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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

D3: National Infrastructure Initiatives (Thu, 2017-05-25)
Chair:National Infrastructure Initiatives

  • Portaging the landscape: Developing & delivering a national RDM training infrastructure in Canada
    Carol Perry (University of Guelph)
    Jane Fry (Carleton University)
    James Doiron (University of Alberta)


    Launched in 2014, the Canadian Association of Research Libraries’ (CARL) Portage Network has a mandate to develop a national research data culture and infrastructure. Under the guidance of its inaugural Director, Chuck Humphrey, the broad goals within this mandate are two-fold:

    1) to develop a robust pan-Canadian network of Research Data Management (RDM) expertise; and

    2) connecting essential infrastructure and service components needed for RDM, and a national preservation and discovery network.

    There are currently six active Portage Expert Groups, including one focused upon the development of RDM training in Canada. This presentation will focus upon three key deliverables undertaken by the group:

    1) an environmental scan to identify existing RDM resources and tools which may be leveraged;

    2) a White Paper that identifies international training activities, gaps in RDM training in Canada, and a high-level view for a national RDM training program for various stakeholders; and

    3) the development and delivery of a national RDM training program. Current status of deliverables, lessons learned, and forward work will be discussed.

  • Putting the puzzle together- a picture of data centres in the UK
    Joanne Webb (Administrative Data Research Network)


    The UK's Economic and Social Research Council (ESRC) have established a three strand programme to encourage the use of Administrative and Big Data in research.  The first strand funded the Administrative Data Network, a UK-wide partnership between universities, government bodies, national statistics authorities and the wider research community.  The Network facilitates secure research access to linked, de-identified administrative data to enable real-world analysis that can benefit society.
    The second strand covers the Big Data Centres: the Business and Local Government Data Centre, the Urban Big Data Centre and the Consumer Data Research Centre.  These concentrate on making data routinely collected by business and local government organisations accessible for academics in order to undertake research in the social sciences.

    The third strand enables partnerships between academic institutions and citizen and voluntary sector organisations, to establish or build on relationships between academic researchers and civil society organisations. The aim is to demonstrate the value of improved data infrastructure, enabling collection and analysis of data which is of interest to civil society organisations and empowering the sector to better use its own data. 

    All three strands aim to enable research in social sciences while safeguarding individuals’ identities.  Working in a diverse changing landscape brings its own challenges and possibilities.  The University of Essex hosts the Administrative Data Service of the ADRN, the Business and Local Government Data Centre and the Human Rights, Big Data and Technology Project.  The challenge is to describe the boundaries, overlaps and synergies in the landscape. 

    This paper will review the UK network of these partnerships, a description of some of the challenges of taking part in such a diverse growing landscape and some of the benefits to researchers and society.

  • Swedish Research Data System
    Johan Fihn (Swedish National Data Service)


    Swedish National Data Service (SND) ran during 2016 a national pilot project with the purpose of looking at possibilities to establish a national infrastructure with the purpose of making research data more accessible. The project introduced a collaboration between SND, university archives and university libraries, where SND works as a back office knowledge center and university librarians functioning as a front office towards researchers. 

    Experiences from the pilot project have been analyzed and integrated into building a new collaborative infrastructure for research data in Sweden. The infrastructure consists of four different modules:

    Module 1 - Swedish Research Data Repository: A Joint Trusted Digital Repository where SND and several universities collaborate in creating common data curation and storage solutions.

    Module 2 - Swedish Research Data Portal: A National Metadata Portal for research data.

    Module 3 - National Knowledge Center: Establishing SND as the National Knowledge Center for research data activities in Sweden, including training of librarians, archivists and researchers.

    Module 4 - Research Data Collaboration. A national collaboration on all things research data, as e.g. preservation formats, standards, common metadata profiles, DMP, and law.

D4: Metadata in the Curation Workflow (Thu, 2017-05-25)
Chair:Amy Pienta

  • C2Metadata project
    George Alter (ICPSR, University of Michigan)
    Jared Lyle (ICPSR, University of Michigan)
    Jeremy Iverson (Colectica)


    Accurate and complete metadata is essential for data sharing and for interoperability across different data types. However, the process of describing and documenting scientific data has remained a tedious, manual process even when data collection is fully automated. Researchers are often reluctant to share data even with close colleagues, because creating documentation takes so much time. 

  • Building metadata for economic data description and access
    Genevieve Podleski (Federal Reserve Bank of St. Louis)


    Making economic time series data accessible and understandable to an ever-widening audience of data users is a large and growing challenge. With input from sophisticated and novice data users and from data and metadata librarians, the Federal Reserve Bank of St. Louis has built a metadata standard for economic time series data that expands on other commonly used schemas to provide a more user-centric framework. This presentation will give an overview of the challenges of data description for cataloging, search, and education, and will present the specific solutions developed for the FRED economic data repository.

