The BioSharing Intiative: data sharing standards

If you’ve worked on a data management plan for an NSF grant, or shoot, just worked on sharing data, you may have been confronted with a drought or deluge of policies, metadata standards and and other considerations as you describe how you will share your data.

In this post and a few to follow, I’ll highlight some resources that are worth a visit as you develop and implement a data sharing plan.

Of course, I’m hoping that the UO data management pages are useful, but there are other resources that are on the rise and not yet incorporated into the UO site (but soon to be!).

BioSharing

BioSharing‘s goal is to create

stable linkages between journals, funders, implementing data sharing policies, and well-constituted standardization efforts in the biosciences domain, to expedite the communication and the production of an integrated standards-based framework for the capture and sharing of high-throughput genomics and functional genomic bioscience data, in particular. This objective is achieved via the creation of web-based catalogues and a communication forum…

The products are a catalog of the following:

- reporting requirements (minimal information checklists to report of the same core set of information)
- terminological artifacts (such as controlled vocabularies and ontologies to describe the information)
- exchange formats (to communicate the information)

The need for standards

More about the need for standards to enable discovery and data sharing is outlined in My Data are Your Data, in Nature Biotechnology:

In January, over 50 researchers from 30 academic and commercial organizations agreed on a standard for describing data sets. The BioSharing initiative, comprising both researchers and publishers, launched the Investigation-Study-Assay ISA Commons, which promises to streamline data sharing among different databases. Life scientists have thousands of databases, over 300 terminologies and more than 120 exchange formats at their disposal, says BioSharing co-founder Susanna-Assunta Sansone of the University of Oxford. In this era of collaborative big science, researchers only move forward by “walking together.”

Elsevier protest — Faculty activism supporting open access

Many faculty members around the world — about 2900 as of this moment — have in the past few days signed a pledge to boycott Elsevier, a major commercial academic publisher. The list of signatories to date is impressive and growing quickly; you can see the current list at “The Cost of Knowledge” website, or if you wish can use that site to add your own name.

The signatories have committed not to publish, referee, or do editorial work for Elsevier journals “unless they radically change how they operate.”

Concerns with Elsevier mirror some that many UO librarians also feel — that Elsevier has been at the forefront of rapid increases in journal pricing, anti-competitive practices aimed at libraries such as “bundling,” monopolizing access to a large segment of the last 90 years of scholarly publishing, lobbying in favor of bills such as SOPA and a bill (the “Research Works Act“) that would repeal the NIH Public Access Policy, and in general a large number of small policies antithetical to author rights and to public access to research.

My own impression is that of all major academic publishers Elsevier is trying the hardest to kill disciplinary and institutional online repositories such as PubMed Central or the arXiv or our own Scholars Bank.

The new pledge, which was launched in a posting a week ago by Mathematics Fields Medalist Timothy Gower, seems to be setting a new standard for faculty revolt against publishers whose practices are seen as focused on profit to the detriment of improved public access to scientific information.

Interested in more perspective? “Elsevier Publishing Boycott Gathers Steam”  and “As Journal Boycott Grows, Elsevier Defends Its Practices” in this week’s Chronicle of Higher Education are quite good.  Forbes also has an interesting economic analysis at “Elsevier’s Publishing Model Might be About to Go Up in Smoke.”

The UO doesn’t take a position on whether our faculty should sign this pledge. However, the UO Senate does have a formal recommendation (resolution passed in 2008) that all UO faculty authors include an author’s addendum as part of any copyright transfer. Such an addendum would let the original author retain rights that Elsevier clearly doesn’t want academic authors to keep, including the right to reuse your own work or to deposit a copy of the work in an online repository.

JQ Johnson
Director, Scholarly Communications
UO Libraries

Panton Fellowships for scientists to promote open data in science

From the Open Knowledge Foundation:

Dear all,

The OKFN is delighted to announce the launch of the Panton Fellowships!

Funded by the Open Society Institute, two Panton Fellowships will be awarded to scientists who actively promote open data in science.

The Fellowships are open to all, and would particularly suit graduate students and early-stage career scientists. Fellows will have the freedom to undertake a range of activities, which should ideally complement their existing work. Panton Fellows may wish to explore solutions for making data open, facilitate discussion, and catalyse the open science community.

Fellows will receive £8k p.a. Prospective applicants should send a CV and covering letter to jobs[@]okfn.org by Friday 24th February.

