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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

Poster Session (Thu, 2016-06-02)
Chair:Jenny Muilenburg

  • An Architecture for Social Science Data Curation
    Deirdre Lungley (UK Data Archive)


    The UK ESRC's Big Data Network (BDN) has a broad ambition to provide a coherent data infrastructure, harnessing new and novel forms of data, to provide social science researchers with the data, tools, technology and skills they need to undertake excellent, impactful research.

    The UK Data Service (UKDS), as part of the BDN, has been tasked with creating cost effective resourcing models. To this end we have adopted the Open Data Platform (ODP) data lake approach. We are utilising the Hortonworks Data Platform (HDP), with its associated data storage, processing and analytics components to showcase the power of the ODP model to provide a cost effective, scalable framework. Students and researchers working on this platform are exposed to industry-standard data tools.

    A hybrid architecture, a HDP cloud installation linked to an on-premises installation coupled with the ODP Hadoop governance framework (Ambari, Ranger, etc.) allows us to provide the Safe-Setting component of our "5-Safes: Secure Access to Confidential Data" commitment. A hybrid approach allowing us to serve both secure and non-secure data services.

    This poster will illustrate how this powerful, scalable, yet cost-effective architecture can, through generic processing, take Big Data from a raw text state through to powerful data products (per user aggregates) and information products (result visualisations).

  • The Metadata Model of The Dataverse Project: Helping More Data Become Discoverable
    Eleni Castro (Harvard University)


    Since 2006 the Dataverse Project, an open source data repository application developed at Harvard's Institute for Quantitative Social Science (IQSS), has provided metadata for datasets in the social sciences using the Data Documentation Initiative (DDI) standard. Over time the Dataverse application has expanded to also include metadata and file support for: additional domains such as astronomy and the biomedical sciences, as well as to increase interoperability with other systems. This poster will describe the process of expanding support to other domains for purposes of interoperability, discovery, preservation and reuse. It will also provide a visual graph outlining all of the currently supported APIs, metadata standards/ schemas (based on DDI Codebook, Dublin Core, DataCite 3.1, Virtual Observatory for astronomy data, and ISA-Tab for biomedical data), ontologies, and thesauri; along with what is planned to be supported in the future (e.g., DCAT, RDF, and

  • Academic Data Services and Makerspaces
    Samantha Guss (University of Richmond)


    Makerspaces have become increasingly popular on college campuses at the same time that support for data research, teaching, and learning has become a top priority for many academic libraries -- but what do these services have in common? Through an exploration of the Maker Movement and other trends in learning spaces, I situate academic data services within the larger conversations about space use in academic libraries and on college campuses. For example, what can data services providers learn from the philosophies and practices of makerspaces? What is the value of physical space for academic data services? By comparing and contrasting the service models and philosophies of different types of learning spaces, I aim to encourage conversation about how we conceive our own data services, how we communicate about them with our users and administrators, and how we can best meet the needs of our communities.

  • Working Across Boundaries: Public and Private Domains, Part 2
    Flavio Bonifacio (Metis Ricerche srl)


    This poster illustrates our efforts to install a Data Service in Turin using Nesstar. We presented the first part of this work in Toronto in 2013, concluding our poster with the information that Metis Ricerche had presented an application project for tender as a member of an Innovative ICT Pole concerning the installation of a data service for the conservation, reuse and dissemination of data. We obtained the funding requested and we are now pleased to announce that we have concluded our project. We will show our results of the second part of the work in our poster. We summarise the installation of a mixed data base built with numerical, text and multimedia data files, such as videos, photos and so on. We named this project Sy.Mul.Story, Multimedial System for storytelling analytics. We are currently presenting the project in Turin to various public and private organisations in order to obtain further funding.

  • Sustainable Environment Actionable Data (SEAD): A Knowledge Network for Collaboration, Data Curation, and Discovery
    Peter Granda (ICPSR - University of Michigan)


    SEAD is a project, sponsored by the National Science Foundation in the United States, to create data services for sustainability science research. This research supports fundamental science and engineering investigations and education needed to understand and overcome the barriers to sustainable human and environmental wellbeing and to forge reasoned pathways to a sustainable future. Sustainability research requires reliable cyberinfrastructure and an enhanced ability to manage, integrate, interpret, share, curate, and preserve data across a broad range of physical and social science disciplines. SEAD offers hosted end-to-end data services that serve this need, helping research teams whether large or small, to be more productive while reducing the effort required to preserve data for the long term. In particular, it serves researchers who produce and analyze heterogeneous data that is unique and at a fine resolution and granularity, those who must work in a collaborative environment, and investigators who lack access to reliable cyberinfrastructure.

    This poster will describe current and developing tools available to researchers in this field as they work through their projects, collect rich metadata throughout that whole process, consider ways to share their data, and discover the best location for its preservation. It will also focus on how the tools and services SEAD provides are applicable to a wide range of research projects beyond sustainability investigations. Finally, conference participants will leave with an understanding of how SEAD data services can be an integral part of best practices for data management, curation, and dissemination of data at their home institutions.

