WikiProteins enables community annotation in a Wiki-based system. Extracts of major data sources have been fused into an editable environment that links out to the original sources. Data from community edits create automatic copies of the original data. Semantic technology captures concepts co-occurring in one sentence and thus potential factual statements. In addition, indirect associations between concepts have been calculated. We call on a 'million minds' to annotate a 'million concepts' and to collect facts from the literature with the reward of collaborative knowledge discovery. The system is available for beta testing at http://www.wikiprofessional.org.A preview of the version highlighted by WikiProfessional is available at:

Copyright and licensing of scientific data, internationally, are complex and present legal barriers to data sharing, integration and reuse, and therefore restrict the most efficient transfer and discovery of scientific knowledge. Much data are included within scientific journal articles, their published tables, additional files (supplementary material) and reference lists. However, these data are usually published under licenses which are not appropriate for data. Creative Commons CC0 is an appropriate and increasingly accepted method for dedicating data to the public domain, to enable data reuse with the minimum of restrictions. BioMed Central is committed to working towards implementation of open data-compliant licensing in its publications. Here we detail a protocol for implementing a combined Creative Commons Attribution license (for copyrightable material) and Creative Commons CC0 waiver (for data) agreement for content published in peer-reviewed open access journals. We explain the differences between legal requirements for attribution in copyright, and cultural requirements in scholarship for giving individuals credit for their work through citation. We argue that publishing data in scientific journals under CC0 will have numerous benefits for individuals and society, and yet will have minimal implications for authors and minimal impact on current publishing and research workflows. We provide practical examples and definitions of data types, such as XML and tabular data, and specific secondary use cases for published data, including text mining, reproducible research, and open bibliography. We believe this proposed change to the current copyright and licensing structure in science publishing will help clarify what users – people and machines – of the published literature can do, legally, with journal articles and make research using the published literature more efficient. We further believe this model could be adopted across multiple publishers, and invite comment on this article from all stakeholders in scientific research.

Prior research shows that article reader counts (i.e. saves) on the online reference manager, Mendeley, correlate to future citations. There are currently no evidenced-based distribution strategies that have been shown to increase article saves on Mendeley. We conducted a 4-week randomized controlled trial to examine how promotion of article links in a novel online cross-publisher distribution channel (TrendMD) affect article saves on Mendeley. Four hundred articles published in the Journal of Medical Internet Research were randomized to either the TrendMD arm (n = 200) or the control arm (n = 200) of the study. Our primary outcome compares the 4-week mean Mendeley saves of articles randomized to TrendMD versus control. Articles randomized to TrendMD showed a 77% increase in article saves on Mendeley relative to control. The difference in mean Mendeley saves for TrendMD articles versus control was 2.7, 95% CI (2.63, 2.77), and statistically significant (p < 0.01). There was a positive correlation between pageviews driven by TrendMD and article saves on Mendeley (Spearman’s rho r = 0.60). This is the first randomized controlled trial to show how an online cross-publisher distribution channel (TrendMD) enhances article saves on Mendeley. While replication and further study are needed, these data suggest that cross-publisher article recommendations via TrendMD may enhance citations of scholarly articles.

BackgroundData are the evidentiary basis for scientific hypotheses, analyses and publication, for policy formation and for decision-making. They are essential to the evaluation and testing of results by peer scientists both present and future. There is broad consensus in the scientific and conservation communities that data should be freely, openly available in a sustained, persistent and secure way, and thus standards for 'free' and 'open' access to data have become well developed in recent years. The question of effective access to data remains highly problematic.DiscussionSpecifically with respect to scientific publishing, the ability to critically evaluate a published scientific hypothesis or scientific report is contingent on the examination, analysis, evaluation - and if feasible - on the re-generation of data on which conclusions are based. It is not coincidental that in the recent 'climategate' controversies, the quality and integrity of data and their analytical treatment were central to the debate. There is recent evidence that even when scientific data are requested for evaluation they may not be available. The history of dissemination of scientific results has been marked by paradigm shifts driven by the emergence of new technologies. In recent decades, the advance of computer-based technology linked to global communications networks has created the potential for broader and more consistent dissemination of scientific information and data. Yet, in this digital era, scientists and conservationists, organizations and institutions have often been slow to make data available. Community studies suggest that the withholding of data can be attributed to a lack of awareness, to a lack of technical capacity, to concerns that data should be withheld for reasons of perceived personal or organizational self interest, or to lack of adequate mechanisms for attribution.ConclusionsThere is a clear need for institutionalization of a 'data publishing framework' that can address sociocultural, technical-infrastructural, policy, political and legal constraints, as well as addressing issues of sustainability and financial support. To address these aspects of a data publishing framework - a systematic, standard approach to the formal definition and public disclosure of data - in the context of biodiversity data, the Global Biodiversity Information Facility (GBIF, the single inter-governmental body most clearly mandated to undertake such an effort) convened a Data Publishing Framework Task Group. We conceive this data publishing framework as an environment conducive to ensure free and open access to world's biodiversity data. Here, we present the recommendations of that Task Group, which are intended to encourage free and open access to the worlds' biodiversity data.

We report the outcomes of BioMed Central’s public consultation on implementing open data-compliant licensing in peer-reviewed open access journals. Respondents (42) to the 2012 consultation were six to one in favor (29 in support; 5 against; 8 abstentions) of changing our authors’ default open access copyright license agreement, to introduce the Creative Commons CC0 public domain waiver for data published in BioMed Central’s journals. We summarize the different questions we received in response to the consultation and our responses to them – matters such as citation, plagiarism, patient privacy, and commercial use were raised. In light of the support for open data in our journals we outline our plans to implement, in September 2013, a combined Creative Commons Attribution license for published articles (papers) and Creative Commons CC0 waiver for published data.