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Conference Presentations 2012

  • IASSIST 2012-Data Science for a Connected World: Unlocking and Harnessing the Power of Information, Washington, DC
    Host Institution: National Opinion Research Center (NORC)

Pecha Kucha: B (Wed, 2012-06-06)

  • Data Publishing and Metadata creation
    Nicole Quitzsch (GESIS - Leibniz Institute for the Social Sciences)

    [abstract]

    The classic form of dissemination of scientific data is to publish only the results of data collection. Their results are published in professional journals, usually without the underlying data. Data should no longer be exclusively part of a scientific publication. This is why the GESIS - Leibniz-Institute for the Social Sciences and the ZBW - Leibniz Information Centre for Economics decided to implement the DOI registration portal for German social and economic data - da|ra. The datasets receive unique DOIs as citable identifiers and all relevant metadata information. Persistent identifiers together with their bibliographical information provide the opportunity to find and to cite primary data in scientific publications. The data is clearly quotable about the DOI. Pre-condition for the citation of data is the creation of qualitative metadata. The da|ra metadata schema consists of mandatory and optional fields. It is compliant with other important metadata standards to ensure metadata interoperability. This presentation will deal with the different steps need to be done for the data publishing process and focus on how new features are included in the already existing DOI service. It will show that using the services enables scientists comfortably to discover, find and access scientific data.

    Presentation:
  • Metadata in organisational surveys
    Tony Machin (University of Southern Queensland)
    Presentation:

C1: Collaboration and Data Support (Thu, 2012-06-07)

  • Johns Hopkins University Data Management Services: Reviewing Our First Year
    David S Fearon (Johns Hopkins University)
    Betsy Gunia (Johns Hopkins University)

    [abstract]

    Of the growing number of academic libraries helping researchers with data management, Johns Hopkins University has one of the first “full service” infrastructures providing data planning consultation and a repository, JHU Data Archive, built specifically for research data. Although drawing upon the expertise of our partner, the Data Conservancy, we are continually evolving our service model, and testing by trial its sustainability and accommodation of diverse practices among disciplines. We will report on the first year of our Data Management Services program, focusing on planning support for NSF's data management plan requirements, and the particular needs of social science. We have developed tools, such as a questionnaire and in-person meetings, for helping researchers with NSF's 2-page plan, and project management workflows for depositing data into the JHU Data Archive. We will discuss outreach strategies for publicizing our services, and incentives for researchers to invest in data preservation and sharing. Case examples from working with a range of social sciences illustrate data management issues distinct from “big data” sciences, such as sharing data with personal identifiers, managing qualitative research, and multi-disciplinary collaborations. With data management requirements expanding among funders, innovations by academic libraries are of broad interest to data curation professionals.

    Presentation:
  • Collaborative Data Management: Best Practices throughout the Data Life Cycle
    Amber Leahey (Scholar Portal, Ontario Council of University Libraries)
    Jacqueline Whyte Appleby (Scholar Portal, Ontario Council of University Libraries)
    Steve Marks (Scholar Portal, Ontario Council of University Libraries)

    [abstract]

    While there is increased recognition of the value of rigorous data management, budgets and resources for this kind of activity are stagnant or decreasing. Perhaps because of this, there has been a growing interest in pursuing collaborative efforts to implement best practices throughout the research data life cycle. Effective collaborations can be local, involving individual researchers or research teams, or large-scale initiatives involving multiple institutions in either informal relationships or formal partnerships such as consortia. When data is collected, processed, archived, or disseminated as part of a collaborative process, the potential for problems is heightened - but so are the rewards. This session will look at examples of effective collaborative data management at all stages of the data life cycle, and consider some of the challenges and potential successes at play when we work together to improve data collection, preservation, and access. Examples will range from landmark projects to emerging initiatives, and include case studies from the Ontario Council of University Libraries (OCUL), an academic library consortium

    Presentation:
  • Establishing Collaborative Networks in Sporting Data
    Carol Perry (University of Guelph)
    Michelle Edwards (University of Guelph)

    [abstract]

    Over the past decade, it has been standard practice in academic institutions for data centres to be the primary location for services related to supporting data. With the advent of changing funder requirements related to research data, data support has quickly become foremost on the minds of administrators across campuses. At the University of Guelph, seemingly disparate groups are now collaborating to provide a suite of services in support of research and the data it produces. This presentation will probe the emerging trend of bringing together expertise from different stakeholders in order to streamline services while enriching the level and depth of support available to researchers.

