A Collaborative Clearinghouse for Data Management Training and Education Resources
Nelson, John C.
Mayernik, Matthew S.
KeywordsData Management Training
Exchange of Good Practices
Research Data Training Registry
Learning Resource Catalog
Curriculum and Instruction
Library and Information Science
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AbstractObjective: The main objectives of this breakout session are for the Data Management Training (DMT) Clearinghouse team to: 1) introduce the Clearinghouse and its current design and implementation, 2) solicit submissions to its learning resource inventory, and 3) collect feedback upon its web interface and future development. Features of the Clearinghouse that will be demonstrated include how to search and browse its inventory as well as submit a learning resource to the Clearinghouse using the LRMI (Learning Resource Metadata Initiative) metadata format. The team will also share the roadmap for the Clearinghouse’s upcoming features. In order to provide feedback regarding the Clearinghouse’s usability, the team will invite the session attendees to test the Clearinghouse’s services and will encourage comments to guide its future development. Setting/Participants/Resources: Since the DMT Clearinghouse is entirely accessible via the web, in order to demonstrate the Clearinghouse successfully, a reliable (and preferably free of charge) internet connection, and an overhead projecting capability will need to be available to the presenter. It would also be very useful for the attendees of the session to have access to the same internet connection, so that if they desire, the attendees can follow along with the steps of the demonstration, and contribute to the Clearinghouse inventory. The main presenter will plan to bring her own laptop with built-in standard HDMI and USB ports. As a result, it will be helpful if a HDMI or USB cable could also be provided for the presenter to connect her laptop to the projecting equipment. Method: Many research organizations, government agencies, and academic institutions have been developing excellent learning resources in order to support and meet the needs for data management training. However, these learning resources are often hosted on various websites and spread across various scientific domains. Consequently, these resources can be difficult to locate, especially by those who are not already familiar with the creators/authors. This is a barrier to the use and reuse of these resources, and can have significant impact on the promotion and propagation of best practices for data management. To address this need within the Earth sciences, the U.S. Geological Survey’s (USGS) Community for Data Integration (CDI), the Federation of Earth Science Information Partners (ESIP), and the Data Observation Network for Earth (DataONE) have collaborated to create a web-based Clearinghouse1 for collecting data management learning resources that are focused on the Earth sciences. The initial seed funding for the effort was provided by a grant received from the USGS CDI earlier in 2016, and ESIP’s Drupal site provided the hosting infrastructure for the Clearinghouse. Members from the USGS, DataONE, ESIP’s Data Stewardship Committee and its Data Management Training Working Group, Knowledge Motifs LLC, as well as Blue Dot Lab met regularly between April and October, 2016 in order to discuss, create, and implement the content structure and infrastructure components necessary to build the current revision of the Clearinghouse. 1. http://dmtclearinghouse.esipfed.org Results: As a registry of information about the educational resources on topics related to research data management (initially focused on Earth sciences), the Clearinghouse serves as a centralized location for searching or browsing an inventory of these learning resources. Currently, the Clearinghouse offers search and browse functionality that is open to all, and submission of information about educational resources by login with a free ESIP account. To assist with discoverability, the learning resources are described using Learning Resource Metadata Initiative (LRMI) schema. Additionally, the resources may be associated with the steps of data and research life cycles, such as the USGS CDI’s Science Support Framework2 and DataONE’s Data Life Cycle3. Leveraging the team’s collective experience in creating, presenting and distributing data management learning resources, the Clearinghouse included the learning resources from USGS, ESIP, and DataONE as its initial inventory, but is expanding to resources from NASA and others. Crowdsourcing is currently the main mechanism for sustaining the Clearinghouse. Going forward, in addition to the built-in workflow to allow anyone from the public to submit descriptive information about the data management learning resources that s/he wishes to share, future capabilities will be added to enable contributions to review, edit, and rank the submissions, as desired. 2. https://my.usgs.gov/confluence/display/cdi/CDI+Science+Support+Framework 3. https://www.dataone.org/data-life-cycle Discussion/Conclusion: The DMT Clearinghouse team was successful in completing the initial development phase as scheduled for the first six months of its funding, including some informal usability testing of the interface. The team aims to continue to develop and enhance the Clearinghouse’s capabilities, including the evaluation of its usability, through collaboration with additional communities, and if feasible, adding the capability for bulk-loading of learning resources. Being able to present the Clearinghouse at the eScience Symposium would not only allow those who are involved with or would like to learn about data management to leverage the Clearinghouse’s resources, but also connect those who would like to contribute to the project with the Clearinghouse team. Ultimately, the Clearinghouse is designed so that the resources from its inventory could be used in a variety of data management training and education environments. By exposing the Clearinghouse to diverse users and communities, the Clearinghouse team can better assess how the Clearinghouse can be updated and what technological enhancements to pursue in the future in order to improve our support of research data management training needs.
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/28707
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