Person:
Parham, Susan Wells

Associated Organization(s)
Organizational Unit
ORCID
0000-0001-6630-1488
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Publication Search Results

Now showing 1 - 10 of 15
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    Reviewing Data Management Plans: Practical Experience for New Service Providers
    (Georgia Institute of Technology, 2022-10-12) Winchester, Stacy ; Sheffield, Megan ; Exner, Nina ; Parham, Susan Wells
    Many academic librarians begin their work in research data support by offering reviews of Data Management Plans (DMPs, also called Data Management and Sharing Plans/DMSPs), which are required components of many grant proposals. After a researcher drafts a DMP, they may want someone to review it, assess its fit with best practices, and give feedback. Reviewing DMPs means evaluating and offering advice for improvement. But how does a library get started with reviewing DMPs? This workshop is tailored for new data librarians and subject librarians starting in data, who want to provide a DMP or DMSP support toolbox. The panel portion will compare real-world practices on how to provide DMP reviews for existing drafts created by researchers in different institutional settings. Next, presenters will compare different approaches, such as contrasting the DART Rubric (“DMPs as A Research Tool”) for in-depth National Science Foundation (NSF) reviews versus the Caltech NSF checklist for fast reviews; discussing how FASEB’s NIH DMSP contest rubric differs from the DART rubric; and summarizing how funder notes in DMPTool can be used for reviewing DMPs from various funders. This discussion will help new DMP evaluators think about how the process might change, and not change, for different funders’ DMPs. Finally, everyone will have guided practice in using the DART rubric to evaluate a simple research proposal and sketch out feedback for improvements in the DMP. At the end, the whole class will be better prepared to evaluate DMPs and offer researcher feedback on how to improve their Plan to make their research data FAIR.
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    Customizing DSpace: Developing Private Communities & Collections for Future Repository Integrations
    (Georgia Institute of Technology, 2022-06) Parham, Susan Wells ; Hagenmaier, Wendy ; Helms, Chris
    In this presentation, practitioners from the Georgia Tech Library will describe our collaboration with DSpace vendor Atmire to deploy code customization allowing greater granularity over access permissions to our unique digital content, and to merge two locally hosted DSpace instances. This collaboration arose from efforts at Georgia Tech to bridge the traditionally separate worlds of the institutional repository and archival digital collections by employing a loosely integrated ecosystem of DSpace, ArchivesSpace, Archivematica, and Vireo. A first step in this effort was to merge two locally hosted DSpace instances used for quite different purposes: our open access institutional repository and a dark archive of both unprocessed born-digital materials and preservation copies of digitized files. Because DSpace is inherently designed for providing open access to an institution’s intellectual output, we required code customization that would allow greater control over access to the restricted content migrated from our dark archive. We collaborated with Atmire to develop a phased deployment process that would allow Georgia Tech to maintain our local technical institutional knowledge and administrative control while employing Atmire’s specialized skill set in DSpace code customization and support. We will share lessons learned about the costs and benefits of this more complex deployment strategy.
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    Building a Collaborative Curation Framework: Working Towards Sustainable Digital Stewardship
    (Georgia Institute of Technology, 2021-11-02) Parham, Susan Wells ; Hagenmaier, Wendy ; Blewer, Ashley
    This presentation will discuss lessons learned from an academic research library’s endeavor to reconsider curation work holistically – across siloed content types, processes, systems, and departments. Georgia Tech team members will explore insights from our efforts working with Artefactual Systems to reimagine and sustain digital stewardship work across existing organizational silos.
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    NSF Data Management Plans as a Repository Research Tool
    (Georgia Institute of Technology, 2016-06) Carlson, Jake ; Hswe, Patricia ; Westra, Brian ; Whitmire, Amanda ; Parham, Susan Wells
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    Development of an Analytic Rubric to Facilitate and Standardize the Review of NSF Data Management Plans
    ( 2015-02-09) Parham, Susan Wells ; Carlson, Jake ; Hswe, Patricia ; Rolando, Lizzy ; Westra, Brian ; Whitmire, Amanda
    The last decade has seen a dramatic increase in calls for greater accessibility to research results and the datsets underlying them. In the United States, federal agencies with over $100 million in annual research and development expenditures are now compelled to create policies regarding public access to research outcomes.1 A sense of urgency has arisen, as researchers, administrators, and institutions must now determine how to comply with new funding agency requirements for data management planning and the sharing of data. As academic institutions develop or expand services to support researchers in meeting these planning and accessibility mandates, there is an increasing demand for mechanisms to better understand researcher needs and practices. The National Science Foundation (NSF) has required a data management plan (DMP) with each new proposal since January 2011. As a document produced by researchers themselves, DMPs provide a window into researchers’ data management knowledge, practices, and needs. They can be used to identify gaps and weaknesses in researchers’ understanding of data management concepts and practices, as well as existing barriers in applying best practices. Formal analysis of DMPs can provide a means to develop data services that are responsive to the needs of local data producers. The IMLS-funded “Data management plans as A Research Tool (DART) Project” has developed an analytic rubric to standardize the review of NSF DMPs. We seek to complement existing tools that have been designed to assist in the creation of a data management plan, such as DMPTool and DMPonline, by developing a tool that will enable consistent analysis of DMP content and quality ex post facto. In this poster, we describe the methodology for developing the analytic rubric, and present results from an initial assessment of DMPs from five U.S. research universities: Oregon State University (lead), Georgia Institute of Technology, Pennsylvania State University, the University of Michigan, and the University of Oregon. The rubric was developed through a review of the NSF’s general guidelines, as well as additional requirements from individual NSF directorates.2 In the rubric, DMP guidelines are translated into a set of discrete, defined tasks (e.g., “Describes what types of data will be captured, created, or collected”), describes levels of compliance for each task, and provides some illustrative examples. We are now conducting a more comprehensive study of DMPs, applying the rubric against a minimum of 100 plans from each study partner. The resulting data set will be analysed with a focus on common observations between study partners and will provide a broad perspective on the data management practices and needs of academic researchers. Once the analysis takes place, the rubric will be openly shared with the community in ways that facilitate its adoption and use by other institutions.