  • The CIC Geospatial Data Discovery Project: A Multi-Institution Project to Create an Open-Source Discovery Portal for Geospatial Data Resources
    Mara Blake (University of Michigan)


    In July 2015, the Committee on Institutional Cooperation (CIC) began the CIC Geospatial Data Discovery Project, a collaborative pilot project to provide discoverability, to facilitate access, and to connect scholars across the CIC to geospatial data resources. Nine of the fifteen CIC member institutions are participating in the project, including the University of Illinois at Urbana­-Champaign, the University of Iowa, the University of Maryland, the University of Michigan, Michigan State University, the University of Minnesota, Pennsylvania State University, Purdue University, and the University of Wisconsin-­Madison. The project will support the creation and aggregation of discovery-focused metadata describing geospatial data resources from participating institutions and will make those resources discoverable via an open source portal . The collectively supported project provides the project staffing and technical infrastructure to host and develop the services.

    The poster will show the organizational formation and structure of this collaborative project, as well as the established processes for collaborative geospatial metadata creation and portal development.

  • A Collaborative Questionnaire and Study Editor within the German Longitudinal Election Study (GLES)
    Claus-Peter Klas (GESIS - Leibniz Institute for the Social Sciences)
    Oliver Hopt (GESIS - Leibniz Institute for the Social Sciences)
    Manuela Blumenberg (GESIS - Leibniz Institute for the Social Sciences)
    Wolfgang Zenk-Moltgen (GESIS - Leibniz Institute for the Social Sciences)


    As presented at the EDDI 2015, several election surveys will be prepare and run on the German national election in 2017 (see overall process to prepare the surveys consists of several steps beginning with preparing and evaluating previous questionnaires within a distributed team, hand over the questionnaires to the polling agency for running the surveys, and finally hand over the results for documentation and archival processes. All these steps are currently done manually, in some cases semi-automatically. Word/ PDF files are used for discussion, documentation and hand-over, resulting in repeated and error-prone documentation steps.

    Based on the GESIS DDI-FlatDB infrastructure we will give an update on the first DDI-L based prototype for our collaborative questionnaire and study editor. The functionality will be creating, editing and structuring questions and study information according to the GLES user needs. All edited information is stored with versioning. In addition we will integrate a comment system for the researchers to interact and provide a rate system, to give certain questions more weight. At any time, the system will be able to export the current status as DDI, Word or PDF file.

  • UK Data Service Impact through Narratives and Case Studies
    Rebecca Parsons (UK Data Service)
    Scott Summers (UK Data Service)
    Louise Corti (UK Data Service)


    The UK Data Service plays a key role in supporting researchers in their quest to provide impact for their funded research.

    We use case studies, including video and modern infographics, to highlight various strands of impact - from showcasing the value of their data deposit to demonstrating powerful and policy relevant reuse of those data.

    In this poster we will demonstrate our portfoilo of 'impact' wares.

  • Doing the right thing: how you construct a service that allows researcher to access unconsented data?
    Carlotta Greci (UK Data Archive, University of Essex)
    Kakia Chatsiou (UK Data Archive, University of Essex)


    The Administrative Data Research Network is a partnership between UK universities, government, national statistical authorities and aims to facilitate access to administrative data previously difficult to access for research. Administrative data refer to information collected primarily for operational purposes by government and other organisations when delivering a service. Within the complex UK data sharing framework, the Network enables secure and lawful access to de-identified linked administrative data to "trusted" researchers.

    Administrative data are in some cases reused for secondary analysis without the data subjects' explicit consent, so the Network only acts when there is a legal right for access and appropriate safeguards are in place. Despite the processing that UK and EU legislation enables, public concern about use of their data is high. Hence the ADRN have been constructed with a specific focus on providing robust and transparent governance and secure data-handling standards.

    From setting criteria on the eligibility to use the Network, an Approvals Panel screening all proposals, the use of Trusted Third Parties to handle data matching, to secure environments with rigorous access procedures, this poster provides an overview of the ADRN model as a way to enable research, using administrative data, to benefit the public

1H: Online user support and training (Fri, 2016-06-03)
Chair:Cameron Tuai

  • Online Tools and Training For Access and Analysis of Restricted Government Data Files
    Warren Brown (Cornell University)


    The Cornell Institute for Social and Economic Research (CISER) has developed tools and training modules for online access enabling researchers to more effectively work with official restricted access statistical files. The research steps covered are: discovery; metadata; practice data sets; summary statistics; and analytical exercises. Cornell's CED2AR repository of metadata in DDI 2.5 enables researchers to discover restricted access official statistical files, and government statistical agencies to securely manage details of documentation. CED2AR processes the metadata and produces search terms that are accessible by major search engines thus enabling discovery of data files based on descriptive information on the study, file and variables. The codebooks for files discovered by the search, may then be browsed and variables searched for. CED2AR enables side-by-side comparison of similar variables across files to aid in the selection of the most appropriate file. Links are provided to zero observation versions of the restricted access files in SAS and Stata for program development and proofing. These resources enable researchers to prepare well-informed applications to the statistical agency data custodians based on knowledge of the data file prior to actual access. Once approved for access, CED2AR provides detailed summary statistics further enabling approved researchers to validate their initial analyses. Finally, links are provided to analytical exercises taking the researcher beyond summary statistics to elementary modeling. At that point the researcher is well prepared to be productive and successful in the investigation of their scientific question. For this presentation the following restricted access files are used: American Community Survey (US); Current Population Survey (US); and Sample of Integrated Employment Biographies-Scientific Use File (DE).

  • 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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