even so, an independently documented dataset might also be described by a data paper or support any number of traditional articles. Academic, governmental, and commercial repositories publish data from diverse place- and interest-based research communities through varying processes with or without linkage to the literature.Merritt, while Purdue University researchers use thePurdue Research Repository (PURR). At the national level, the DutchData Archiving and Networked Services (DANS) accepts a broad range of data from researchers in the Netherlands.Figshare andZenodo publish data from any researcher in any field. These broad-topic publishers are well suited to handle heterogeneous or long-tail data that does not fit comfortably in a specialized repository. But, because repositories typically cannot assemble domain expertise across such a broad range of disciplines, this inclusiveness imposes limits on documentation requirements and validation. While Figshare and Zenodo do accommodate rich documentation, they require very little.Institutional repositories preserve and publish any kind of data generated by the research communities they serve, e.g., University of California researchers deposit data inthe Digital Archaeological Record (tDAR). A narrower example from the life sciences is the group of databases centered around model organisms, such asWormBase37 orFlyBase38; these databases aggregate diverse, but finite, data types and benefit from extensive domain expertise. Along similar lines, a data publisher may deal with a particular data-type, such as gene expression data in theGene Expression Omnibus (GEO) or seismological data inSeismicPortal. Focus on a particular type of data facilitates rigorous technical validation and development of specialized metadata requirements to ensure the data is useable. For instance, GEO data ingest meshes with Minimum Information About a Microarray Experiment (MIAME)39 documentation guidelines40. As a final example, a publisher might be devoted to a particular scientific instrument or facility, such as theOne Degree Imager Portal, Pipeline, and Archive (ODI-PPA) or theWorldwide LHC Computing Grid), the massive infrastructure built to handle the output of the Large Hadron Collider (LHC). Unlike most other publishers, these emphasize real time access to data coming off the instruments.Interest-based research communities are served by a thriving ecosystem of specialized data publishers. The broadest of these publishers serve entire disciplines, e.g.,Because researchers know the databases that serve their community, data in disciplinary repositories is easy to discover and because it is relatively standardized, it is easy to reuse. A disadvantage is that the data from a single research program can be distributed across many repositories , whereas an institutional or broad-scope repository can publish the whole research story.41 released aJoint Declaration of Data Citation Principles. The first of the eight principles states, in part, that “[d]ata citations should be accorded the same importance in the scholarly record as citations of other research objects, such as publications”. Most of the time, this means that when a published dataset contributes to a paper, it should be cited formally in the reference list.Data citation is the element of publication that has come the farthest toward consensus. In early 2014, a coalition of organizations brought together by Future Of Research Communication and E-Scholarship (FORCE11)42. Many data publishers provide no guidance on citation; others ask users to cite a proxy publication . However, a growing number of data publishers do supply users with explicit citation instructions; Dryad, Figshare, and Zenodo dataset landing pages all display a formatted citation and links for import into reference managers.Unfortunately, actual practice lags far behind this consensus. Not all article publishers allow data citations in the references and, even when permitted, most authors refer to data in the text without a formal citationMany data publishers facilitate formal citation by assigning unique permanent identifiers, most commonly the same ones used for journal articles: Digital Object Identifiers (DOIs). In addition to precisely specifying what resource is being cited, a DOI can be resolved to locate the referenced dataset. Note, however, that a DOI is neither sufficient nor necessary for citability, which demands that the referenced object be persistent and locatable via the citation. If a dataset moves and the DOI is not updated with the new location, the citation breaks. Conversely, a well-maintained web-address works as well as a DOI in theory– although a DOI is more likely to be maintained in practice.Committee on Data for Science and Technology (CODATA) recommendations43 and conveys all the information required to obtain aDataCite DOI44 or be listed in theThomson-Reuters Data Citation Index. The basic format works well when a dataset can be cited like an article, but that is not always the case.The present consensus is that a dataset should be cited using, at a minimum, five elements largely familiar from article citations: creator(s), title, year, publisher and identifier. This format agrees withdeep citation. When supporting an assertion in writing, it usually suffices to cite the entirety of an article or the page of a book and leave it to the inquisitive reader to find the relevant passage. But, to reproduce an analysis performed on a subset of a larger dataset, the reader needs to know exactly what subset was used . Datasets vary so widely in structure that there may not be a good general solution for describing subsets. The most common suggestion is to cite the entire dataset in the reference list and describe the subset in the text of the paper45. TheFederation of Earth Science Information Partners (ESIP) and theNational Snow and Ice Data Center (NSIDC) both recommend defining the subset in the citation itself, using a format suited to the dataset’s internal structure .One major complication data citation faces is the need forarXiv.org) are complicating the situation, but datasets are especially prone to bedynamic. Two kinds of dynamic datasets warrant consideration:growing datasets that add new data while never changing or deleting existing data, andrevisable datasets where data may by added, deleted, or changed.A second major complication arises when datasets change. In the past, the printing process cemented one version of an article as the version of record. Even for traditional scholarly literature, web-based publishing and preprint servers -Daily47 dataset. Or, consider WormBase, the genome database used by theCaenorhabditis elegans research community. WormBase encompasses genomic sequences ofC. elegans and 20 related species massively annotated with gene structures, protein sequences, expression patterns, and a host of other information from empirical data and computational predictions. Every two months, WormBase administrators respond to new data and better computational models by issuing a revised version with new material added and inaccurate material deleted or corrected.Consider USC00046336, a weather station at the Oakland Museum of California. Each day, the high temperature, low temperature and amount of precipitation recorded at the MuseumAdditions and updates to published datasets are extremely valuable, but a researcher seeking to reproduce an analysis of a dynamic dataset needs access to a particular version. To enable that access, previous versions must be preserved and citable. Growing datasets can be cited with an access date or a date range in the citation, as recommended by ESIP and NSIDC. Revisable datasets are more difficult; the most common approach is to accumulate revisions and periodically publish a new version with a citable version number. For example, WormBase identifies each release with a version number and makes all of the previous versions available.Digital Curation Centre (DCC), Dataverse, and the UKNatural Environment Research Council (NERC) insist that any change to a dataset should trigger a new identifier48. To handle the difficulties with dynamic data that this policy creates, the DCC recommends periodically issuing growing datasets a new identifier that refers to thetime-slice of new records and freezing versions of revisable datasets as individually-identifiedsnapshots.Controversy persists around the specific issue of identifiers for dynamic datasets. DataCite recommends, but does not insist, that their DOIs refer to immutable digital objects. NSIDC and ESIP instruct researchers to use a single identifier for growing datasets and include the access date in the citation; each major version of a revisable datasets gets a new identifier, but minor versions do not. In contrast, theThe difficulties surrounding deep citation and dynamic data could potentially be solved by turning the identifier-issuing process on its head. Instead of the dataset publisher issuing identifiers for data at the level that researchers seem likely to cite, researchers could issue identifiers for only the part of the dataset that they want to cite.Data Citation Working Group recently put forth a sophisticated proposal applicable to data in (or convertible to) databases. Identifiers created under this scheme would wrap together identification of a database, a query to return the cited dataset, the version of the database queried for this analysis, and a number of other useful components. The ultimate promise is to provide a simple yet precise citation for any selection of data, at the cost of technical complexity “under the hood”.The Research Data Alliance (RDA)Data validation is the least resolved aspect of data publication, and fundamental questions are still unanswered: What minimum level of quality should a published dataset guarantee? How and by what criteria can datasets be evaluated against that guarantee? How should dynamic datasets be handled? Is literature peer-review an appropriate model?et al. (2012)5 draw a useful distinction betweentechnical andscientific review. Technical review verifies that a dataset is complete, its description is complete, and that the two match up. Domain expertise is generally not required, and many repositories provide at least some level of technical review. Scientific review evaluates the methods of data