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    Re-purposing Archival Theory in the Practice of Data Curation
    (Georgia Institute of Technology, 2014-02-25) Rolando, Lizzy ; Hagenmaier, Wendy ; Parham, Susan Wells
    The research data sharing imperative has produced an explosion of interest around institutional research data curation and archiving. For institutions seeking to capture their intellectual output and ensure compliance with funding agency requirements, data archiving and data curation are increasingly necessary. With some notable exceptions, data curation in academic institutions is still a fairly nascent field, lacking the theoretical underpinnings of disciplines like archival science. As has been previously noted elsewhere, the intersection between data curation and archival theory provides data curators and digital archivists alike with important theoretical and practical contributions that can challenge, contextualize, or reinforce past, present, and future theory. Archival theory has critical implications for defining the workflows that should be established for an institutional data curation program. The Georgia Institute of Technology Library and Archives has been developing the services and infrastructure to support trustworthy data curation and born-digital archives. As the need for archiving research data has increased, the intersection between data curation and digital archives has become progressively apparent; therefore, we sought to bring archival theory to bear on our data curation workflows, and to root the actions taken against research data collections in long-standing archival theory. By examining two different cases of digital archiving and by mapping core archival concepts to elements of data curation, we explored the junction of data curation and archival theory and are applying the resulting theoretical framework in our practice. In turn, this work also leads us to question long held archival assumptions and improve workflows for born-digital archival collections.
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    Research Data Needs Assessment at Georgia Tech
    (Georgia Institute of Technology, 2013-10-21) Rolando, Lizzy ; Parham, Susan Wells ; Doty, Chris ; Valk, Alison
    From late 2010 through spring of 2013, Georgia Tech Library’s Research Data Project Team conducted a multi-faceted assessment of GT research data needs. In this program, we will discuss the four methodologies used in our data needs assessment. Each methodology served a different purpose, allowing us to collect different but complementary information. While our survey provided a broad overview of practices, individual interviews contributed to a more thorough and nuanced understanding of trends observed in the survey. By analyzing data management plans submitted alongside NSF proposals, we better understand how researchers expect to comply with funding agency requirements for data management and sharing. Finally, data archiving case studies prompted deep discussions with researchers about their data, as well as critical conversations within the Library about the types, formats, and volumes of data we can commit to preserving. This combination of methodologies and results informs our strategic goal to develop campus partnerships to collect, manage, share, and preserve Georgia Tech digital research data. While our assessment was conducted with a narrow scope of research data services, the methodologies employed can easily be adapted and used to study and assess other Library services.
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    NSF DMP Content Analysis: What Are Researchers Saying?
    (Georgia Institute of Technology, 2012-10) Parham, Susan Wells ; Doty, Chris
    As of January 2011,the National Science Foundation (NSF) has required a data management plan (DMP) as part of all grant proposals.Georgia Tech’s librarians and information technologists presented DMP development guidelines to support the requirement and later examined 181 plans submitted in the first eight months of 2011.
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    GALILEO Knowledge Repository (GKR) Metadata
    (Georgia Institute of Technology, 2012-08-09) Carter, Andy ; Downey, Catherine Jannik ; Fay, Robin ; Givens, Marlee ; Parham, Susan Wells
    GKR metadata origins and guidelines, creating metadata in DSpace, training GKR partners and a list of disciplines.
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    NSF DMP Content Analysis: What Are Researchers Saying?
    (Georgia Institute of Technology, 2012-07-23) Parham, Susan Wells ; Doty, Chris
    The National Science Foundation (NSF) implemented its requirement that all grant proposals include a two-­‐page data management plan (DMP) in January 2011. Like our colleagues at research institutions across the U.S., librarians and technologists at Georgia Tech developed services to support this mandate, including guidelines and workshops for developing a DMP. Toward the end of the requirement's first year, we assessed the impact of our consultation and outreach services by reviewing the content of submitted data management plans. In collaboration with the GT Office of Sponsored Programs, we examined NSF DMPs submitted by Georgia Tech researchers during the first eight months of the mandate (through 9/6/11). Of the 335 submitted proposals, we reviewed the content of 183 plans. We excluded those proposals that were grant supplements or transfers. While it is too early to draw conclusions regarding a correlation between the quality of data management plans and proposal approval, we used the DMP review to inform our own data services, data repository planning, and outreach.