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Conference Presentations 2017

  • IASSIST 2017-IASSIST 2017 – Data in the Middle: The common language of research, Lawrence
    Host Institution: University of Kansas

B1: Programs of Instruction (Wed, 2017-05-24)
Chair:Jungwon Yang

  • Supporting our researchers: The provision of data services in Canada: a case study
    Jane Fry (Carleton University)
    Chantal Ripp (Data Liberation Initiative, Statistics Canada)


    The use of statistical data for teaching and research purposes in Canada has substantially increased with the creation of the Data Liberation Initiative (DLI) program, established in 1996 as a partnership among Statistics Canada, other federal departments, and Canada’s academic community.  While some Canadian universities have a long history in the provision of data services, that was not the norm everywhere, especially in small universities and colleges.  To maximize the use of data, it was evident that increased education, resources and tools were required to support those delivering data services on their campuses. The development of the DLI Survival Guide, will be examined in this presentation. 

    The Survival Guide is an innovative and collaborative project driven by academic librarians and staff of the DLI program to address the diverse needs of those providing data services.  We will present a mix-methodology approach used to address the evolving needs of the community and describe the challenges and opportunities that were met and how they were addressed over the years. Suggestions for ways to maintain the currency and new ways to utilize the Survival Guide will also be given.


B2: Repository Strategies across Communities (Wed, 2017-05-24)
Chair:Wendy Thomas

  • The Data Seal of Approval in the Australian context - Assessing the Australian Data Archive as a Trusted Digital Repository.
    Steven McEachern (Australian Data Archive)


    Data archives and funding agencies are increasingly interested in certification of data archives and repositories as "trusted digital repositories". There is now current interest in Australia in understanding certification models for Australian archives and repositories. 

  • DataverseNL – New developments of a data management support system for Dutch universities, research organisations, and higher education
    Marion Wittenberg (Data Archiving and Networked Services (DANS))
    Peter Doorn (Data Archiving and Networked Services (DANS))
    Vyacheslav Tykhonov (Data Archiving and Networked Services (DANS))


    Twelve years ago Data Archiving and Networked Services (DANS) in the Netherlands developed the first self-deposit archiving system EASY. Over the last few years, most universities and research institutes have developed research data management policies. Many institutions want to offer a repository service to the staff of their institution for storing and sharing research data. University libraries or other university departments usually want to have the control of such a repository solution. To meet this demand, we started working according to a front-office, back-office model. A practical implementation of this is DataverseNL, built upon software developed by Harvard University (IQSS).

    DataverseNL is a shared service provided by the participating institutions and DANS. DANS performs back-office tasks, including server and software maintenance and administrative support. The participating institutions are responsible for managing the content, the data deposited by their staff. The repositories (or dataverses) within DataverseNL are positioned for data storage and sharing during research and about ten years after the conclusion of a research project. With a SWORD interface to EASY, long-term archiving is secured. In this presentation, we will focus on future developments like data tagging for privacy-sensitive data, visualization of data and building Virtual Research Environments within DataverseNL.

  • FAIR Data in Trustworthy Repositories: Everybody wants to play FAIR, but how do we put the principles into practice?
    Ingrid Dillo (Data Archiving and Networked Services (DANS))
    Peter Doorn (Data Archiving and Networked Services (DANS))


    There is a growing demand for quality criteria for research datasets. We will argue that the Data Seal of Approval and FAIR principles get as close as possible to giving quality criteria for research data. They do not do this by trying to make value judgements about the content of datasets, but rather by qualifying the fitness for data reuse in an impartial and measurable way. By bringing the ideas of the DSA and FAIR together, we will be able to offer an operationalization that can be implemented in any Trustworthy Digital Repository. 

    In 2014 the FAIR Principles were formulated. The well-chosen FAIR acronym is attractive: it almost automatically gets stuck in your mind once you have heard it. In a relatively short term, the FAIR data principles have been adopted by many stakeholders, including research funders.

    The FAIR principles are remarkably similar to the underlying principles of DSA (2005): the data can be found on the Internet, are accessible, in a usable format, reliable and are identified in a unique and persistent. The DSA presents quality criteria for repositories, whereas the FAIR principles target individual datasets. The two sets of principles will be discussed and compared and a tangible operationalization will be presented.


B3: Infrastructure to Support Restricted Data Sharing (Wed, 2017-05-24)
Chair:Infrastructure to Support Restricted Data Sharing

  • Using the 5-Safes framework: a case study of health data access in the UK
    Carlotta Greci (The Health Foundation)
    Arne Wolters (The Health Foundation)


    The Health Foundation is an independent charity committed to bringing about better health care provision for people in the United Kingdom. Our in-house research relies on the analysis of patient level data, which can provide insights into health utilisation and outcomes. It is important for any organisation processing patient information to be able to keep these data safe, and demonstrate this to data providers.This paper discusses the application of the ‘5 Safes framework’ in health services research.

    This framework provides guidance in risk mitigation when using health records, whether in aggregated form, fully identifiable or when de-identified. Fundamental to the framework is creating an appropriate balance of controls in all five dimensions of safe data access (safe data, safe people, safe projects, safe settings and safe outputs).The Health Foundation applies this framework in the designing and operating of its secure data environment. Combined with active data provider engagement, and adherence to national and international standard of best practice, the secure data environment enables the safe processing of de-identified patient’s medical records linked across various health care services in the United Kingdom.

