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Conference Presentations 2016

  • IASSIST 2016-Embracing the 'Data Revolution': Opportunities and challenges for research, Bergen
    Host Institution: NSD - Norwegian Centre for Research Data

Plenaries (Wed, 2016-06-01)

  • Plenary 1: Data for decision-makers: Old practice - new challenges
    Gudmund Hernes (Fafo Institute; BI Norwegian School of Management)
  • Plenary 2: Embracing the 'Data Revolution': Opportunities and challenges for research
    Matthew Woollard (UK Data Archive/ UK Data Service)

Plenary (Wed, 2016-06-01)

  • Data for decision-makers: Old practice - new challenges
    Gudmund Hernes (Fafo Institute; BI Norwegian School of Management)
  • Embracing the 'Data revolution': Opportunities and challenges for research, or what you need to know about the data landscape to keep up to date
    Matthew Woollard (UK Data Archive/UK Data Service)

1A: Vintage data/Data rescue (Wed, 2016-06-01)
Chair:Stuart Macdonald

  • Digitising 100 Years of Parliamentary Data - An Exercise in Producing a Living Digital Record of Political History
    Samuel Spencer (Parliamentary Libaray/Commonwealth of Australia)


    Data journalism is a growing field for the improvement of civic engagement in democracy, and the use of open data in political coverage has grown substantially in recent years. At the core of this is the ability to compare and contrast modern events in a historical context, and this requires accurate data to be centrally managed and easily accessible.

    Currently, historical information on Australian Parliaments has been available in the Parliamentary Library's flagship publication the Parliamentary Handbook - an extensive almanac with biographies, tables and records dating back to Australia's federation. This data is used as a way to track key social issues, such as length of service, gender representation in parliament and historical election information in an authoritative format.

    To improve access to this information the library began development of a mobile app which evolved into a complete data management system for the recording and sharing of information. To complement this the Parliamentary Library is developing an open-source data management system for managing parliamentary biographies and service histories based on Popolo, a civic data framework for the management and dissemination of parliamentary information. Along with interactive biographies and records of ministries and parties, the system for the first time allows users to build custom tables from complex queries that are dynamically updated as new information is made available.

    Coupled with this is the development of a biographical data management system that will ensure that records of new parliamentarians and future changes to existing parliamentarians are captured in a single system.

    In this presentation, we cover the challenges and successes in digitising over 100 years parliamentary data, including migration, data cleansing and data trust issues. We also provide a technical breakdown of the chosen framework and infrastructure, and issues during development especially when dealing with imprecise or incomplete historical records.

  • "Vintage" Is Just a Cooler Word for "Old": Salvaging the SSLS/SYPS
    Laine Ruus (University of Edingburgh)


    The first Scottish School Leavers survey (SSLS) was administered in 1962, and conducted usually biennially until 2005. Various principal investigators and funding agencies have been involved; the last PI, Dr. Linda Croxford, has retired, and is cleaning out her office at University of Edinburgh. Some surveys/waves have been deposited with the UKDA. Much of the documentation is paper only, and because of confidentiality and privacy concerns, access to the microdata files has been restricted. Consequently, the data from these surveys spanning over 30 years, in about 17-20 different files, with comparable questions but various levels of documentation, have been underutilized.

    Beginning in 2014, the Data Library began a salvage operation. The primary focus has been on those data not in UKDA, primarily the 1977 through 1983 surveys. In order to maximize access, it was decided to employ an on-line interactive interface, with good metadata display, a wide range of statistical analysis and recoding/computing, and the best available variable-level confidentiality management capabilities, namely SDA. The processes undertaken to salvage these classic microdata files, ensure their long-term preservation, and enhance access to them, while respecting privacy and confidentiality, will be outlined.

  • Data Survival on a Seemingly Deserted Island?
    A. Michelle Edwards (Cornell University)
    Berenica Vejvoda (McGill University)


    "Survival, to continue to live or exist, especially in spite of danger or hardship"
    Data formats and collection methods have changed dramatically over the years, leaving very valuable data behind in the dust. Historical Canadian Agricultural Census and Canadian First Nations surveys are only two examples from one country. The question that may come to mind is: Should all "forgotten or older data survive?" Should data librarians and data archivists invest valuable resources to rescue historical and older data? If we do, how do we evaluate and determine which data survives and which do not? How do we ensure that the surviving data matches today's standards for privacy and access? Should this be a priority? We can only imagine the benefits that adding older data can provide to new data creation and knowledge mobilization, creating valuable links between the past and today's data collections. In order to assist data survival, funding and resources are required. What funding opportunities exist today to help us provide support for surviving data? This paper will discuss the challenges that may be encountered while rescuing older data, provide different scenarios where surviving data could be used, and provide results of a survey of funding opportunities used to rescue data.