collection, the overall plausibility of the data, and the likely reuse value. Scientific review does require domain expertise, making this level of validation more difficult to organize13. When data is published with a data paper, review may be split between the repository for technical review and the data journal for scientific review.Callaghan51. Open peer review atF1000Research and post-publication commenting atPubMed Commons are just two of many ongoing web-enabled experiments in article evaluation.Peer review guarantees that journal articles entering the scholarly record reach some level of validity . In many fields, peer-reviewed publications enjoy a much higher status than any other literature. Any effort to apply the prestige of “publication” to datasets cascades naturally into an effort to apply the prestige of “peer review”. But as data validation seeks to model itself on literature peer review, literature peer review itself is in flux52. Researchers are already over-whelmed by peer review of articles53 and could find any increased workload unreasonable. Despite all these difficulties, venues for peer-reviewed data papers are opening rapidly.Journal article reviewers traditionally consider whether the methods used are appropriate for the questions asked and the data collected support the conclusions drawn. In the absence of particular questions and conclusions, it is not obvious what peer review of data should certify. A dataset may serve for some purposes, but not for others and a reviewer may anticipate many potential uses for the data, but surely not allGigaScience, an exception, assigns technical review of the dataset to a separate data reviewer. The guidelines that various data journals provide to reviewers are fairly uniform, except that about half consider novelty or potential impact, while the rest only require the dataset to be scientifically sound. Although the guidelines are similar, review processes differ widely.Data paper journals wrap scientific peer review of the paper and the dataset together into a single process.Biodiversity Journal andScientific Data. Both journals divide reviewer guidelines into three sections along similar lines, whichBiodiversity Journal calls “quality of the data”, “quality of the description”, and “consistency between manuscript and data”.Scientific Data follows a traditional peer-review process: an editor appoints reviewers who are encouraged to remain anonymous. In contrast, review atBiodiversity Journal follows a flexible and open process featuring entirely optional anonymity and multiple types of reviewer. There, an editor appoints two or three “nominated” reviewers who must report back and several “panel” reviewers who read the paper and only comment at their discretion. Additionally, the authors may choose to open the paper to public comment during the review process.As an example, compareet al. (2011) propose a set of independent data peer review guidelines similar to the ones used by data journals3. Each of TheNational Aeronautics and Space Administration (NASA) Distributed Active Archive Centers (DAACs) draws on an affiliated User Working Group for domain expertise. The NSIDC combines an internal assessment of the effort that will be required to publish a dataset at a desired level of service  with an external assessment of scientific quality. ThePlanetary Data System (PDS) peer-reviews datasets via an in-person meeting with representatives of the repository, the dataset creators, and the reviewers.Data journals all model their data validation more or less faithfully on literature peer review, but independent data validation practices and proposals are considerably more varied. Lawrenceet al. (2010) suggest that “data use in its own right provides a form of review”, and go on to point out that the context of reuse demonstrates that the data is not simply “good”, but fit for some particular purpose52. The DANS repository solicits feedback from researchers who use its datasets: users are asked to rate the dataset on a one to five scale in each of six criteria 55. Researchers trust peer review in part because they understand the process and its limitations; if researchers come to understand them, alternate pre- or post-publication validation processes could potentially provide the same level of assurance.Pre-publication validation can be supplemented or replaced by post-publication feedback from successful or unsuccessful reusers. Parsons23. Each Open Context dataset is rated from one to five based not on qualityper se, but on the thoroughness of the validation; a one comes with no guarantees, a three has passed a technical review, and a five has passed external peer review. Whereas Open Context is a boutique publisher, focusing on data presentation and reuse, tDAR is a large repository primarily concerned with collecting and preserving archaeology data for future use. tDAR is able to operate at scale by performing only technical validation and streamlining data deposition with a minimum of mandatory description. However, tDAR also serves as a platform for high-quality data publication. The repository accommodates contributors who provide more information, and much of the content is deposited by digital curators who can be relied on to supply rich descriptions. Furthermore, two data paper journals,Internet Archaeology andJournal of Open Archaeological Data, recommend both tDAR and Open Context as repositories for their peer-reviewed data. Thus, data validation depends not only on discipline and data type, but on a host of external factors, including the goals of the organizations and researchers involved.Two examples from archaeology, Open Context and the Digital Archaeological Record (tDAR), illustrate the diversity of approaches to data validation. Open Context provides multiple validation processes that incorporate peer review beyond a simple accept/reject binaryConsensus abides wherever traditional scholarly publication offers a clear model for data; controversy churns wherever the literature offers only murky guidance. Static datasets of manageable size and simple structure can be made available, identified, and cited like the literature. Dynamic and complex datasets raise questions that attract multiple and sometimes conflicting answers. Where the guidance of the print metaphor threatens to give out, it must be extended creatively— or abandoned for another approach entirely.56 argue that thinking about data through the metaphor of print publication is often misleading. They advocate treating publication as only one metaphor in a larger ecosystem of metaphors for sharing data. For example, they associate the uniform, high-volume output from instruments like the Large Hadron Collider with industrial production and suggest “Big Iron” as an alternative metaphor for this kind of data.Parsons and Fox (2013)57. Here, one thinks of releasing a dataset like a piece of software and regards subsequent changes as analogous to updated versions. The open-source software community has already developed many potentially relevant tools for working collaboratively, managing multiple versions, and tracking attribution. Ram (2013)58 catalogs a multitude of scientific uses for the software version control systemGit, including data management. Open Context uses Git andMantis Bug Tracker to track and correct dataset errors. TheDat project “aim[s] to bring to data a style of collaboration similar to what Git brings to source code”. Furthermore, projects such asIPython Notebook integrate data, processing, and analysis into a single package. Unfortunately, scientific software struggles for recognition59 just as data does, so that metaphor offers little guidance for navigating the academic reward system. On the other hand, the publication metaphor targets this system explicitly, but leaves numerous other gaps.Another alternative metaphor that seems to be gaining particular traction is “data as software”data publication may come to refer to only those means of dissemination most directly drawn from the scholarly literature, or it may open as a canopy over a range of approaches. Whichever the case, it is our hope and expectation that for the foreseeable future, mixing of metaphors and contemplation of the unique properties of research data will continue to yield novel forms of data-centered scholarly production.Although some aspects of data publication have matured to a firm and useful consensus– exemplified most powerfully by the Joint Declaration of Data Citation Principles– the field as a whole is still burgeoning. Controversial issues, such as validation, may be best addressed by presenting an array of options rather than converging on a single solution. In the ongoing conversation, A nice rewrite and a very much improved paper, especially since it is now properly classified as a review article. Just a few small corrections listed below.Page 4, Para 5:"Writing a request to the creator should [very rarely] be part of the process" As noted before creator permission is sometimes legitimate.Page 5, para 2:"The most familiar kind of data publication is a traditional journal article accompanied by underlying data. " [citation needed] or change the sentence.Page 5, para 7"Data papers are predated by an approach that Lawrence et al. (2011) call data publication by proxy..." This is not true. As Hans Pfeiffenberger notes, ESSD dates back to 2008. Indeed I wouldn't be surprised if Lawrence chatted a bit with ESSD editors, Pfeiffenberger and Carlson, in preparing his paper.Page 6, para 1NSIDC does do external scientific reviews but they only go outside when they don’t have expertise in house. So it's sort of a combined approach. A quibble, but they pride themselves on in-house scientific expertise and engagement.Page 6 para 2:This paragraph is a little confused. Domain repositories don’t usually serve interdisciplinary use very well, but I don’t see how it’s necessarily bad to be distributed. What do you mean by publishing the whole research story? No one entity can do that.