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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

1C: Data appraisal/selection (Thu, 2016-06-02)
Chair:Bobray Bordelon

  • A Data-Driven Approach to Selecting and Curating Content at a Domain Repository
    Justin Noble (Inter-university Consortium for Political and Social Research)
    Amy Pienta (Inter-university Consortium for Political and Social Research)

    [abstract]

    The volume of scientific research data being produced is expanding at a rapid rate in the social sciences. We propose to use administrative repository data to guide selection and appraisal practices to ensure that curation resources are used effectively to make the most valuable content findable, understandable, accessible, and usable now and in the future. ICPSR captures information about search behavior to guide what content to add to the repository and also analyzes historic information about data usage to ensure that data likely to get the widest use are curated to the highest level. This paper will share these two analytic models and results. Considerations such as data collection methodology, currency of topic, and breadth and quality of the data surface as key attributes that influence the desirability of data collections. By analyzing a decade of data use patterns, we present information about attributes that predict longer term use of data as well. Finally, how the data-driven models can be linked to repository practices and policies are discussed.

  • Your Data Wish is Granted: Establishing a Library Data Grants Program at the University of Michigan
    Mara Blake (University of Michigan)

    [abstract]

    In the fall of 2015 the University of Michigan began the Library Data Grants Program as a two-year pilot project. Adding data to the library's collection can prove challenging because of high cost and challenging licensing. Additionally, the impact of those challenges can make the timeframe to acquire data sets long, challenging many researchers requesting data from the library. The library created this program in an attempt to streamline requests for data and clearly communicate a time line to requesters. An additional aim of the program is to create closer, positive relationships for our community of data users on campus. The project received applications from researchers for the library to acquire data sets required for their research projects. The Library Data Grants Committee assessed the proposals based on ability to purchase or license the data, merit of research project, cost, and expected use of the data to make awards. The presentation will provide an assessment of the program after the first cycle of applications and awards, and outline the future direction of the project and broader data collections at the University of Michigan Library.

2C: Promoting research data sharing (Thu, 2016-06-02)
Chair:Peter Granda

  • Incentivize Replication in Economics - Can Data Journals Help?
    Ralf Toepfer (ZBW Leibniz Information Centre for Economics)

    [abstract]

    Though replications and reproducible research are the touchstones of the scientific method, up to now there are just a few published replications in the pages of economics journals. Even in cases where replication attempts fail in reproducing the results of original research paper, economists do not really seem to be particularly interested in such replications. The main reason is that replications do not lead to academic prestige. However, the awareness among researchers, that empirically-based research often is based on shaky grounds, has increased in the last years - not only in economics but also in sociology and psychology. The publication of positive and negative replication attempts can contribute to regain public trust and credibility in empirical economics' research. Against this background my talk will discuss how a data journal could incentivize replications in economics. I will present some studies which describe the outcome of replication attempts and discuss the meaning of failed replications in economics. As a possible way forward I will present the idea of establishing data journals to give a stronger incentive for Economists to conduct replication studies.

    Presentation:
  • Improving Research Data Sharing by Addressing Different Scholarly Target Groups: Individual Researchers, Academic Institutions, Or Scientific Journals
    Monika Linne (GESIS - Leibniz Institute for the Social Sciences)

    [abstract]

    It is gratifying that in recent years a growing awareness for the necessity of research data preservation has led to the implementation of various data sharing repositories in the field of the Social and Economic Sciences. However, some of these repositories address only a specific user group, since issues such as use rights, data access, workflows, data review processes, or metadata schemas are oriented to the needs of a particular target group. Aware of this matter, GESIS is committed to the continuous development of its data sharing services, aiming at different user groups, such as individual researchers, academic institutions or scientific journals. These groups place diverse demands on a data sharing tool, which have to be taken into consideration. Therefore, GESIS provides data sharing tools with functionalities adjusted to certain user groups. These are, for instance, individual researchers without an institutional affiliation or authors, who want to publish data sets they have used for the publication of their research results in academic journals.
    Additionally, GESIS, in collaboration with the Social Science Centre Berlin, the German Institute for Economic Research, and the German National Library of Economics started the development of SowiDataNet. This tool concentrates on the specific demands of data that has been collected in academic institutions. The overarching objective is the implementation of a national data infrastructure for decentralized research data from the Social and Economic sciences in Germany. SowiDataNet will also consider functionalities for organizational data management of internal data that is not intended to be published (yet!).
    The barriers and concerns about data sharing can only be overcome, if repositories respond to the specific requirements of different user groups. All the benefits and possibilities of data sharing can only be exploited, if the tool is equipped to render them accessible.

