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Conference Presentations 2015

  • IASSIST 2015-Bridging the data divide: Data in the international context, Minneapolis
    Host Institution: University of Minnesota

D4: MPC data infrastructure: Integration and access (Thu, 2015-06-04)
Chair:Catherine Fitch

  • MPC data infrastructure: The challenges and benefits of data integration
    Lara Cleveland (Minnesota Population Center)
    Presentation:
  • Introduction to MPC data
    Katie Genadek (Minnesota Population Center)
    Presentation:
  • Terra Populus: Integrated data on populatioin and environment
    Tracy Kugler (Terra Populus)
    Presentation:
  • NHGIS: Access & integration strategies for U.S. Census tables and boundary data
    Jonathan Schroeder (University of Minnesota: Minnesota Population Center)
    Presentation:

D5: Curation and research data repositories (Thu, 2015-06-04)
Chair:Stephanie Tulley

  • New curation software: Step-by-step preparation of social science data and code for publication and preservation
    Limor Peer (Yale University)
    Stephanie Wykstra (Innovations for Poverty Action)

    [abstract]

    As data-sharing becomes more prevalent through the natural and social sciences, the research community is working to meet the demands of managing and publishing data in ways that facilitate sharing. Despite the availability of repositories and research data management plans, fundamental concerns remain about how to best manage and curate data for long-term usability. The value of shared data is very much linked to its usability, and a big question remains: What tools support the preparation and review of research materials for replication, reproducibility, repurposing, and reuse? This paper describes new data curation software designed specifically for reviewing and enhancing research data. It is being developed by two research groups, the Institution for Social and Policy Studies at Yale University and Innovations for Poverty Action, in collaboration with Colectica. The software includes curation steps designed to improve the research materials and thus to enable users to derive greater value from the data: Checking variable-level and study-level metadata, replicating code to reproduce published results, and ensuring that PII is removed. The tool is based upon the best practices of data archives and fits into repository and research workflows. It is open-source, extensible, and will help ensure shared data can be used.

    Presentation:
  • Using CED²AR to improve data documentation and discoverability within the United States Federal Statistical System Research Data Center (FSS-RDC)
    William Block (Cornell University)
    Todd Gardner (U.S. Census Bureau)

    [abstract]

    The secure environment within the Federal Statistical System Research Data Center (FSS-RDC) supports qualified researchers in the United States while protecting respondent confidentiality with state-of-the-art tools and processes. While the FSS-RDC contains data from an increasing variety of sources, few standards exist for the format and detail of metadata that RDC researchers have at their disposal. Data producers do not, as a rule, consider future research use of their data; rather, the metadata they produce is oriented toward the immediate objective at hand. Still, the RDCs need to have thorough documentation in order for researchers to carry out their projects. This presentation provides an update on the Comprehensive Extensible Data Documentation and Access Repository (CED²AR), a lightweight DDI-driven web application designed to improve the documentation and discoverability of both public and restricted data from the federal statistical system. CED²AR is part of Cornell's node of the NSF-Census Research Network (NCRN) and is now available within the FSS-RDC environment. CED²AR is being used by researchers not familiar with XML or DDI to document their data, supports variable level searching and browsing across codebooks, passively versions metadata, offers an open API for developers, and is simple to get up and running.

  • DDI as RDM: Documenting a multi-disciplinary longitudinal study
    Barry Radler (University of Wisconsin-Madison)

    [abstract]

    Adhering to research data management principles greatly clarifies the processes used to capture and produce datasets, and the resultant rich metadata provides users of those datasets the information needed to analyze, interpret, and preserve them. These principles are even more important with longitudinal studies that contain thousands of variables and many different data types. MIDUS (Midlife in the United States) is a national longitudinal study of approximately 12,000 Americans that studies aging as an integrated bio-psychosocial process. MIDUS has a broad and unique blend of social, health, and biomarker data collected over 20 years through a variety of modes. For nearly 10 years, MIDUS has relied on DDI to help manage and document these complex research data. In late 2013, the National Institute on Aging funded MIDUS to improve its DDI infrastructure by creating a DDI-based, harmonized data extraction system. Such a system allows researchers to easily create documented and citable data extracts that are directly related to their research questions and allows more time to be spent analyzing data instead of managing it. This presentation will explain the rationale, methods, and results of the project.

    Presentation:

E1: Geospatial and qualitative data (Thu, 2015-06-04)
Chair:Amber Leahy

  • Mixed method approaches to GIS: Qualities, quantities, and quandaries
    Andy Rutukowski (University of Southern California)

    [abstract]

    Geographic Information Systems (GIS) have the potential to make sense out of large collections of data. Historically GIS projects have been focused on quantitative data and analysis, whereas qualitative data has been mostly limited to classifying or labeling categories or types. More recently GIS work has shown how different types of qualitative data (such as interviews, Tweets, archival newspaper classifieds, photographs, etc.) can improve our understanding of quantitative data and therefore produce more meaningful maps. I will outline some recent cases of mixed methods approaches to GIS projects and discuss how these approaches benefited from including qualitative data. I will also consider the challenges of collecting, using, and archiving qualitative data. Lastly, I will consider the politics of mixing your methods in academic and other settings.

    Presentation:
  • The landscape of geospatial research: A content analysis of recently published articles
    Mara Blake (University of Michigan)
    Nicole Scholtz (University of Michigan)
    Justin Joque (University of Michigan)

    [abstract]

    Researchers at all levels frequently refer to existing journal articles for references to data sources, tools and methods, but often the lack of clear information about these prevents continuity and reproducibility in research practices. The authors undertook this study to capture information about the body of published literature utilizing geospatial research methods. The paper presents the results of content analysis on published articles that used methods of geospatial analysis as a major part of their research methodology. In order to better understand the landscape of current publishing practices and methodological approaches, the authors coded a sample of articles from a selection of journals drawn from a variety of disciplines that utilize geospatial analyses. They coded the articles for content, including: data citation; software and tools used; specificity of research methodology description; and methodological errors. In addition to the coded variables, the authors also compiled metadata about the the articles, including: journal title; journal subject area; primary author subject affiliation; primary author sex; and number of authors. The paper presents an exploration of the current state of data and geospatial related practices, especially transparency and quality of sources and methods.

  • GoGeo: A Jisc-funded service to promote and support spatial data management and sharing across UK academia
    Tony Mathys (EDINA, University of Edinburgh)

    [abstract]

    The implementation and encouragement of good data management practices and data sharing in the social sciences is a formidable challenge, especially for spatial data within academic disciplines that embrace the use of Geographical Information Systems (GIS), image processing and statistical software for research and teaching. The Joint Information Systems Committee (Jisc) has taken the lead to provide resources to support data management and sharing across UK academia. The GoGeo service is an example of Jisc's commitment to provide resources to securely manage and share spatial data. These resources include the Geodoc online metadata tool, which allows users to create, edit, manage, import, export and publish standards-compliant (ISO 19115, UKGEMINI, INSPIRE, DDI and Dublin Core) metadata records; the GoGeo portal, which allows users to publish their records into public or private metadata catalogues; and, ShareGeo, a repository for users to upload and download spatial data. The service also offers geospatial metadata workshops to introduce academics and students to geospatial metadata, standards and to the GoGeo service's resources. This presentation will provide an overview of the GoGeo service, which started as a project between the EDINA and the UK Data Archive in 2002. Its successes and shortcomings will be summarised as well.

  • 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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  • Resources

    Resources

    A space for IASSIST members to share professional resources useful to them in their daily work. Also the IASSIST Jobs Repository for an archive of data-related position descriptions. more...

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