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. The article focuses on a topic that receives a lot of interest these days. Therefore it is very timely. The article provides a useful and valuable overview of the current state of affairs and the ongoing debate. The title does justice to the content of the article. So does the abstract.Mark Parsons and Peter Fox.This is the second version of the article. I do not see many changes in the text based on the earlier critical comments made byThe overview is very informative for everyone who needs a quick introduction into the subject. I do miss the opinion of the authors themselves on the issues at hand and on the quoted suggestions by others. This would have been appropriate in a concluding paragraph.Detailed comments:In the Introduction I miss a clear link between data publishing and data citation and creating the possibility for researchers to receive academic credits for their work on data. This academic credit is crucial as an incentive for researchers to put valuable time and effort in sharing their data.Why publish data? a reference to the Dutch fraud cases might be useful, as these cases got a lot of international attention and more or less triggered the discussion in the Netherlands with respect to research data management, long term preservation of data and data publishing and citation. A reference could be:In the paragraph International Journal of Digital Curation. 2013; 8(1): 229-243http://dx.doi.org/10.2218/ijdc.v8i1.256Doorn P, Dillo I, van Horik R: Lies, Damned Lies and Research Data: Can Data Sharing Prevent Data Fraud?Types of data publication a threefold model is introduced to categorize data publications. It is not clear how this model relates to the terminology and categorisation presented in theintroduction. This could be somewhat confusing for the reader.In the paragraphFurthermore, there are of course many other models available, e.g. that of the The Data Publication Pyramid, developed on the basis of the Jim Gray pyramid, to express the different manifestation forms that research data can have in the publication process:et al.: Report on integration of data and publications. October 2011. Located at: http://www.stm-assoc.org/2011_12_5_ODE_Report_On_Integration_of_Data_and_Publications.pdf Reilly S, Schallier W, Schrimpf S, www.knowledge-exchange.info/datametrics Or the model presented in the report: Costas, R., Meijer, I., Zahedi, Z. and Wouters, P. (2013). The Value of Research Data - Metrics for datasets from a cultural and technical point of view. A Knowledge Exchange Report, available fromhttp://www.trusteddigitalrepository.eu/Site/Trusted%20Digital%20Repository.html With respect to trustworthy digital repositories, I would like to add a few comments. First of all, in Europe a European Framework for Audit and Certification of Digital Repositories is emerging. It contains three certification standards  and three levels of certification  see:Of these three standards, only DSA has been up and running for some time now ,with 31 seals awarded and 30 ongoing self-assessments at this moment. The NESTOR seal has become available only very recently and the ISO standard is not yet officially available. The accompanying ISO 16919 standard: Requirements for bodies providing audit and certification of candidate trustworthy digital repositories, has been published very recently and now the ISO organization needs to be set up in the different countries, including the training of national auditors. The audits done by CRL are not fully official, since CRL is no formal ISO accreditation body.In Europe we see a growing interest in TDRs, coming from funders who want to push open data and data sharing and demand the deposit of publicly funded data in long term TDRs. Furthermore European research infrastructures and projects are also looking more and more into the issue of trust hen it comes to data sharing and a groeing number of them is incorporating (parts of) the DSA guidelines into there repositories and policies .https://www.icsu-wds.org/community/membership/certification Yet another certification procedure is offered by the ICSU/WDS to repositories that aim to become a member of the World Data System. See:The certification of TDRs could also help publishers/editorial boards with Data Availability Policies to point their authors to the right repositories for the long-term storage of their data.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Having made some similar comments myself I must agree with this review. But a few points may merit amendment:Abstract:Note that what 'publication' means is the same as in print as in digital form. It does not imply peer-review or editorial oversight in either format.Citability:Yes, data citations are important but some datasets and web-based resources do not show how they should be cited, some journals do not allow citations to web resources in the Reference list, and even were both possible, too many authors neglect to cite actual datasets and instead cite a web site (which may have many datasets) or a related print paper.I agree that a DOI is not enough and only permanent if it is updated when documents are moved. A full author-tile-publisher citation as you suggest is more informative and human readable.I do not think it is problematic to cite parts of datasets. Pages and chapters in books are already cited for example. In most datasets it is also possible to identify individual dat records. Also, the actual data used could be provided in an Appendix so the reader is left in no doubt. Neither do I think 'versioning' is a problem. Where new data are added (e.g. to a time-series) then they comprise a new dataset, as they would if published in print. Where many corrections are made they a dataset can be treated like a paper; i.e. the original can be 'retracted' and replaced, or the new version be published with the metadata stating that it is more accurate.You mention venues for peer-reviewed data papers. For this article to advance previous articles, perhaps it could expand on these venues and how they manage the details of the peer-review process?Biological Conservation, 173, 68-73. http://www.vliz.be/en/imis?module=ref&refid=234968Costello MJ, Wieczorek J. 2014. Best practice for biodiversity data management and publication.Biological Conservation 173, 155-165. http://www.marinebiology.ugent.be/component/imis/?module=ref&refid=230520Costello MJ, Appeltans W, Bailly N, Berendsohn WG, de Jong Y, Edwards M, Froese R, Huettmann F, Los W, Mees J, Segers H, Bisby FA. 2014. Strategies for the sustainability of online open-access biodiversity databases.Trends in Ecology and Evolution 28 (8), 454-461.http://dx.doi.org/10.1016/j.tree.2013.05.002Costello MJ, Michener WK, Gahegan M, Zhang Z-Q, Bourne P. 2013. Data should be published, cited and peer-reviewed.Marine Ecology Progress Series 316, 203-214.http://www.int-res.com/abstracts/meps/v316/Costello, M.J., Vanden Berghe E. 2006. “Ocean Biodiversity Informatics” enabling a new era in marine biology research and management.http://links.gbif.org/qa_ipr_advancing_biodiversity_data_publishing_en_v1.Costello MJ, Michener WK, Gahegan M, Zhang Z-Q, Bourne P, Chavan V. 2012. Quality assurance and intellectual property rights in advancing biodiversity data publications. ver. 1.0, Copenhagen: Global Biodiversity Information Facility, Pp. 33, ISBN: 87‐92020‐49‐6. Accessible atI have published a few papers you may find of interest:I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. General Comments:Note: This review was written by Parsons and accepted (with some modification) by Fox. Insights likely come from conversations between Fox and Parsons, errors from Parsons.why there is controversy in some areas and then use the evidence they have compiled to suggest a path forward.  They need to be more forthright in saying what data publication means to them, or what parts of it they do not deal with. Are they satisfied with the Lawrence et al. definition? Do they accept the critique of Parsons and Fox? What is the scope of their essay?I am very glad the authors wrote this essay. It is a well-written, needed, and useful summary of the current status of “data publication” from a certain perspective. The authors, however, need to be bolder and more analytical. This is an opinion piece, yet I see little opinion. A certain view is implied by the organization of the paper and the references chosen, but they could be more explicit. The paper would be both more compelling and useful to a broad readership if the authors moved beyond providing a simple summary of the landscape and examinedThe authors take a rather narrow view of data publication, which I think hinders their analyses. They describe three types of  data publication: Data as a supplement to an article; data as the subject of a paper; and data independent of a paper. The first two types are relatively new and they represent very little of the data actually being published or released today. The last category, which is essentially an “other” category, is rich in its complexity and encompasses the vast majority of data released. I was disappointed that the examples of this type were only the most bare-bones .  