Full details can be found at [Panton Principles](http://pantonprinciples.org/panton-fellowships/). You can also see our [blog post](http://blog.okfn.org/2012/01/25/panton-fellowships-apply-now/).

Please do feel free to circulate these details to interested individuals and appropriate mailing lists!

Kind regards,
Laura

–
Laura Newman
Community Coordinator
Open Knowledge Foundation
http://okfn.org/
Skype: lauranewmanonskype

copyright conflicts and online open access

If you follow copyright and intellectual property legislation, you might get the impression that universities and libraries are under attack from the publishing industry. There have recently been a series of lawsuits and bills designed to strengthen content publishers at the expense of authors and universities.

One awful example is SOPA (and it’s companion bill in the Senate, PIPA), which attempts to combat online “piracy”, may pass, and if it does will have very negative consequences for the stability of the Internet since it undermines the domain name system on which the Internet depends. Many of us noted and supported the Internet blackout earlier this week, which seems to have had an effect in getting widespread attention for the problem. The UO’s congressional delegation is firmly opposed to PIPA and SOPA, but if you have colleagues at other institutions it would never hurt to alert them to the issues.

Another such bill is H.R. 3699, which would undo the progress that the National Institutes of Health have made in making taxpayer-funded research publicly available. H.R. 3699 has started to generate strong reactions from the academic community. For example, there was an excellent op ed piece in the New York Times last week by Michael Eisen — see “Research Bought, Then Paid For” http://www.nytimes.com/2012/01/11/opinion/research-bought-then-paid-for.html#   In stark contrast, a recent OSTP request for information solicits advice that could result in extending the NIH public access mandate to more federal agencies. The UO filed a response discussing some of the benefits of improved public access. You can read it at https://scholarsbank.uoregon.edu/xmlui/handle/1794/11810

Yet a third interesting bill is H.R. 3433 (aka the GRANT Act), which, nominally in the name of public access to information, in fact would have serious consequences for NSF funding since it would mandate public disclosure of the names of reviewers (bye bye blind peer review) and would publish all grant applications (bye bye competitive advantage as foreign countries jump on the bandwagon based on which NSF grants are funded before our researchers have a chance to do the research).

I’m happy to report that our Office of Public and Government Affairs (Betsy Boyd) is on top of all of these.  She writes “There are several bills, as JQ noted, that threaten innovation and open access in the name of transparency and open access.”

We live in interesting times.

GigaScience — open access journal

In the UO Science Library blog I try to highlight new open access science journals as I hear about them. If one looks relevant to innovations in visualizing, preserving, presenting or sharing data, I’ll also include them here.

Here’s a recently launched journal that is focused on “big data” studies, and will be waiving the article processing charge for all articles published during the first year.

GigaScience aims to revolutionize data dissemination, organization, understanding, and use. An online open-access open-data journal, we publish ‘big-data’ studies from the entire spectrum of life and biomedical sciences. To achieve our goals, the journal has a novel publication format: one that links standard manuscript publication with an extensive database that hosts all associated data and provides data analysis tools and cloud-computing resources.

Our scope covers not just ‘omic’ type data and the fields of high-throughput biology currently serviced by large public repositories, but also the growing range of more difficult-to-access data, such as imaging, neuroscience, ecology, cohort data, systems biology and other new types of large-scale sharable data.

via GigaScience.

E-Science Reading List

Deb Carver (Dean of UO Libraries), John Conery (Professor, Computer and Information Science), Lynn Stearney (Director of Grants, UO Foundation), Sean Sharp (Research and Instructional Technology, Campus Information Services), and I are participating in the ARL/DLF E-Science Institute.

The following is a list of readings compiled by the institute staff, and organized by topic. It’s pretty comprehensive, and may be helpful if you’re interested in gaining some background in these topics.

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Readings Organized by Topic Area

July, 2011

Data deluge

Chicken or the egg?  Did e-Science cause the so called data deluge or is e-Science a response to this phenomenon?  The early e-Science funding initiatives in the U.K. at the beginning of the last decade targeted projects where data infrastructure was integral to managing the massive flow of data from digital instrumentation.  This focus anticipated the ever-expanding use of digital instrumentation across research domains and, indeed, within society.  The following articles take stock of the data deluge phenomenon.  Regardless of whether e-Science has caused or has been a response to this phenomenon, a basic understanding of the massive production of digital data helps focus on the variety of issues related to managing research data.

