A Spatial Collaboration: Building a Multi-Institution Geospatial Data Discovery Portal

As academic education and research increasingly take advantage of geospatial data and methodologies, we see a corresponding exponential growth in the number of available geospatial resources in the form of GIS datasets and scanned historical maps. However, users can experience difficulty finding these resources due to the unconnected multitude of platforms and clearinghouses that host them. Additionally, the resources are not always well described with web semantic metadata that facilitates discovery. In response to this challenge, The Big Ten Academic Alliance Geospatial Data Project began in 2015 to provide discoverability, facilitate access, and connect scholars to geospatial resources. Our project leverages a multi-institutional collaboration and open source technologies to improve discovery for users of geospatial data and scanned maps. We outline collaborative workflows and strategies for a successful multi-institution collaboration

IASSIST / DCN Data Curation Workshop

Workshop at the 2018 IASSIST Annual Conference.“Launching the Data curation Network: A cross-institutional staffing model for curating research data” funded 2018-2021 by the Alfred P. Sloan Foundation grant G-2018-10072

A Spatial Collaboration: Building a Multi-Institution Geospatial Data Discovery Portal

As academic education and research increasingly take advantage of geospatial data and methodologies, we see a corresponding exponential growth in the number of available geospatial resources in the form of GIS datasets and scanned historical maps. However, users can experience difficulty finding these resources due to the unconnected multitude of platforms and clearinghouses that host them. Additionally, the resources are not always well described with web semantic metadata that facilitates discovery. In response to this challenge, The Big Ten Academic Alliance Geospatial Data Project began in 2015 to provide discoverability, facilitate access, and connect scholars to geospatial resources. Our project leverages a multi-institutional collaboration and open source technologies to improve discovery for users of geospatial data and scanned maps. We outline collaborative workflows and strategies for a successful multi-institution collaboration

Extending the Research Data Toolkit: Data Curation Primers

Niche and proprietary data formats used in cutting-edge research and technology have specific curation considerations and challenges. The increased demand for subject liaisons, library archivists, and digital curators to curate this variety of data types created locally at an institution or organization poses difficulties. Subject liaisons possess discipline knowledge and expertise for a given domain or discipline and digital curation experts know how to properly steward data assets generally. Yet, a gap often exists between the expertise available within the organization and local curation needs. While many institutions and organizations have expertise in certain domains and areas, oftentimes the heterogeneous data types received for deposit extend beyond this expertise. Additionally, evolving research methods and new, cutting-edge technology used in research often result in unfamiliar and niche data formats received for deposit. Knowing how to ‘get-started’ in curating these file types and formats can be a particular challenge. To address this need, the data curation community have been developing a new set of tools – data curation primers. These primers are evolving documents that detail a specific subject, disciplinary area or curation task, and that can be used as a reference or jump-start to curating research data. This paper will provide background on the data curation primers and their content detail the process of their development, highlight the data curation primers published to date, emphasize how curators can incorporate these resources into workflows, and show curators how they can get involved and share their own expertise

Launching the Data Curation Network

Presentation at the 2018 Research Data Access and Preservation (RDAP) Summit in Chicago, IL.“Launching the Data curation Network: A cross-institutional staffing model for curating research data” funded 2018-2021 by the Alfred P. Sloan Foundation grant G-2018-10072

Data Curation Network: Developing and Scaling Research Data Management

Presentation at the NISO Virtual Conference: Open Data Projects.“Launching the Data curation Network: A cross-institutional staffing model for curating research data” funded 2018-2021 by the Alfred P. Sloan Foundation grant G-2018-10072

Implementing a Cross-Institutional Staffing Model for Curating Research Data

Poster presented at the Research Data Alliance (RDA) 11th Plenary in Berlin, Germany.“Launching the Data curation Network: A cross-institutional staffing model for curating research data” funded 2018-2021 by the Alfred P. Sloan Foundation grant G-2018-10072

Launching the Data Curation Network

Presentation at the 2018 International Digital Curation Conference (IDCC) in Barcelona, Spain.“Launching the Data curation Network: A cross-institutional staffing model for curating research data” funded 2018-2021 by the Alfred P. Sloan Foundation grant G-2018-10072

Data Curation Network: A Cross-Institutional Staffing Model for Curating Research Data

Funders increasingly require that data sets arising from sponsored research must be preserved and shared, and many publishers either require or encourage that data sets accompanying articles are made available through a publicly accessible repository. Additionally, many researchers wish to make their data available regardless of funder requirements both to enhance their impact and also to propel the concept of open science. However, the data curation activities that support these preservation and sharing activities are costly, requiring advanced curation practices, training, specific technical competencies, and relevant subject expertise. Few colleges or universities will be able to hire and sustain all of the data curation expertise locally that its researchers will require, and even those with the means to do more will benefit from a collective approach that will allow them to supplement at peak times, access specialized capacity when infrequently-curated types arise, and stabilize service levels to account for local staff transition, such as during turn-over periods. The Data Curation Network (DCN) provides a solution for partners of all sizes to develop or to supplement local curation expertise with the expertise of a resilient, distributed network, and creates a funding stream to both sustain central services and support expansion of distributed expertise over time. This paper presents our next steps for piloting the DCN, scheduled to launch in the spring of 2018 across nine partner institutions. Our implementation plan is based on planning phase research performed from 2016-2017 that monitored the types, disciplines, frequency, and curation needs of data sets passing through the curation services at the six planning phase institutions. Our DCN implementation plan includes a well-coordinated and tiered staffing model, a technology-agnostic submission workflow, standardized curation procedures, and a sustainability approach that will allow the DCN to prevail beyond the grant-supported implementation phase as a curation-as-service model