  • Documenting non-survey data in the Social Sciences with DDI-Lifecycle
    Wolfgang Zenk-Möltgen (GESIS - Leibniz Institute for the Social Sciences)
    Kerrin Borschewski (GESIS - Leibniz Institute for the Social Sciences)


    Non-survey data – such as experimental data, social network data, etc. – become more and more important for the work of social scientists. Also, their variety increases steadily. Thus, social science archives have to pay further attention to non-survey data and corresponding data documentation. This presents the Data Documentation Initiative with the challenge to broaden its scope, in order to enable the documentation of the different kinds of non-survey data within its metadata standard. 

    This presentation will display a case study of documenting non-survey data with DDI-Lifecycle, based on data examples retrieved from ‘datorium’ - the data repository service of the GESIS Leibniz Institute for the Social Sciences ( We will determine the information on study and dataset level needed, in order to enable data reuse. Furthermore, we will assess if those information can sufficiently be captured with DDI-Lifecycle. The insights retrieved from this case study can support the further development of the DDI standard. Additionally, they build a basis for data capture and archival work in the future, by considering and examining new data sources for the social sciences.

E1: Preservation Matters (Thu, 2017-05-25)
Chair:Sophia Lafferty-Hess

  • Who cares about 3D data preservation?
    Jennifer Moore (Washington University)
    Hannah Scates Kettler (University of Iowa)


    Preservation of 3D research data is a present and emerging need.  An increasing number of researchers are generating, capturing and/or analyzing 3D data, but are rarely focused on preservation or reuse. This paper and presentation will describe models of 3D data creation and use, outline the specific concerns for this data type, unpack complexities and challenges of preserving it, examine existing resources, and discuss possible standards and solutions while working through local case studies from the field of anthropology.

  • Preparing data files for preservation with Colectica Datasets
    Jeremy Iverson (Colectica)
    Dan Smith (Colectica)


    Data have no meaning without metadata. Statistical data tools like SAS, SPSS, and Stata provide limited metadata capabilities. Commonly, datasets contain variable and value labels, but even these are often missing. Without metadata, research is less credible. To enhance reproducibility and preservation, it must be simpler to add rich metadata to statistical files.

  • You can’t replicate what you can’t find: Data preservation policies in economic journals
    Courtney Butler (Federal Reserve Bank of Kansas City)
    Brett Currier (Federal Reserve Bank of Kansas City)


    This presentation will review digital preservation strategies of economic journals that have data availability policies. Long-term data preservation is critical for future reproducibility of economic research. A greater focus is being placed on making research data publicly available, but there is a dearth of official policies and discussion in the literature concerning preservation.

    A sampling of about 250 economics journals was developed by cross-referencing journal impact factors, h5-indices, IDEAS rankings, and Federal Reserve Bank of Kansas City staff authorship and service to the journal. This sampling analyzes whether data preservation policies are present either independently or as part of a larger data availability policy. Preliminary results indicate that while data availability policies are becoming much more common, data preservation policies are practically nonexistent. This has strong implications for future research reproducibility. In response, the Federal Reserve Bank of Kansas City is developing an institutional data preservation platform as an alternative solution.

E2: Encouraging Data Publishing in the Social Sciences and Humanities (Thu, 2017-05-25)
Chair:Karen Hogenboom

  • Publishing and reviewing data papers: experiences from the Research Data Journal for the Humanities and Social Sciences
    Louise Corti (UK Data Archive)
    Peter Doorn (DANS)


    In this paper we will, as lead editors of the Research Data Journal for the Humanities and Social Sciences, hosted by Brill publishers, provide our experiences of commissioning, editing and publishing data paper for the new peer-reviewed, online only, open access data journal, established by DANS in 2015. The Research Data Journal contains short publications (data papers) in which researchers describe their dataset: the context of their investigation of the problem and methods used. This is followed by an overall profile of the dataset, for example in terms of general characteristics or remarkable results. Conclusions as an ordinary scientific paper are not required, but there is room for concluding remarks. Readers can respond via a comments field to the content. The data must be deposited in a trusted repository, such as via DANS or the UK Data Service.

    Data papers are a relatively new venture for the humanities and social sciences, and we have had to work hard to show potential authors the value of them as a valuable output, to complement not only their own research publications, but to promote their published datasets. We showcase some of the papers and set out our requirements and review process for the papers.

  • 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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