• The data deluge and Data, data everywhere – The February 25, 2010 issue of the Economist included an article about the general deluge of data in society (the former link) and a technology pull-out section on overall characteristics of data (the latter link.)  These are particularly informative articles from the popular press.
• The end of theory: the data deluge makes scientific method obsolete  – This June 23, 2008 story from Wired Magzine by Chris Anderson reflects a Google-perspective about making discoveries through huge amounts of data.  In other words, with a enough data and the right algorithm you don’t need a scientific model.  He suggests a scientific method based on computationally derived patterns from massive data collections that doesn’t require models to test.  What makes this method work are petabytes of data.
• The coming data deluge – This short opinion piece from IEEE Spectrum within Technology introduces a number of words appearing in our language because of the data deluge.  For example, the author makes reference to data scientists.
• Data -The February 11, 2011 issue of Science was dedicated to the challenges and opportunities arising from the data deluge in research.  This is an excellent compendium presenting perspectives on “the increasingly huge influx of research data” from a variety of scientific fields.

Data-driven science

The following trilogy provides a solid introduction to current thinking around data-driven science (or more generally, data-driven research).  The first title is an anthology describing the emergence of data-driven science.  The chapter by Jim Gray on e-Science: A Transformed Scientific Method, which was reproduced from a presentation in January 2007, serves as the framework for the other authors who provide examples of data-driven science in various disciplines.  The second title is from the U.S. Interagency Working Group on Digital Data, representing key U.S. agencies involved in scientific research.  Working from a set of data principles that they developed, this report outlines a strategic vision around scientific data for U.S. federal agencies.  The third title is a report to the European Commission from the High Level Expert Group on Scientific Data .  This report provides a useful public statement about the value of scientific data to society and espouses a vision for data in 2030.

• The Fourth Paradigm: Data-Intensive Scientific Discovery  – This collection of essays from Microsoft Research is a tribute to Jim Gray and his ideas about data-driven science.
• Harnessing the Power of Digital Data for Science and Society - This document includes a set of principles upon which federal scientific agencies should manage the data they produce.  There is an excellent appendix on the roles for organizations and individuals.
• Riding the Wave: How Europe can gain from the rising tide of scientific data – Released in October 2010, this report establishes a strong case for European developments in research data infrastructure over the next several years.  The second chapter of this report uses a variety of scenarios that expresses the value proposition for investing in data infrastructure.  The third chapter describes challenges that have to be overcome in building new data infrastructure (which they interchangeably call “scientific e-infrastructure.”)  The fourth and fifth chapters present a vision for 2030 and a call for action, respectively.  This 38-page publication is an excellent follow up to The Fourth Paradigm: Data-Intensive Scientific Discovery, which was released in 2009.
• Science Magazine, Special Online Collection: Dealing with Data (Feb 11, 2011) – Issue devoted to challenges with scientific research data, introducing many key ideas in different scientific disciplines.

Data Curation

The life cycle management of information is fundamental to understanding digital curation, for it is the stewardship and management of digital objects across the life cycle that determines the activities of digital curation.  Similarly, the essence of data curation is defined by the context of the research life cycle (see the class glossary for a definition the research life cycle.)  The management of research data spans the research life cycle, consisting of the many activities related to the design, production, manipulation, analysis and preservation of the data itself and its supporting metadata.  The stewardship of research data ensures that responsibilities for all data and metadata activities across the life cycle are assigned, understood and carried out.  It is the combination of the activities of research data management and the responsibilities of data stewardship over the research life cycle that embodies data curation.  The following articles introduce data curation and its supporting concepts.  Beginning with an article by Anna Gold, an overview of data curation is provided that traces the evolution of the concept and its current state of development.

Data Curation

• Data Curation and Libraries: Short-term developments, long-term prospects – Anna Gold provides a summary of the developments and events over the past decade that have shaped data curation as it is today.

The Data Life Cycle

• JISC Research Lifecycle diagram – JISC, which historically stood for the Joint Information Systems Committee in the UK but  which is now simply known as JISC, employs a life cycle diagram to describe the support their organization provides to researchers across the stages of the research life cycle.  This brief, succinct representation of the life cycle shows two interrelated cycles making up an overall research life cycle.  One cycle consists of the stages associated with knowledge management and scholarly communications, while the other cycle has stages making up the research process.
• Curation Lifecycle Model – The UK Digital Curation Centre provides an online representation of a life cycle model depicting stages in curating and preserving data from a digital records management perspective.
• The data life cycle is mentioned in some the above readings, including pages 8 and 9 of Harnessing the Power.  The entry for data life cycle in the class glossary also links to an article describing characteristics of the research life cycle model.
• e-Science and the Life Cycle of Research – by Charles Humphrey, June, 2008. Brief introduction to the research life cycle (also linked from the glossary of key terms and concepts).