I think a deeper examination of this third category and its complexity would help the authors better characterize the current landscape and suggest paths forward.Some questions the authors might consider: Are these really the only three models in consideration or does the publication model overstate a consensus around a certain type of data publication? Why are there different models and which approach is better for different situations? Do they have different business models or imply different social contracts? Might it also be worthy of typing “publishers” instead of “publications”? For example, do domain repositories vs. institutional repositories vs. publishers address the issues differently? Are these models sustaining models or just something to get us through the next 5-10 years while we really figure it out?I think this oversimplification inhibited some deeper analysis in other areas as well. I would like to see more examination of the validation requirement beyond the lens of peer review, and I would like a deeper examination of incentives and credit beyond citation.I thought the validation section of the paper was very relevant, but somewhat light. I like the choice of the term validation as more accurate than “quality” and it fits quite well with Callaghan’s useful distinction between technical and scientific review, but I think the authors overemphasize the peer-review style approach. The authors rightly argue that “peer-review” is where the publication metaphor leads us, but it may be a false path. They overstate some difficulties of peer-review  while not fully considering who is responsible for what. We need a closer examination of different roles and who are appropriate validators . The narrowly defined models of data publication may easily allow for a conventional peer-review process, but it is much more complex in the real-world “other” category. The authors discuss some of this in what they call “independent data validation,” but they don’t draw any conclusions.Only the simplest of research data collections are validated only by the original creators. More often there are teams working together to develop experiments, sampling protocols, algorithms, etc. There are additional teams who assess, calibrate, and revise the data as they are collected and assembled. The authors discuss some of this in their examples like the PDS and tDAR, but I wish they were more analytical and offered an opinion on the way forward. Are there emerging practices or consensus in these team-based schemes? The level of service concept illustrated by Open Context may be one such area. Would formalizing or codifying some of these processes accomplish the same as peer-review or more? What is the role of the curator or data scientist in all of this? Given the authors’s backgrounds, I was surprised this role was not emphasized more. Finally, I think it is a mistake for science review to be the main way to assess reuse value. It has been shown time and again that data end up being used effectively  in ways that original experts never envisioned or even thought valid.we need to look more closely at who we are trying to incentivize to do what. There is no reason to assume it follows the same model as research literature publication. It may be beyond the scope of this paper to fully examine incentive structures, but it at least needs to be acknowledged that building on the current model doesn’t seem to be working.The discussion of data citation was good and captured the state of the art well, but again I would have liked to see some views on a way forward. Have we solved the basic problem and are now just dealing with edge cases? Is the “just-in-time identifier” the way to go? What are the implications? Will the more basic solutions work in the interim? More critically, are we overemphasizing the role of citation to provide academic credit? I was gratified that the authors referenced the Parsons and Fox paper which questions the whole data publication metaphor, but I was surprised that they only discussed the “data as software” alternative metaphor. That is a useful metaphor, but I think the ecosystem metaphor has broader acceptance. I mention this because the authors critique the software metaphor because “using it to alter or affect the academic reward system is a tricky prospect”. Yet there is little to suggest that data publication and corresponding citation alters that system either. Indeed there is little if any evidence that data publication and citation incentivize data sharing or stewardship. As Christine Borgman suggests,Finally, what is the takeaway message from this essay? It ends rather abruptly with no summary, no suggested directions or immediate challenges to overcome, no call to action, no indications of things we should stop trying, and only brief mention of alternative perspectives. What do the authors want us to take away from this paper?Overall though, this is a timely and needed essay. It is well researched and nicely written with rich metaphor. With modifications addressing the detailed comments below and better recognizing the complexity of the current data publication landscape, this will be a worthwhile review paper. With more significant modification where the authors dig deeper into the complexities and controversies and truly grapple with their implications to suggest a way forward, this could be a very influential paper. It is possible that the definitions of “publication” and “peer-review” need not be just stretched but changed or even rejected.Detailed comments:The whole paper needs a quick copy edit. There are a few typos, missing words, and wrong verb tenses. Note the word “data” is a plural noun. E.g., Data are not software, nor are they literature. Page 2, para 2: “citability is addressed by assigning a PID.” This is not true, as the authors discuss on page 4, para 4. Indeed, page 4, para 4 seems to contradict itself. Citation is more than a locator/identifierIn the discussion of “Data independent of any paper” it is worth noting that there may often be linkages between these data and myriad papers. Indeed a looser concept of a data paper has existed for some time, where researchers request a citation to a paper even though it is not the data nor fully describes the data (e.g the CRU temp records)Page 4, para 1: I’m not sure it’s entirely true that published data cannot involve requesting permission. In past work with Indigenous knowledge holders, they were willing to publish summary data and then provide the details when satisfied the use was appropriate and not exploitive. I think those data were “published” as best they could be. A nit, perhaps, but it highlights that there are few if any hard and fast rules about data publication.Page 4, para 2: You may also want to mention the WDS certification effort, which is combining with the DSA via an RDA Working Group:Page 4, para 2: The joint declaration of data citation principles involved many more organizations than Force11, CODATA, and DCC. Please credit them all (maybe in a footnote). The glory of the effort was that it was truly ajoint effort across many groups. There is no leader. Force11 was primarily a convener.Page 4, para 6: The deep citation approach recommended by ESIP is not to just to list variables or a range of data. It is to identify a “structural index” for the data and to use this to reference subsets. In Earth science this structural index is often space and time, but many other indices are possible--location in a gene sequence, file type, variable, bandwidth, viewing angle, etc. It is not just for “straightforward” data sets.Page 5, para 5: I take issue with the statement that few repositories provide scientific review. I can think of a couple dozen that do just off the top of my head, and I bet most domain repositories have some level of science review. The “scientists” may not always be in house, but the repository is a team facilitator. See my general comments.Page 5, para 10: The PDS system is only unusual in that it is well documented and advertised. As mentioned, this team style approach is actually fairly commonPage 6, para 3: Parsons and Fox don’t just argue that the data publication metaphor is limiting. They also say it is misleading. That should be acknowledged at least, if not actively grappled with.We have read this submission. We believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above. Thank you for refereeing our paper and thank you especially for delivering your report so quickly.We submitted the paper as a review article, not an opinion piece, and it was reclassified somewhere along the way.  I contacted an editor at F1000 about the issue, and I believe it will be switched back shortly.  While there is undoubtedly a viewpoint inherent in the way we have organized the manuscript, it was our intention to deliver a timely summary of the current landscape as a foundation for future thinking, not to offer prescriptions or to endorse particular approaches.  We have no shortage of opinions about data publication, and a true opinion piece may follow at some point, but our aim here was to remain fairly neutral.  I think the paper you are asking for would also be valuable, but it's an entirely different paper from the one we have written.That said, your report is full of suggestions for expansion of analysis and clarification of scope that would absolutely improve the paper (e.g. the question of why some issues resist consensus more than others is an excellent one), and we will certainly address them in the next version.


Famed microbiologist René J. Dubos (1901–1982) was an early pioneer in the developmental origins of health and disease (DOHaD) construct. In the 1960s, he conducted groundbreaking experimental research concerning the ways in which early-life experience with nutrition, microbiota, stress, and other environmental variables could influence later-life health outcomes. He also wrote extensively on potential health consequences of a progressive loss of contact with natural environments (now referred to as green or blue space), arguing that Paleolithic experiences have created needs, particularly in the mental realm, that might not be met in the context of rapid global urbanization. He posited that humans would certainly adapt to modern urban landscapes and high technology, but there might be a toll to be paid in the form of higher psychological distress (symptoms of anxiety and depression) and diminished quality of life. In particular, there might be an erosion of humanness, exemplified by declines in altruism/empathy. Here in the first of a two-part review, we examine contemporary research related to natural environments and question to what extent Dubos might have been correct in some of his 50-year-old assertions. Human beings can almost certainly survive and multiply in the polluted cage of technological civilization, but we may sacrifice much of our humanness in adapting to such conditions…The maintenance of biological and mental health requires that technological societies provide in some form the biological freedom enjoyed by our Paleolithic ancestors”.