2D: Data sharing behavior (Wed, 2016-06-01)
Chair:San Cannon

  • A Game Theoretic Analysis of Research Data Sharing
    Tessa Pronk (Utrecht University)


    While reusing research data has evident benefits for the scientific community as a whole, decisions to archive and share these data are primarily made by individual researchers. Is research data sharing to their advantage? To tackle this question, we built a model in which there is an explicit cost associated with sharing datasets whereas reusing such sets implies a benefit. In our calculations, conflicting interests appear for researchers. Individual researchers are always better off not sharing and omitting sharing costs, whereas at the same time both sharing and not sharing researchers are better off if (almost) all researchers share. Namely, the more researchers share, the more benefit can be gained by the reuse of those datasets. Further simulation results point out that, although policy measures should be able to increase the rate of sharing researchers, and increased discoverability and dataset quality could partly compensate for costs, a better measure would be to directly lower the cost for sharing, or even turn it into a (citation-) benefit. Making data available would in that case become the most profitable, and therefore stable, strategy. This means researchers would willingly make their datasets available, and arguably in the best possible way to enable reuse.

  • Data Sharing Behavior: the Sociology of Data Sharing
    Alexia Katsanidou (GESIS, Leibniz Institute for the Social Sciences)
    Wolfgang Zenk-Moltgen (GESIS, Leibniz Institute for the Social Sciences)


    Some social science researchers are pioneers in sharing their data and promoting the replication and transparency in science movements. Others are still very protective of their data and prefer to keep it safe in their own computers. Previous work on data sharing focused on the relation between journal data policies and research data availability (Ghergina and Katsanidou 2013 and Zenk-Moltgen and Lepthien 2014). A clear literature gap is the omission of analyzing individual researcher intrinsic motivation for data sharing.
    Social psychology offers the analytical framework that allows us to investigate how personal beliefs can shape intentions of individuals and how these intentions influence their behavior. Based on the theory of planned behavior by Ajzen and Fishbein, which emphasizes the impact of peer group, this paper sets out to explain data sharing behavior by authors in political science and sociology journals.
    A set of authors of publications from pre-selected ISI indexed journals have been surveyed. The aim is to explore the authors' personal beliefs, intention and behavior regarding sharing the data their analysis is based upon. By presenting first results of this survey, we hope to shed some light on a previously obscure component of data sharing behavior.

  • Data Sharing and Data Citation: Linking Past Practices and Future Intentions
    Steven McEachern (Australian Data Archive)
    Janet McDougall (Australian Data Archive)


    The increasing interest in the archives and repository communities into the use of data citation practices has occurred in parallel to the interest in data sharing practices among depositors. The relationship between data sharing and data citation has not however been considered an issue this paper seeks to address. Recent research by McDougall (2013), drawing on data from Tenopir et al. (2011) suggests that there is a clear link between previous secondary data use and data sharing intentions. Tenopir et al. (2011) also report that the key consideration among researchers to share their data is the appropriate citation of the data when their data are reused. This suggests that past data use and data citation practices may be important influences on future data sharing intentions.
    This paper seeks therefore to explore the relationship between data sharing and data citation in detail. The paper presents the results of a recent survey of Australian social science researchers, which explores two key areas of research practice - use of secondary data, citation of secondary data, and personal data sharing experience - and their relationship to both data citation and data sharing intentions.

    McDougall, J. (2013) Sharing social science data: why do researchers share their data with others? Unpublished minor thesis, Masters of Social Research program, Australian Demographic and Social Research Institute. Canberra: Australian National University

    Tenopir C, Allard S, Douglass K, Aydinoglu AU, Wu L, Read E, et al. (2011) Data Sharing by Scientists: Practices and Perceptions. PLoS ONE 6(6): e21101. doi:10.1371/journal.pone.0021101

  • 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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