  • The Role of Case Studies in Effective Data Sharing, Reuse and Impact
    Rebecca Parsons (UK Data Service)
    Scott Summers (UK Data Service)

    [abstract]

    The effectiveness and impact of social science research is under constant review. From the sharing, reuse and archiving of social science research data to the outcomes, reach and impact of research, social science professionals are under increasing pressure to realise the maximum potential of their data collections and their research findings.
    The UK Data Service is playing a key role in supporting researchers in this process and is using detailed and well-received case studies to provide them with guidance on the best practice for sharing and reusing data and also identifying and capturing the impact of research.
    The impact of research is now routinely considered when considering the "success" of funded projects, but the reality of identifying and capturing impact can be a challenge. Publishing data in its own right is now recognised as being impactful to funders, yet exposing this narrative through "showcasing" is under exploited. Such narratives can incentivise others to share data and also improve the quality of the data and documentation. This paper seeks to explore the role that case studies of research can play in this regard. It achieves this by exploring two separate, but intertwined questions.
    This paper considers how to shape and position a powerful case study; identifying common challenging issues encountered when sharing data and in effectively capturing impact.
    The paper also examines the role that depositor and user case studies can play in enhancing the reuse of a showcased data collection. To achieve this, a variety of illustrative depositor and impact case studies are discussed, highlighting the role that these can have on research projects.
    The paper concludes with some tentative conclusions on how the UK Data Service can continue to develop the role of cases studies in its work and assist our users throughout the lifecycle of their own projects.

  • How to Convince Researchers of the Usefulness of Data Archiving - The Data Archive in Finland (FSD) as a Case Study
    Annaleena Okuloff (Finnish Social Science Data Archive, University of Tampere)
    Katja Falt (Finnish Social Science Data Archive, University of Tampere)

    [abstract]

    Data archiving and reuse is not a common practice in the humanities and health sciences. Researchers in these disciplines can be hesitant to deposit their research data for archiving and reuse. Data repositories and archives spend a lot of time advertising their services at academic institutions and researchers in order to change the attitudes towards open data. This advertising aims at alleviating the concerns researchers may have towards archiving research data.
    We present a case study, the Data Archive in Finland (FSD) that is broadening its services to the health sciences and humanities. Data sharing practices in these disciplines have not been established. Thus it is vital to introduce the benefits of open research data to these disciplines.
    In order to chart the researchers' attitudes towards and knowledge about data archiving and reuse, a web-based survey was executed and directed at researchers in the health sciences and humanities. Based on the answers provided in the survey it has been possible to identify the concerns of the researchers and to draw up efficient ways to promote data archiving. We thus present some of the themes emerging from the survey, connected to data archiving, as well as strategies used to approach researchers.

2G: Research data management infrastructure and service models (Thu, 2016-06-02)
Chair:Jane Burpee

  • Developing Human Infrastructure to Support Research Data Management Services
    Christie Peters (University of Kentucky)

    [abstract]

    In an effort to develop data management expertise within the library, a team of librarians who have expertise with various aspects of research data management at the University of Kentucky (UK) Libraries established a semester-long training program aimed at retooling library faculty in the area of research data management. The project team distributed a survey beforehand aimed at discerning the perceived level of knowledge about and comfort level with various aspects of research data management, related training needs, and opinions about the level of support needed for data management-related services on campus. The initial 4-day workshop, which included ten guest speakers from across campus, utilized hands-on activities to help participants process the information conveyed. Monthly brown bag sessions on related topics, a semester-long badging program aimed at providing additional resources, motivation and recognition for the various skills achieved, and a concluding celebration at the end of the semester with an external speaker followed the initial workshop. This presentation outlines the results of the pre- and post-workshop surveys, an overview of the training program, feedback from the program's first cohort, and lessons learned throughout the program.