“Life Magazine, 1970  is dependent not only on other human beings and on the physical world but also on other creatures—animals, plants, microbes—that have evolved together with him. Man will ultimately destroy himself if he thoughtlessly eliminates the organisms that constitute essential links in the complex and delicate web of life of which he is a part” [“ a part” .As we transition our discussions toward other potential evolutionary mismatches  in Part II, we conclude Part I with the topic of biodiversity. Dubos had much to say concerning the loss of biodiversity and forewarned that discussions of biodiversity loss should not be privileged by select species that are emotionally favored by humans. Even the lowly microbe was as relevant as the Giant Sequoia in his biodiversity discussions:benefits of local biodiversity may also be without conscious realization. For example, research has shown that as it relates to human health and well-being, the benefits of urban green spaces appear to be related to the extent of their overall biodiversity [Of course, rapid urbanization is a significant driver of global biodiversity loss . In turniversity -273.Remarkably, when humans hear birdsongs in the background of an experimental setting in which they are tasked with rating urban environments, their appreciation for scenes of urban landscapes is increased along a gradient coincident with the diversity of audible birdsongs . We havemissing more than merely green/blue space, natural sounds, and light at the right time. The ability of green spaces to facilitate social contacts is an important consideration [less likely to engage in excessive screen time [missing in the modern landscape vs. our ancestral past—diversity of microbes and traditional dietary patterns.Emerging studies certainly support Dubos in his contention that revisiting certain “Paleolithic experiences,” at least the more pleasant ones (vs. those that might have helped develop our efficient fight or flight response), could have a positive influence on metropolitan quality of life. However, the modern urban environment may be deration . Childreeen time ; therefobios (life), philia (love)) is a 20th century neologism that was “coined” in the 1980s. However, the term biophilia appeared in many 19th century medical and psychology dictionaries as meaning not only love of life but also the instinct for self-preservation common to man and the lower animals [It is commonly stated that biophilia (Greek— animals . It was Forest and Stream and Dog Fancier [Biophilism means the love of life. The love of what sort of life”? Adams queried in a 1907 article [out of self love one should come into…love of humanity, out of love of humanity into love of all sentient things. When he has so far evolved, he is a biophilist. As there may be born a poet, so there may be born a biophilist”. However, Adams argued that although birth can provide the ingredients for biophilism, it could only be realized if the innate powers, as he called them, were “more than drawn out. They must be developed, trained” through experience.In 1895, Adams formed a “Bureau of Biophilism”, which included the well-known naturalist John Burroughs, poets Henry Abbey and Eugene Field, dog expert Eugene Glass, et al. . Writing Fancier ,280, Ada article , answeriper se, others did so for him. For example, in 1969 scholar Michael McGrath interpreted Fromm’s biophilia [A simple form of biophilous behavior is that of plants leaning toward the source of sunlight…biophilia confirms and promotes life. The biophilous person produces rather than destroys, creates rather than hoards. He is more interested in living things, such as nature and other people, than he is ‘dead’ things such as sports cars and spaceships”.References to biophilia and biophilism waned until the mid-20th century when psychologist Eric Fromm provided some renewed enthusiasm for the term as it pertains to mental state. Although Fromm made little reference to nature or the environment iophilia  in a wayThe New York Times—“Our deepest needs stem from ancient and still poorly understood biological adaptations. Among them is biophilia: the rich, natural pleasure that comes from being surrounded by living organisms, not just other human beings but a diversity of plants and animals that live in gardens and woodlots, in zoos, around the home and in the wilderness” [biological joie de vivre” that could be obtained through solidarity with other forms of life.…the essential factors of biological joie de vivre exist in every human being because they are inscribed in the genetic code. In fact, this aspect of life has probably not changed significantly since the Stone Age…the purely biological enjoyment of life can, in addition, evolve into a more subtle experience of universal fellowship with all other human beings and even with other forms of life…ever since the Stone Age, and in all parts of the world, human beings have expressed their awareness of solidarity with other forms of life….” [Said Dubos—“ life….” .Biophilia, as in the love of all life on Earth, was subsequently positioned in the early 1970s as a potential benefit to environmental conservation . In 1979derness” . Dubos,


A universal Tree of Life (TOL) has long been a goal of molecular phylogeneticists, but reticulation at the level of genes and possibly at the levels of cells and species renders any simple interpretation of such a TOL, especially as applied to prokaryotes, problematic. One of the several ways in which microbiology puts the neo-Darwinian synthesis in jeopardy is by the threatening to “uproot the Tree of Life (TOL)” . LateralThe Origin of Species was a nontheistic reason for the discoverability and utility of such classifications. “Community of descent is the hidden bond which naturalists have been unconsciously seeking, and not some unknown plan of creation,” he wrote [Before 1859, hierarchical (tree-like) patterns of organismal relationships were commonly drawn and taken to mirror some natural order, most likely divine [he wrote . There whe wrote . Baptesthe wrote .After Darwin, classifications were most often assumed without proof to be evolutionary: phenetics was taken to be identical to phylogenetics. As De Querioz noted, “…the relationships expressed in existing taxonomies were merely reinterpreted as the result of evolution, and evolutionary concepts were developed to justify existing methods” . Not mucIn the mid-1960s, molecular sequencing  appeared to offer a way out of such circularity, a possible independent proof of the TOL hypothesis, some thought. Emile Zuckerkandl and Linus Pauling wrote:“…molecular phylogenetic trees should in principle be definable in terms of molecular information alone. It will be determined to what extent the phylogenetic tree, as derived from molecular data in complete independence of organismal biology, coincides with the tree constructed on the basis of organismal biology…”And thus,“…If the two trees are mostly in agreement with respect to the topology of branching, the best available single proof of the reality of macro-evolution would be furnished” .This made a lot of sense at the time. The way in which genes replicate and mutate is, barring recombination, tree-like. One consequence is that ancestral nodes in a tree constructed from gene sequences are interpreted as corresponding to real ancestors . Nothing like that would necessarily be the case for trees based on “organismal biology,” that is, on phenotypic similarities and differences. If evolution were not the cause of phenotypic similarities and differences, then phenetic classifications would be like those used to order books in a library: all the books on Canadian cuisine might (arguably) belong on the same shelf, but no one would claim that they descended from one first book on that subject. Nodes in such a phenetic classification need not represent ancestors .So, agreement between trees would indeed have been some sort of “proof” of Darwin’s TOL hypothesis, with two caveats. The first is that no widely accepted prokaryotic tree “constructed on the basis of organismal biology” was actually available for comparison: microbiologists had given up the attempt to make one in the mid-1950s, and no one since has been foolish enough to reboot the effort. The second is that agreement of molecular and organismal trees is not really a disproof of the theistic explanation Darwin wanted to supplant. Any sensible creator would surely use similar genes to make similar organisms.The molecular phylogenetic tree-making enterprise has grown more spectacularly than Zuckerkandl and Pauling could have dared hope, and, in particular, the use of small-subunit ribosomal RNA (ssu rRNA) as “molecular chronometer” has revolutionized systematics, most importantly making it possible to put all prokaryotes and all eukaryotes into a single universal TOL. The story of how Carl Woese courageously pioneered the use of this molecule has been often told ,11. And Thermotoga maritima had been transferred from Archaea [That LGT might be a spoiler for the TOL was only a suspicion at the beginning of the era of molecular phylogenetics. Japanese clinical microbiologists found in the early 1960s that antibiotic resistance could spread between bacterial species via “resistance transfer factors,” now called plasmids . But at  Archaea  stunned “…different genes give different trees, and there is no fair way to suppress this disagreement, then a species (or phylum) can ‘belong’ to many genera (or kingdoms) at the same time: There really can be no universal phylogenetic tree of organisms based on such a reduction to genes” .A decade and a half of prokaryotic tree-making has not produced general agreement on just how much LGT there is, other than “much more than we expected,” although there have been many serious attempts . Indeed,The complexity hypothesis is the notion that genes whose products interact with the products of many others will have so many coevolved molecular dependencies that function in a distantly related cellular environment is impaired. “Connectivity” (number of protein–protein interactions), not functional category, is in fact the key determinant , and thePuigbo et al. ,22 have Escherichia coli , the average strain carries about 5,000 genes. Genes shared between all or almost all strains number little more than 3,000, but the number of gene families with a representative in at least one E. coli genome is approaching 100,000 [Prochlorococcus, the world’s most plentiful organism and most important oxygen-provider, shows an average genome content of only about 2,000 genes but a pangenome calculated at 85,000, so far [Most gene families are not among the NUTs, however, and even within a designated species, a sizeable fraction of any genome participates in rapid gene loss and gain (by LGT). The pangenome concept, which aims to describe the gene repertoire of a bacterial species by comparing gene contents of several to many of its strains, supports this notion. A typical bacterial genome comprises a “core” of genes present in all or nearly all of the strains