  • Identifying less common types of restricted data
    Trace Crago (Boise State University)
    Amber Sherman (Boise State University)
    Jean Barney (Boise State University)


    Most researchers are aware that personally identifiable information needs to be protected and restricted. There are established ways to automatically scan for information like Social Security or Credit Card numbers and best practices exist for de-identifying or masking variables which could reveal identity. However, there are many other laws and policies which restrict the publishing of certain types of data including information about endangered animals and protected areas. More awareness of the less common types of restricted data is needed among researchers and data management professionals.

    The national trend toward interdisciplinary research programs makes it more likely that a single researcher will lack a complete knowledge of applicable laws. This paper will discuss the research taking place to create a database of sensitive information types along with corresponding laws restricting that information and suggestions for identifying each of those data types.

  • Facilitating collaboration with restricted-use data
    John Marcotte (ICPSR / University of Michigan)


    Data protection requirements often impede collaborations.  A typical security plan requires a standalone (non-networked) computer in a locked office. This requirement makes collaborating with colleagues at the same institution difficult; moreover, it makes collaborating across institutions practically impossible.The challenge is to provide a platform that facilitates collaboration while also meeting security requirements.  Cloud computing with virtualized machines can meet these challenges.   

    Virtual machines can be configured to prevent them from accessing the Internet so that researchers cannot copy files to a server on the Internet.   With virtual environment, implementing vetting of output by authorized reviewers can easily be incorporated into the protocols.   Researchers from different institutions can access the virtual machines in the cloud and have access to shared project resources and files.Virtual environments have been recognized for their security. 

    The most important feature of this type of virtual environment is that the restricted-use data never leave the system. Access to the data may be modified instantly.  When a data use agreement expires, access can be immediately terminated. Another facet is controlling output so that it can be vetted for disclosure risk.   In addition to these security controls, virtual environments can be setup with common disk space for projects. This disk space is a way for researcher at different location to collaborate.  Since this space is within the virtual environment, it meets security requirements.

  • UK Data Service responses to changes in the data landscape
    Hersh Mann (UK Data Archive)


    The Approved Researcher scheme is used by the United Kingdom Office for National Statistics to grant access to microdata that cannot be published openly. Following on from reviews of this scheme and of data that fall within its remit, there have been changes to the mechanisms by which the UK Data Service provides access to these data sources. These changes relate to the process of gaining permission to access data, and to a statistical disclosure review of the licences under which sensitive variables are held.

    Using these reviews as exemplars, this presentation will discuss how the impact of the changes affects the operation of the UK Data Service (in acquisition, licensing, ingest, access, and support) and how the user experience is altered in parallel. This exercise demonstrates the value of working closely with data depositors at all stages of the data lifecycle to strike a balance between preserving data security and ensuring that sensitive information can be shared safely and practically for legitimate research needs. As legislation and attitudes evolve to encompass new forms of data, there will be a continuing need for data producers and data services to provide dynamic responses to new developments.


B4: IASSIST: Data Professionals and Collaboration (Wed, 2017-05-24)
Chair:Paul Bern

  • Building a bigger data tent: What can IASSIST learn from CODATA?
    Ernie Boyko (Carleton University (Retired))


    CODATA, an interdisciplinary scientific committee of the International Council for Science (ICSU), has many things in common with IASSIST.  Established in 1966, CODATA promotes and encourages the compilation, evaluation, and dissemination of reliable data of importance to science and technology on a world-wide basis. IASSIST is an international organization of professionals working with information technology and data services to support research and teaching. Membership in CODATA is country and scientific union based while IASSIST is made up of individual memberships.  In spite of these differences in organizational structure, the focus on technology in support of data stewardship and on capacity-building are shared strategic directions of both organizations.

    A current proposal to merge the International Social Science Council (ISSC) with ICSU has the potential to bring IASSIST and CODATA even closer together in mission. This presentation will update the audience on the merger process and will outline the strategic directions and recent achievements of CODATA. It will conclude by identifying new doors in data development and service that could be opened by working more closely with CODATA. We look forward to an engaging discussion of our new opportunities.

  • Maximizing on The IASSIST Way: Data Support for All (without burning out)
    Paula Lackie (Carleton College)
    Adetoun Oyelude (University of Ibadan)
    Libby Bishop (UK Data Archive, U of Essex)
    Dessi Kirilova (Syracuse University)


    The demand for expert support in all phases of the data lifecycle as well as under increasingly diverse settings has never been greater - and it continues to grow exponentially.  Coincidentally, our professional staffing levels have rarely kept pace with this demand.  To maintain our professional standards, IASSIST members can do more to rely on one another to maximize on our shared expertise.  We have a broad set of expertise in working with written guides, maximizing students as peer leaders, reaching across academic disciplines and being fluid with our vocabulary. Surely there’s a way that we can pull these resources and expertise together for our mutual benefit!

    Join us in a discussion of models for local/institutional support as well as mechanisms to employ through our membership in IASSIST to continue to nurture the responsible use of data for good, never for evil.

  • IASSIST Quarterly

    Publications Special issue: A pioneer data librarian
    Welcome to the special volume of the IASSIST Quarterly (IQ (37):1-4, 2013). This special issue started as exchange of ideas between Libbie Stephenson and Margaret Adams to collect


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