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Conference Presentations 2014

  • IASSIST 2014-Aligning Data and Research Infrastructure, Toronto
    Host Institution: University of Toronto, Ryerson University, and York University

4M: Energizing the DDI Standard through Tools (Thu, 2014-06-05)
Moderator: Marcel hebing

  • Forging a community: Current developments in MTNA's OpenDataForge Suite of applications
    Arofan Gregory (Metadata Technology)
    Andrew DeCarlo (Metadata Technology)
  • Colectica 5: Now with DDI 3.2
    Jeremy Iverson (Colectica)
    Dan Smith (Colectica)
  • DDI on Rails and r2ddi: Building a workflow for panel documentation
    Marcel Hebing (DIW Berlin - German Institute for Economic Research)
  • DDI-RDF tools takes your DDI-XML to the DISCO
    Olof Olsson (Swedish National Data Service (SND))
    Jannik Jensen (Danish National Archive)

4O: Trust and Data Sharing (Thu, 2014-06-05)
Chair:Jen Darragh

  • Re-using qualitative data: Qualitative researchers' understanding of and their attitude on data re-use
    Ayoung Yoon (University of North Carolina at Chapel Hill)


    In recent years, data sharing and data reuse in scientific research have been discussed in greater frequency. This has occurred with the revolution in the field of science known as data-intensive research and the growth of data in “big science”. Discussions regarding qualitative data sharing and reuse have also been very active, especially in Europe, where data archiving practices are well established. There has been a significant amount of interest in the issues related to the reuse of qualitative data. Organizations, such as the Social Research Council in the UK and the Australian Research Council have been trying to support this interest. However, the discussions do not seem to be as prominent in the United States, despite a long history of depositing and curating practices of scientific data. This study aims to understand the researchers’ thoughts and perceptions regarding qualitative data reuse in the field of social science in the United States. In particular, this study will focus on the barriers or hindrances to reusing qualitative data, the appropriate conditions for reusing qualitative data, and the perspectives of qualitative researchers on data reuse. The preliminary results from the in-depth interviews with qualitative researchers in social science will be presented.

  • Discovering and accessing Social Science data of East Asian countries: Trends and obstacles
    Jungwon Yang (University of Michigan)


    The increasing use of geographic information system (GIS), combined with the wider availability of statistics of census and economic data, has recently opened up new possibilities for more interdisciplinary academic research in social sciences. Social science researchers have become more and more interested in combining geographic analysis and traditional quantitative and statistical methods in order to test hypotheses and present arguments in more effective ways. Yet, discovering, accessing, and using international geospatial data and statistics is still a challenge for researchers: As OECD Global Science Forum report (2013) noted, information about the existence of micro-data and their availability for the re-use is often difficult to find. The language, legal, cultural, and technological obstacles often exacerbate the difficulty to re-use the discovered data. In this paper, I review what kinds of new data on East Asian countries have been recently developed by national statistical agencies, government departments, and academic institutions. Also, what obstacles researchers have encountered in using the data in their research are investigated.

  • Data sharing and citation practices: An application of the theory of planned behaviour to social science research practice
    Steven Mceachern (Australian Data Archive)
    Janet McDougall (Australian Data Archive)


    This paper will showcase the results of a recent project run by the Australian Data Archive that aims to better understand the data sharing and data citation behaviours and attitudes of Australian social science researchers both in Australia and internationally. We define these two behaviours as follows: a) data sharing: “the voluntary provision of information from one individual or institution to another for purposes of legitimate scientific research” (Boruch, 1985) b) data citation: “the practice of providing a reference to data in the same way as researchers routinely provide a bibliographic reference to outputs such as journal articles, reports and conference papers” (ANDS, 2011) Drawing on the theory of planned behaviour (Azjen, 1991), the study explores researchers’ current and intended data sharing and data citation practices, attitudes towards each behaviour, and perceived social and institutional barriers and supports for data sharing and data citation within their organisation and discipline. The paper will present the results of the ADA survey, and compare with two recent US studies to explore cross-national similarities and differences in data sharing and citation behavior.

  • Methodology and outcomes of using the Data Seal of Approval to benchmark and guide trust issues in an evolving European Research Data
    Herve L'Hours (UK Data Archive)


    This paper will outline the methodology and processes used to develop and define the requirements for trust in the emerging Consortium of European Social Science Data Archives (CESSDA). As CESSDA evolves from a “Council” to a “Consortium” one goal is to ensure that national service providers can align to the same (or similar) practices and standards to maximise cross-national efficiency and interoperability. A key part of this collaboration is trust. The 16 trust guidelines of the data seal of approval were used to benchmark current practice, identify potential gaps and to support the development of mutual trust structures. The paper outlines the progress to date on this project and discusses the potential impact of audit and certification of trusted digital Repositories on data management within this research infrastructure.


5P: Big Picture Metadata (Thu, 2014-06-05)
Chair:San Cannon

  • Using identifiers to connect researchers, authors and contributors with their research data
    Elizabeth Newbold (The British Library)


    The ORCiD and DataCite Interoperability Network (ODIN) project is a collaboration between The British Library, CERN, ORCiD, DataCite, Dryad, arXiv and the Australian National Data Service with the aim of using persistent, open and interoperable identifiers for people and for datasets to connect researchers, authors and contributors with their research data. This paper will outline the key results from the first year of the project including the proofs of concept in the Humanities and Social Sciences (HSS) and High Energy Physics (HEP) and will outline the commonalities between the extremely different disciplines that will inform a way forward for implementing an identifier ecosystem across disciplines. The paper will highlight technical work that has already been performed between making the identifier systems interoperable and will showcase value added services that have been built on the open APIs provided by the identifier systems. The paper will also outline gaps that currently hinder the adoption of such systems and outline a way forward for libraries and data centres to help implement these initiatives. The ODIN project ran a session at IASSIST 2013 and are grateful to have the opportunity to update the community on the progress made in its first full year.

  • Rich metadata from Blaise
    Beth-ellen Pennell (University of Michigan)
    Gina Cheung ()


    This presentation will discuss the process and challenges faced during the harmonization and preparation of the metadata and data files of the Collaborative Psychiatric Epidemiology Surveys (CPES) The CPES joins together three nationally representative surveys of adults living in the United States: the National Comorbidity Survey Replication, the National Survey of American Life, and the National Latino and Asian American Study. These data were collected face-to-face using the Blaise software. The Blaise data were transformed into XML capturing the rich metadata available in Blaise data models. The combined CPES dataset contains approximately 20,000 interviews. The initial combined dataset had 9.400 raw variables distributed over 92 sections of the three surveys. The final dataset contains approximately 5,600 harmonized variables, 400 constructed variables and 14 separate weights. The website contains rich metadata including an interactive cross-walk of all harmonized variables with question text in 5 languages, response options, missing data codes, descriptive statistics (frequencies, etc), universes, detailed documentation of all constructed variables, and descriptive statistics of all variables, among a wide variety of other products. These products will be discussed in light of the upcoming release of DDI 3.2 and version 5 of Blaise.

  • 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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