Research Data Management

• Managing and Sharing Data: Best Practices for Researchers – This guide was developed by the UK Data Archive outlining the many topics to consider around the best practices in managing research data.  The intended audience is researchers and employs a checklist for the topics that are covered.
• Guide to Social Science Data Preparation and Archiving: Best practice throughout the data life cycle – This ICPSR publication describes data management activities across a life cycle perspective that are deemed to be best practices in the social sciences.
• D-Lib Magazine, vol 17, issue 1/2, Jan/Feb 2011. Special issue on research data management including issues like citation and identifiers.

Data Stewardship

• Stewardship of digital research data: a framework of principles and guidelines – This Research Information Network publication sets out a policy framework in the UK for data stewardship based on five principles.  The roles and responsibilities of the key players involved with research data receive particular attention in this report.

Research Libraries, Data and e-Science

Many research libraries have been involved over the past decade and a half in developing digital collections, in producing digital content through digitization projects and in preserving digital content through institutional repositories.  More recently and in conjunction with the emergence of data-driven science, the inclusion of research data in digital collections has become a focus of many libraries.  Some of the following readings explore the retooling that libraries face to incorporate research data into their digital collections.  Other readings provide case studies about how some libraries are addressing e-Science and research data.  Some of this work can be done within an institution and several of the case studies present local approaches to building research data collections and providing e-Science data services.  However, the support for e-Science and research data will increasingly require cross-institutional collaboration among libraries.  A typical e-Science project tends to consist of a large research team where the researchers are from different universities, come from a variety of disciplines and are located in institutions from around the globe. Examples of this include the teams of physicists working with the Hadron Collider and the international teams of scientists conducting research under the banner of the International Polar Year.  They work together through shared technology that generates massive volumes of data and supports its storage and processing through a distributed high-speed network.  No single research library has the capacity to respond to such large-scale projects thus challenging libraries to find new ways to collaborate around e-Science research data.  The infrastructural requirements alone to ingest, manage, preserve and provide access to large-scale research data are an impetus for libraries to collaborate.

Retooling

• Retooling Libraries for the Data Challenge  – In this concise article, Dorothea Salo reviews pertinent characteristics of research data, digital libraries and institutional repositories in proposing ways in which libraries can address the data challenge.
• Long-Lived Digital Data Collections: Enabling Research and Education in the 21st Century – This is a National Science Board 2005 report.
• Agenda for Developing E-Science in Research Libraries – This November 2007 report contains recommendations about e-Science to the Scholarly Communication Steering Committee, the Public Policies Affecting Research Libraries Steering Committee, and the Research, Teaching, and Learning Steering Committee.
• To Stand the Test of Time: Long-term Stewardship of Digital Data Sets in Science and Engineering – This 2006 ARL report contains the results of NSF-funded workshop to compose an agenda for research data infrastructure in science and engineering.
• Skilling Up to Do Data: Whose Role, Responsibility, Career? – This 2009 IJDC article by Graham Pryor and Martin Donnelly looks on data curation roles and skills in the UK and proposes a framework for skills development in data management.
• Steps Toward Large-Scale Data Integration in the Sciences: Summary of a Workshop  - This report “summarizes a 2009 National Research Council workshop to identify some of the major challenges that hinder large-scale data integration in the sciences and some of the technologies that could lead to solutions. The workshop examined a collection of scientific research domains, with application experts explaining the issues in their disciplines and current best practices. This approach allowed the participants to gain insights about both commonalities and differences in the data integration challenges facing the various communities. In addition to hearing from research domain experts, the workshop also featured experts working on the cutting edge of techniques for handling data integration problems. This provided participants with insights on the current state of the art. The goals were to identify areas in which the emerging needs of research communities are not being addressed and to point to opportunities for addressing these needs through closer engagement between the affected communities and cutting-edge computer science.”
• The Shape of the Scientific Article in the Developing Cyberinfrastructure” – This report by Cliff Lynch discusses how “E-science represents a significant change, or extension, to the conduct and practice of science.  This article speculates about how the character of the scientific article is likely to change to support these changes in scholarly work. In addition to changes to the nature of scientific literature that facilitate the documentation and communication of e-science, it’s also important to recognize that active engagement of scientists with their literature has been, and continues to be, itself an integral and essential part of scholarly practice; in the cyberinfastructure environment, the nature of engagement with, and use of, the scientific literature is becoming more complex and diverse, and taking on novel dimensions.”