of its species and often many more “dispensable” or “accessory” genes  present  100,000 ,25. Proc, so far ,27. Arch, so far , and we According to a “strong version”  of the pAs we go deeper than species into the TOL, the fraction of vertically inherited genes can only get smaller. In an influential 2009 analysis, Lapierre and Gogarten extended and deepened the pangenome analysis to 573 bacterial genomes spanning the then available diversity . The corWhat, then, did LUCA’s genome contain? At one extreme, one might imagine that all contemporary gene families have their coalescents (roots) or direct ancestors thereof, in the genome of LUCA. On this model, either (i) that genome was large, and descendant lineages have differentially lost gene families, or (ii) many important and widely distributed gene families have evolved since LUCA and are not detectably homologous to other gene families with which they share common origins. Mixtures of (i) and (ii) might also be entertained.At the other extreme, one could hold that LUCA as a cell had a “normal” or even smallish prokaryotic genome  with only 100 or so genes (represented in NUTs) that might potentially have been passed down directly to all or almost all contemporary genomes. This would be a “uniformitarian” model, explaining the past in terms of processes familiar from the present. In all descendant lineages, the majority of LUCA’s genes will have been replaced via LGT—from closely related and distant lineages of other genes, homologous or not, carrying out the same or quite different cellular functions . A key difference from the first model is that some contemporary gene families will have had coalescents that predate LUCA –37. ThatMore explicitly, according to the second model, the fraction of any particular contemporary prokaryote’s genes that have been strictly vertically inherited along a lineage of replicating genomes tracing all the way back to LUCA would comprise a universally conserved core (roughly the NUTs) plus “character genes” defining its metabolic lifestyle—methanogenesis genes if both LUCA and the contemporary prokaryote were methanogens, for instance. If the contemporary prokaryote we picked was instead a cyanobacterium while LUCA was methanogenic, non-core shared genes would be substantially fewer. Given that even within the NUTs there is some incongruence of trees, the fraction of a randomly chosen or “average” contemporary prokaryote’s genes that have been inherited only vertically since LUCA could easily be only a small percentage.A third model, favored by some, is to redefine LUCA as a community, not a single cell or species ,39. AlthIf one assumes, almost as an entailment of Schleiden and Schwann’s cell theory, that all cells derive from previous cells, then it could be the case that there is a single tree-like pattern relating all cells, although one would need to look up to the level of “species” in lineages where sex became a reproductive necessity. Although incongruence of gene trees due to LGT means that no single one can be taken as topologically equivalent to such a tree of cells and species, the STOL might still be the best (though not a guaranteed) proxy for it. Patrick Forterre endorses this common view when he writes:“The universal tree should depict evolutionary relationships between domains defined according to the translation apparatus reflecting the history of cells (and their envelope) and not according to the global genome composition that is influenced by LGT, virus integration and endosymbiosis, the history of which is incredibly complex” .But we might also ask what warrant there is to believe in such a tree-like history of cells, coupled or not to molecular phylogenies. Reticulating events that would compromise trees at the cellular level are occasional or regular whole-cell fusions, mixing entire genomes and, more contentiously, conjugation and the compromising of cellular integrity represented by phage attachment or transformation. These latter introduce only a little genetic material each time, but when summed over many events, can replace every gene: the argument would be over whether the pattern of material as well as genetic relationships might be seen as non-tree-like.Interspecies whole-cell fusion resulting in heterodiploid cells does occur in haloarchaea  but is pSo, even a tree of cellular lineages is not an unproblematic concept. Students of animals and plants have long accepted that incomplete lineage sorting, introgression, and full-species hybridization pose difficulties for the sorts of trees that Darwin might have had us draw. But it is microbes, with their promiscuous willingness to exchange genes between widely separated branches of any “tree,” that have most seriously jeopardized the neo-Darwinian synthesis, in the oversimplified form that we have often presented it to the public . More so


Conversations with R. D. Laing, B. Mullan). Nonetheless, despite the commonly perceived demise of ‘anti-psychiatry’, with which Laing was associated, the PA has survived nearly 50 years and still runs two community houses. In this book, Bruce Scott, a member of the PA, where he did his psychoanalytic psychotherapy training, offers the testimonies of 14 people who have lived in a PA household. These were obtained mostly by face-to-face interviews or by questionnaire.R. D. Laing and others founded the Philadelphia Association (PA) in 1965. The PA provides community households where people with emotional difficulties can live with others. The first ‘official’ community was the infamous Kingsley Hall, a ‘counterculture’ centre in the East End of London, which after 5 years was largely trashed and uninhabitable. In retrospect, Laing admitted that it was not a ‘roaring success’ (docta ignorantia or the doctrine of learned ignorance, a concept used by Nicolas Cusanus in the 15th century to recognise the limits of knowledge. For Scott, this is a path to health practised by the PA communities. However, there is little discussion about whether such neutrality is attainable. I am uncertain whether Scott’s search for an ‘anti-method’ is anything more than being pragmatic. The testimonies commonly mention the lack of structure in the households. I have no problem with mystery and perplexity and I totally agree with an anti-materialistic stance for dealing with mental distress. The PA rightly wants to avoid the objectification of people with mental health problems. Helping them find their own way is not easy.Scott sees the PA communities as providing true asylum, in the sense of an ‘inviolable place’. There is no discussion, however, about whether such asylum is possible if the person is detained under the Mental Health Act 1983. My guess is Scott would say not. He makes a case for This book describes the tension between ‘going to pieces’ and being helped to ‘come back together again’. Regression and psychosis can be mechanisms of healing and re-adaptation, as noted by Donald Winnicott among others. The PA continues to explore these areas, as does this book, but it may be increasingly difficult to find space for them in a bureaucratic society.


The Phonological Mind thesis (d thesis ,b on log The Phonological Mind thesis  I openly acknowledge. But Everett’s superficial reading of the scientific literature and his incendiary rhetoric do not challenge this hypothesis.I believe Everett’s concerns are unfounded. Everett’s broader objections to cognitive nativism are rooted in an erroneous conflation of explanations at the cognitive and biological levels, an implausible view of the links between the cognitive phenotype and the genotype, and a disregard for a large experimental literature that counters his assertions. Similarly, in his attack on The Phonological Mind thesis are discussed in the final section. While my reply focuses mostly on the arguments in Dark Matter of the Mind, of which My reply proceeds as follows. I first consider Everett’s broader critique of cognitive nativism and address his logical and methodological concerns about the falsification of nativist claims and their congruency with genetic and evolutionary evidence. Having established some ground rules for testing the core knowledge hypothesis, I proceed to consider the evidence for innate phonological constraints by evaluating the empirical evidence for UG in a particular case study—the restrictions on syllable structure. Everett’s remaining arguments against To appreciate Core knowledge theory articulates a cognitive hypothesis regarding the origins of knowledge  have no effect on behavior; (b) emanate from extraneous sources, external to the domain in question; or (c) are induced  by tracking the statistical or structural regularities in the child’s experience. In the specific case of phonology, the hypothesis that a principle P forms part of a core phonological system  would be falsified by either showing that the preference attributed to P is inactive (1) (a), or by showing that it is neither linguistic or innate .(1)Falsifying the core knowledge hypothesis. The hypothesis that a principle P forms part of core knowledge of phonology (UG) will be falsified by showing that(a)P is inactive.(b)P emanates from extraneous non-phonological sources .