    Presentation:
  • Integrating Numeric, Statistical, and Geospatial Data Services for Graduate Students
    Maria A Jankowska (Charles E. Young Research Library, UCLA)

    [abstract]

    This paper argues for collaboration among faculty, academic subject specialists, data librarians, GIS specialists, and data curators in order to respond to growing graduate student demand for digital statistical information and data. It presets weaknesses and strengths of a model operating at the Charles E. Young Research Library at the University of California, Los Angles. The article outlines a process in which graduate students benefit from having access to multiple points of service. The diversity of service points fosters relationships among all participants and improves communication between instructors and library staff, ultimately strengthening services offered to graduate students. Major challenges to the ongoing successful partnership include the availability of needed resources and sustainability of the model, which fulfills graduate students' needs for numeric, statistical, and geospatial data.

    Presentation:

C2: DDI Implementation, Production, and Migration (Thu, 2012-06-07)

  • Metadata-driven Survey Design at the Australian Bureau of Statistics
    Samuel C Spencer (Australian Bureau of Statistics)

    [abstract]

    DDI provides survey methodologists with ample metadata to describe statistical survey design. However it is widely recognise that description of processes is not enough, we must be able to use metadata to drive statistical workflows. One particular goal is the ability to automatically generate personalised and dynamic electronic forms from structured metadata. The Australian Bureau of Statistics has conducted research examining how this can be achieved through the novel use of XML technologies to enhance standard DDI 3.1 XML. By examining the use of XSL transforms, and XPath specifications embedded with DDI Lifecycle metadata, we can provide metadata-driven 'industrialisation' to statistical processes. To demonstrate this capability, this talk presents a case study from the Australian Bureau of Statistics, featuring a late-stage prototype of an XSLT system that automatically creates dynamic web forms featuring complex question sequencing and word-substitution in questions using DDI Lifecycle XML. This is demonstrated using DDI3.1 that describes the complex series of ABS instruments - Monthly Population Survey, which includes the Australian Labour Force Survey as well as supplementary questionnaires.

    Presentation:
  • Integrating DDI 3-based Tools with Web Services: Connecting Colectica and eXist-db
    Johan Fihn (Swedish National Data Service)
    Jeremy Iverson (Colectica)

    [abstract]

    The Swedish National Data Service (SND) maintains metadata about its holdings in the Data Documentation Initiative's DDI-Lifecycle format. The total amount studies in the holdings amounts to over one thousand, both quantitative and qualitative. SND stores and indexes this metadata using eXist-db, an open source XML database. Colectica is another DDI 3-based tool, but by default it uses a different repository structure for storing metadata. In order to allow Colectica tools to interact with SND metadata, we implemented a set of Web Services on top of eXist-db that allow Colectica to store and load information using eXist-db. We will demonstrate functionality provided by the eXist-db system, discuss the steps we took to integrate with Colectica, and demonstrate the resulting functionality with the two systems working together. We will also present recommendations on how to interact between DDI repositories in general and DDI tools. Implementations on our approach could be done from other DDI repositories.

    Presentation:
  • Feature Enhancement of Easy DDI Organizer (EDO)
    Yuki Yonekura (University of Tokyo)
    Keiichi Sato (University of Tokyo)
    Yukio Maeda (University of Tokyo)

    [abstract]

    From 2010, Social Science Japan Data Archive started to study DDI and also develop Easy DDI Organizer(EDO). EDO is a tool which helps researchers to conduct social surveys. It enables researchers to record survey metadata such as study purpose, sampling procedure, data collection, question, and variable descriptions along with data lifecycle. In this year, following new features were added to the EDO. These are importing SPSS files, question sequence manager, exporting codebook/questionnaire, and English interface. We will introduce these new features at the presentation.

  • Migrating a Large Collection to DDI-Lifecycle
    Wolfgang Zenk-Möltgen (GESIS, Leibniz Institute for the Social Sciences)

    [abstract]

    The GESIS Data Archive holds about 5000 studies, mainly social science surveys. The documentation of these studies consists of study descriptions, variable descriptions with questions and answers, and other material like methodological information. The datasets are documented by tools that use the DDI-Codebook metadata standard (formerly known as DDI 2). Since 2008, the DDI Alliance has published the DDI-Lifecycle standard (DDI 3/DDI-L), that focuses on re-usable documentation and the support of the full research data lifecycle. To use some of the many advantages that DDI-L provides, a migration of the available documentation should be conducted. The talk will focus on the benefits and challenges of such a migration project, and will show possible options during that process. The use of the recently published DDI version 2.5 will be considered because it aims at making the migration to DDI-L easier. The support of software for the format conversion and for the necessary re-arrangement of documentation parts will be investigated. The consequences of such a migration project for the future maintenance of the data and documentation will be shown.

    Presentation:
  • 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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