  • Supporting the Development of a National Research Data Discovery Service - a Pilot Project
    Stuart Macdonald (University of Edingburgh)

    [abstract]

    The Jisc-funded UKRDDS Project aims to develop a national Research Data Discovery Service to allow discovery of research data held in institutions across the UK. The University of Edinburgh is one of the pilot institutions funded to support the development of the service by harvesting metadata records for datasets generated as part of the research process by local researchers.
    The University of Edinburgh Research Data Management (RDM) Roadmap is a major Information Services-led project to provide a comprehensive RDM & storage service. One of the main objectives of the RDM Roadmap falls under the category of "Data Stewardship", namely tools and services to aid in the description, deposit, and continuity of access to completed research data outputs. This reflects one of the EPSRC funding body's key research data expectations and is a University RDM policy requirements.
    Currently two RDM services are available to University of Edinburgh researchers to address data stewardship, namely:

    •   PURE, the University's Current Research Information System, where descriptive metadata about datasets can be added along with files, persistent identifiers and links to related research outputs or projects.
    •   Edinburgh DataShare, a free-at-point-of-use open access data repository which allows University researchers to upload, share, and license their data resources for online discovery and re-use by others.

    This paper will outline the prospective service and the pilot project. It will detail the use of PhD interns to support the work of Information Services through engagement with the university research community in order help identify and describe data assets for ingest into both PURE and DataShare, and to validate and quality control metadata records for the purpose of being harvested by UKRDDS.

  • Modularizing Archive Services in the Social Sciences
    Oliver Watteler (GESIS, Leibniz Institute for the Social Sciences)

    [abstract]

    Social science projects and public institutions produce increasing amounts of data to answer research questions. Although a growing number of these data sources are made available, some data producers are not looking for the "classical" full archival service, but only to particular services like long-term preservation (e.g. in institutional repositories). This development was foreseeable and poses challenges to the organizational structures of existing data service providers.
    To address these challenges, the Data Archive of GESIS, the Leibniz Institute for the Social Science, will modularize its service portfolio. We will move away from offering services as fixed "bundles" only (e.g. documentation, long-term preservation, registration, and distribution or onsite access for all) and aim instead at more accurately customized offers for depositors. By modularizing our services and introducing improved workflow management we hope to make archiving and data services more efficient and more beneficial for the scientific community. GESIS will deliver more timely services, research projects will see reduced costs in time and effort (e.g. in data preparation). Other specialized data services providers might profit from hearing of our experience. This presentation reviews the first phase of services restructuring. We set up new workflows and develop management capacities. Its second aim is to open an exchange with other institutions that have undergone structural changes or are planning to do so.

    Presentation:
  • Research Data Management Tools and Workflows: a Report from the Front
    Cristina Ribeiro (University of Porto)
    Joao Rocha da Silva (University of Porto)
    Joao Aguiar Castro (University of Porto)
    Ricardo Carvalho Amorim (University of Porto)
    Joao Correia Lopes (University of Porto)
    Gabriel David (University of Porto)

    [abstract]

    Research datasets include all kinds of objects, from web pages to sensor data, and originate in every domain. Concerns with data generated in large projects and well-funded research areas are centered on their exploration and analysis. For data on the long tail, the main issues are still how to get data visible, satisfactorily described, preserved, and searchable.
    Our work aims to promote data publication in research institutions, considering that researchers are the core stakeholders and need straightforward workflows, and that multi-disciplinary tools can be designed and adapted to specific areas with a reasonable effort. For small groups with interesting datasets but not much time or funding for data curation, we have to focus on engaging researchers in the process of preparing data for publication, while providing them with measurable outputs. In larger groups, solutions have to be customized to satisfy the requirements of more specific research contexts.
    The tools available to researchers can be decisive for their commitment. We focus on data preparation, namely on dataset organization and metadata creation. For groups in the long tail, we propose Dendro, a research data management platform based on open-source tools, and explore automatic metadata creation with LabTablet, an electronic laboratory notebook. For groups demanding a domain-specific approach, our analysis has resulted in the development of models and applications to organize the data and support some of their use cases. Overall, we have adopted ontologies for metadata modeling, keeping in sight metadata dissemination as Linked Open Data.

  • 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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