(c)P is induced  by tracking the statistical or structural regularities in the child’s experience.in principle; I am not concerned with whether the ONSET hypothesis is correct.To illustrate how one can apply these conditions, let us consider in detail one specific example, concerning the putatively universal constraint on syllable structure  that requires syllables to have an onset . Accordingly, syllables like (2)ONSET: Syllables must have onsets.ap, e.g., ap.pen.dec.to.my) would not necessarily establish that fact. In modern phonological theory . Some authors have argued that Arrernte presents precisely this case . Notice that counter-examples . ONSET presents one such putative constraint. By hypothesis, the ONSET constraint is abstract, so its effect should be independent of the articulatory and acoustic demands associated with the production and perception of specific sounds in a given context , their modality of presentation , and the state of sensorimotor systems . Demonstrating that phonological principle P can be subsumed by sensorimotor constraints would falsify the hypothesis that P forms part of the core knowledge system of phonology.Another way to falsify ONSET is to show that the l system ,b. But cpa (over ap) required experience with syllables like pa, ba, ma, etc. As in the case of sensorimotor correlates, the role of experience must be interpreted with caution. And indeed, the (un)learnability of P does not mean that its acquisition requires no experience at all. It is trivial to show that, absent some minimal triggering conditions, language will not emerge normally. Similarly, absent experience with speech, deaf individuals will develop a sign language, whose phonology is distinct from that of hearing speakers. Experience, then, clearly plays a critical role in triggering the unfolding of the putative phonological phenotype . The hypothesis that certain phonological primitives and constraints are innate cognitive traits . In his view, however, the list of methodological requirements for demonstrating core knowledge is more extensive (see 3). In particular, Everett imposes restrictions on the range of admissible experimental methods, and on the genetic and evolutionary conditions for demonstrating core knowledge. I consider these three objections in turn.(3)Everett’s conditions for demonstrating that principle P forms part of a core knowledge Demonstrate the role of P in infancy by relying on methods “more sound than babies’ sucking or eye-movements.”(b)“Keep genetics and epigenetics  separate.”(c)Provide a plausible account for the evolution of the trait.Any response to contrasting stimuli—be it manual button press, looking time or neural activity—can only be linked to cognitive structure if those stimuli are matched for all other relevant dimensions. The critical challenge for making such inferences is the control of stimuli, not the modality of response. However, Everett does not show that such controls are lacking in any of the hundreds of studies that employ this procedure. In fact, none of these experimental results is reviewed with any detail. In any case, the evidence for core knowledge in infancy is not limited to looking time or sucking methods. For example, near infrared spectroscopy shows that the brain activity of neonates is modulated by the syllable hierarchy  separate.” To illustrate the logical difficulties inherent in the notion of innate knowledge, Everett considers the “pro-drop” parameter . By his account, each of the two settings of the parameter  must each be associated with different genes. Accordingly, if the “pro-drop” parameter were truly innate, then this knowledge must be “located somehow, somewhere in the human genome” (p. 2), and consequently, one would have expected these two settings to doubly dissociate: some genetic mutations should have selectively impaired the acquisition of a “pro-drop” language, but spared a language that lacks the “pro-drop” option; other mutations should have produced the complementary pattern. However, no such dissociations are reported. Beyond this empirical challenge, Everett is concerned that the hypothesis of innate knowledge presents an inherent contradiction. If knowledge  is genetically coded, then it must be subject to mutations, which would ultimately prevent certain languages from being learnable. In the case of the “pro-drop” parameter, Everett would predict that some language learners should be genetically predisposed toward favoring the “drop” option, whereas others (those carrying the opposite parameter setting) should be predisposed toward learning languages that do not drop their subject. The result is that “not all people may be able to learn every language” (p. 2). Put differently, if UG is innate, then it cannot be universal.However, there are a number of fallacies in this logic. First, innateness and universality are not an oxymoron. Humans are innately equipped with two eyes, yet this trait does not become abruptly extinct  in the population by sudden spontaneous mutations. This is because innate traits are buffered by homeostatic mechanisms that seek to detect and correct replication errors in the genome, as well as cell and tissue malfunctions during embryonic development. These checks and balances are not infallible. Accordingly, rare genetic abnormalities or developmental problems  could prevent the typical acquisition of universal grammar, just as they can result in a single “cyclopean” eye in human fetuses . Such ragenotypes and phenotypes. Core knowledge  concerns properties of the cognitive phenotype—the putative set of cognitive principles that are somehow represented in the brains of individual speakers; this is not conceptually identical to the genotype of these individuals , nor are genotypes and phenotypes necessarily related in a one-to-one fashion. By hypothesis, the tendency of humans to converge on a cognitive phenotypic trait is constrained by their genome, but the links between the phenotype and genotype are complex. For example, the “blue eye” and “brown eye” phenotypes are not expressed on distinct genes; rather, eye color is a complex genetic trait that is linked to multiple single nucleotide polymorphisms that do not sum up in a linear, additive fashion  must doubly dissociate. Everett predicts such dissociations because he believes that distinct innate principles  must be “localized” in distinct bits of DNA. But this requirement is based on a misunderstanding of the relation between on e.g., . Likewison e.g.,  as well on e.g., . Languagonly at the level of analysis to which they apply  core knowledge is vacuous or untestable. Rather, these facts remind us that innateness is a multifaceted problem that can be evaluated at different levels of analysis. Genetics and the cognitive sciences represent two very different levels. Critically, it is both unreasonable and biologically unrealistic to expect direct, one-to-one mapping across these levels . The proey apply , and in prerequisite for establishing that core knowledge exists. To reiterate, the core knowledge hypothesis is first a claim concerning the synchronic cognitive state of individual speakers. We now turn to evaluating the empirical evidence for its support in the case of phonology.Everett’s final condition, his demand for a complete evolutionary history of core knowledge, is another such diversionary tactic. Everett is of course right to urge us to explore the evolution of core  knowledge—a question The Phonological Mind examines the origins of phonological primitives and constraints by reviewing the empirical evidence in multiple case studies using a broad interdisciplinary perspective, informed by linguistic analysis, behavioral experiments with adults and children, and neuroimaging studies. In most of these cases, the conclusions are unclear—a fact that I openly acknowledge (contrary to Everett’s assertions). One such case, however, has been the subject of systematic investigation that directly pits the UG account against various non-linguistic explanations (per the requirements in 1a-c above). Accordingly, this case features prominently in bla, with stop-liquid onsets, are preferred  relative to bna , which, in turn, are preferred to bda (two stops); least preferred are syllables like lba ; together those preferences give rise to a syllable hierarchy (see 4). Such preferences have been documented statistically in the distribution of these syllables in language surveys The syllable hierarchy: blif>bnif>bdif>lbifBox 1; see also Box 1). His exposition of the linguistic literature  of 4), followed by liquids , nasals  and obstruents . Using these levels, one can calculate the sonority distance in the onset by subtracting the sonority level of the first onset consonant from that of the second . Accordingly, syllables like bla exhibit a large rise in sonority (s = Δ2) and bna exhibits a smaller rise (Δs = 1), whereas lba exhibits sonority fall (Δ2 = -2). Indeed, as the sonority cline decreases, the syllable becomes underrepresented across languages The sonority distance in complex onsetssonority sequencing generalization (SSG). The SSG states that onsets must rise in sonority, whereas codas must exhibit a sonority fall. A related principle, the minimal sonority distance, states that languages restrict the minimal sonority distance they allow; English, for instance, requires a rise of at least two steps, so it allows syllables like bla (Δs = 2), but bans syllables like bda (Δs = 0). This observation is captured by a constraint on syllable structure known as the bwa, or account for the aversion to syllables like /ji/ across languages. However, these observations are fully in line with the SSG. Considering the English ban on bwa, Everett is right to note that the SSG should render such a syllable well formed in English . However, this does not show that the SSG is wrong. Indeed, no single phonological constraint can single-handedly capture the entire phonology. In the case of bwa, its avoidance is due to an independently motivated constraint that bans adjacent identical features , however, are known counterexamples to the SSG. Since English typically requires its syllables to exhibit a rise of two steps in sonority, plateaus such as spot should have been unattested. While this fact is amenable to a formal explanation Other syllable hierarchies predicted by the SSG:(a)mla>mda(b)fsa>ftamlif over mdif). Similarly, a more detailed  over ftik . These results are borne out by experimental evidence , as well as the related hierarchies (see 6) is the product of universal grammatical constraints .bnif to bdif, and bdif to lbif despite the fact that none of these syllable types exists in their language? To the extent that such preferences are detected, we next examine whether they result from universal grammatical constraints, or from various non-grammatical sources—auditory, articulatory, or lexical.Our research program proceeds in two steps. First, we ask whether speakers are sensitive to the structure of syllables that they have never heard before. For example, do English speakers favor (7)Testing the syllable hierarchy:(a)Ill-formed syllables are systematically misidentified—the worse formed the syllable, the more likely its misidentification.