Case Studies

• E-Science and Data Support Services:  A Study of ARL Member Institutions – This 2010 ARL report by Soehner, Steeves & Ward reviews the different approaches libraries are taking toward e-Science and data support services.  Six institutional cases studies are also provided.
• Data Sharing, Small Science, and Institutional Repositories (post-print) – This 2010 article by Cragin, Palmer, Carlson and Witt in Philosophical Transactions of the Royal Society A contains results of the Data Curation Profiles research project done by UIUC and Purdue on how faculty view and practice data sharing.
• Librarian Roles in Institutional Repository Data Set Collecting: Outcomes of a Research Library Task Force (access requires subscription) – This 2011 article by Newton, Miller and Bracke in Collection Management describes the Purdue Libraries task force charged with building faculty-produced collections for a data repository prototype.  This project developed an inventory and characterized the resources and skills required of the libraries and its data-collecting librarians. The roles and activities of librarians identified during the project were explored.
• Determining Data Information Literacy Needs: A Study of Students and Research Faculty (access requires subscription) – This 2011 article by Carlson, Fosmire, Miller and Sapp-Nelson in portal: Libraries and the Academy describes how “researchers increasingly need to integrate the disposition, management, and curation of their data into their current workflows. However, it is not yet clear to what extent faculty and students are sufficiently prepared to take on these responsibilities. This paper articulates the need for a data information literacy program (DIL) to prepare students to engage in such an e-research environment. Assessments of faculty interviews and student performance in a geoinformatics course provide complementary sources of information, which are then filtered through the perspective of ACRL’s information literacy competency standards to produce a draft set of outcomes for a data information literacy program.”
• Data Curation Program Development in U.S. Universities:  The Georgia Institute of Technology Example – This 2011 article by Walters in The International Journal of Digital Curation presents GT’s data curation program development. The main characteristic is a program devoid of top-level mandates and incentives, but rich with independent, “bottom-up” action. The paper addresses program antecedents and context, inter-institutional partnerships that advance the library’s curation program, library organizational developments, partnerships with campus research communities, and a proposed model for curation program development.
• Data Services for the Sciences: A Needs Assessment” – This 2010 article by Westra in Ariadne describes scientific research data management as “a fluid and evolving endeavour, reflective of the high rate of change in the information technology landscape, increasing levels of multi-disciplinary research, complex data structures and linkages, advances in data visualisation and analysis, and new tools capable of generating or capturing massive amounts of data.  These factors create a complex and challenging environment for managing data, and one in which libraries can have a significant positive role supporting e-science. A needs assessment can help to characterise scientists’ research methods and data management practices, highlighting gaps and barriers, and thereby improve the odds for libraries to plan appropriately and effectively implement services in the local setting.”
• The Cornell University Library (CUL) Data Working Group (DaWG) report – This 2008 report contains five recommendations from the Data Working Group detailing how the Cornell University Library could engage in data curation.  Included within these recommendations is a set of services that could be provided to researchers and local infrastructure and policies needed to sustain these services.
• Responding to the Call to Curate:  Digital Curation in Practice at Penn State University Libraries (pre-print) – This 2011 article by Hswe, Furlough and Giarlo in the The International Journal of Digital Curation presents how Pennsylvania State University Libraries established a Content Stewardship program for the university, describing the planning and staffing needed for its implementation.  They specifically address the challenges of starting and sustaining a stewardship services program.

DuraSpace to Bring Cloud-Based Platform “Direct-to-Researchers”

DuraSpace is pursuing development of a cloud-based storage system that can more easily be used by researchers for data storage while also addressing data curation and management issues.

The not-for-profit DuraSpace organization announced that it will develop a hosted, cloud-based data storage and management service aimed at meeting the specific needs of working scientists and researchers. The new service, an expansion of DuraSpace’s popular DuraCloud data management and archiving service, is being funded through a grant from the Alfred P. Sloan Foundation.

via Duraspace.org news release.

Interested in this at the UO? Let me know.