(b)The misidentification of ill-formed syllables is inexplicable by non-grammatical sources, including:(i)Auditory/phonetic failure(ii)Articulatory difficulty(iii)Similarity to familiar syllablesgrammatical repair. We reason that, if all grammars universally encode the syllable hierarchy, then ill-formed syllables will not be represented faithfully. Instead, ill-formed syllables  will be recoded  by the grammar as better-formed syllables . Repair, then, can potentially provide a litmus test for the ill-formedness of a syllable. And if ill-formedness depends on the syllable hierarchy, then this hierarchy should determine the likelihood of repair—the worse formed the syllable, the more likely its repair, hence, its misidentification. These predictions are borne out by numerous studies with speakers of various languages. Figure 2 summarizes results from speakers of English . In particular, syllables like lbif could be misidentified because people fail to extract their phonetic form from the auditory signal . These findings from neonates agree with the outcomes from an imaging study with adults . Together, these results suggest that syllable structure is constrained by abstract grammatical principles that are broadly shared across languages, possibly universally. The repair of ill-formed syllables results from their violation.Finally, several studies counter the lexical analogy explanation—the possibility that h adults  showing attempted to address any non-grammatical explanation for the results. Instead, his exposition reduces the experimental logic ad ridiculum to the following: if people misidentify lbif, ergo, the SSG is an instinct.Given the large experimental literature that has examined the syllable hierarchy, one would expect a critique to scrutinize the experimental logic, methods, statistical analysis or results of specific studies. However, Patient readers must endure the bulk of his critique to learn that the actual rationale guiding the experimental investigation is far more nuanced, and those non-phonological  sources for the syllable hierarchy have been carefully considered and evaluated experimentally. Even then, however, Everett’s description hardly does justice to the research program as a whole. For example, he briefly acknowledges that the syllable hierarchy has been replicated in silent reading (contrary to the auditory/phonetic account), but then immediately moves to dismiss these results on grounds that “we know too little about the relationship between speaking and reading” , p. 7. T...in looking at new words speakers often try to create the phonology in their heads and so this “silent pronunciation” could guide such speakers’ choices, etc. Everyone (modulo pathology) has roughly the same ears matched to roughly the same vocal apparatus. Thus although phonologies can grammaticalize violations of functionally preferable phonotactic constraints, one would expect that in experiments that clearly dissociate the experimental data from the speaker’s own language, the functionality of the structures, e.g., being auditorily easier to distinguish, will emerge as decisive factors, accounting for speakers’ reactions to non-native sequences that respect or violate sonority sequencing, etc. In fact, there is a name for this, though with a somewhat different emphasis, in Optimality Theoretic Phonology  – the “eThis passage is striking for various reasons. First, it is puzzling to see the liberty Everett takes in dismissing the huge literature on reading, which suggests  that speakers are acutely sensitive to the phonological structure of printed words . Alternatively, perhaps the syllable hierarchy reflects principles that are inferred on the fly. Everett implies that a single encounter with an unfamiliar stimulus results in the emergence of phonological constraints, a phenomenon he attributes to the The Emergence of the Unmarked , not the evidence for the hierarchy itself, and for the most part, his formal objections are erroneous. His only objection to the experimental findings is based on an incoherent model of silent reading for which there is no support. I thus conclude that Everett’s attack on the syllable hierarchy is unfounded.Anticipating the shortcomings of his own attack on the syllable hierarchy, Everett declares that even if the SSG were to be replaced by more adequate formal principles, the “core knowledge” hypothesis would still crumble. This is because “the evidence she (IB) provides for an instinct fails no matter what principle she might appeal to” (p. 7). In support of this assertion, Everett submits that all other hallmarks  of core knowledge in phonology need not arise from any innate universal principles. Specifically, he asserts that algebraic rules can be learned from experience, and that the properties of phonological systems  can all be traced to sensorimotor, rather than phonological pressures. The regenesis of signed phonological systems, in Everett’s view, is irrelevant to spoken phonology, and the early onset of spoken phonology simply reflects rapid learning. Finally, scaffolding  is simultaneously false and non-specific to phonology. Once again, however, Everett’s anti-nativist fervor clouds some critical scientific nuances.(8)Other evidence against core knowledge of phonology:(a)Algebraic rules are learned from experience.(b)The unique, shared design of phonological systems, their early onset in development and their spontaneous regenesis are all explained by sensorimotor pressures, not principles specific to phonology.(c)Regenesis establishes a false analogy between signed and spoken phonology.(d)The early onset of phonology reflects early learning.(e)Scaffolding is both false and not specific to phonology.The Phonological Mind (see 9).Everett’s attack on algebraic rules conflates two very different hypotheses about (a) the computational properties of linguistic rules  and (b) the origins of some rules , which together form the thesis of (9)The Phonological Mind thesis:(a)The algebraic hypothesis (Computation): The phonological grammar consists of algebraic rules.(b)The universal grammar hypothesis (Origins): Some grammatical primitives and constraints are innate.b or k), such that all category members are treated alike . Furthermore, the grammar encompasses mechanisms that operate over entire categories using variables  and, consequently, grammatical rules can encode abstract relations among categories . For example, the ∗XXY rule (where X and Y stand for any two consonants) bans any XXY form, that is, any tri-consonantal structure with identical consonants at its beginning, regardless of whether these consonants are familiar or novel. The hypothesis that some grammatical rules are innate  is a second hypothesis that is logically distinct from the algebraic hypothesis. Everett attacks the algebraic hypothesis because algebraic rules, such as the Semitic ban on XXY stems  rather than their members . This distinction becomes particularly significant in light of Everett’s subsequent argument that phonological pressures are sensorimotor. Obviously, if phonological systems were to directly reflect analog sensorimotor pressures, then, ipso facto, such systems could not possibly be phonological ; they would be sensorimotor. Nonetheless, Everett is right to note that many phonological principles “conspire” to favor structures that optimize sensorimotor pressures. The Phonological Mind captures both the distinction between these two systems (phonology and the sensorimotor system) as well as their convergence. The distinction between the phonology and the sensorimotor systems is explained by the hypothesis that the two systems are distinct, and they differ in their computational properties. Their convergence is explained by the hypothesis that sensorimotor pressures shape the design of the phonological system in phylogeny . To reiterate, the correlation between phonology and sensorimotor pressures does not necessarily mean causation affecting on-line, language processing.The algebraic hypothesis is critical for two reasons. First, it explains productivity—the capacity of the grammar to generalize phonological principles across the board, to any member of a class . Second, it allows one to draw a principled distinction between the  phonological grammar, and the  phonetic and sensorimotor systems  and innate would explain the capacity of phonological systems to emerge spontaneously in a new linguistic modality, in nascent sign language . It is unclear what Everett means by “successfully,” as there is certainly ample research to suggest that significant cross-modal phonological similarities exist. For example, as with spoken languages, signers encode syllables and constrain their internal structure by appealing to their sonority , is likewise countered by evidence for the syllable hierarchy in neonates . While kro e.g., —it is unro e.g., . The finMoving to his last point (8e), Everett rejects scaffolding—the hypothesis innate core knowledge forms the basis for related bodies of knowledge that are acquired in later development. For example, the  core knowledge of number forms the basis for the recursive number system that emerges optionally in later development. In a similar vein, the putative innate knowledge of phonology could explain the fact that mature writing systems tend to encode phonological principles, and reading tends to recover phonological structure from print.every writing system ever invented is phonological. Rather, phonology appears to impose a constraint on the cultural evolution of writing systems, such that mature writing systems tend to encode phonological units (Everett objects on grounds that scaffolding is both (a) not specific to phonology and (b) false, since some writing systems are hieroglyphic. However, these claims are both self-contradictory and individually unwarranted. Scaffolding does not mean that al units , and reaal units . SimilarThe Phonological Mind, I concluded, “While the core phonology proposal seems to presently offer the best explanation for the wide range of evidence considered in this book, the available evidence is insufficient to fully evaluate this hypothesis,” and I proceeded to indicate a number of open questions for future research (Everett is certainly right to question whether phonology is a system of core knowledge. I applaud his efforts to unveil the origins of language and his many contributions to the field. Summarizing the state of research in research , p. 312.research , p. 6. NThe author confirms being the sole contributor of this work and approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.