Cultivating a Data Science Learning Community

Poster for 2021 Internal Funding Showcas

Teaching Mineralogy with Crystal Structure Databases and Visualization Software

This resource collection provides information on how to incorporate crystal structure databases and 3-D visualization software into undergraduate mineralogy courses. Features include background information for teachers on how to teach with data, models, and visualizations; commentary on the benefits of physical versus virtual models; and a set of links to online crystal structure databases. There are also links to visualization software, tutorials, and example exercises and activities

Geoscience Education in the New Cyberinfrastructure

The development and rapid expansion of cyberinfrastructure has produced increasingly data-rich, linked networks which open up new possibilities and challenges for using data in geoscience education. Using undergraduate petrology courses as a case study, this site will help College instructors and students to learn more about the benefits and challenges of using large databases, and to download and contribute tutorials, exercises, and activities using large digital databases. Educational levels: Graduate or professional, Undergraduate lower division, Undergraduate upper division

The Montana-Yellowstone Geologic Field Guide Database

This database integrates field-based research, teaching, and learning and is intended to make geoscience field guide literature more accessible and useful to users. Features include background information for educators about learning in the field, and a database of educationally-useful geologic field guides and road logs in Montana and Yellowstone National Park that is searchable by keyword, topic, geographic location, or geologic province. There is also a set of links to the 'Top 10' geological field trip locations in Montana and Yellowstone, links to field-based exercises, and a collection of aerial photos of the area

Adapting to Changes in Publishing When Searching for Alternatives and Reporting on Animal Research: A Librarian's Perspective.

Since the inaugural issue of ATLA, many changes within publishing have occurred, impacting when, where, and how researchers conduct literature searches for non-animal alternatives. Such changes include increased rate of growth in scientific publications, greater number of databases and online resources available to search, opportunities for open and almost immediate dissemination of research outputs such as preprints and method protocols, and the development of reporting guidelines for animal research. Here we offer a librarian's perspective on these changes and advice on how to manage them to enable robust and diverse alternatives to be implemented in future research

Data Management Practices of Health Sciences Researchers

This study was approved and granted exempt status from the University’s Institutional Review Board (IRB). Librarians at the University of Pittsburgh Health Sciences Library System conducted a 25-question online survey of the data management practices of researchers within the six schools of the health sciences (School of Medicine, School of Health and Rehabilitation Sciences, Graduate School of Public Health, School of Nursing, School of Pharmacy, and School of Dental Medicine). The survey was administered via SurveyMonkey. Questions included researchers’ demographics and data management practices such as the use of file naming conventions, assignment of metadata to data files, storage of working and back-up data, data accessibility, and the use of data management plans (survey instrument provided). All multiple choice questions required a response and the majority were “check all that apply.” Participants were recruited between June 4 and June 21, 2013. A non-targeted message requesting confidential participation in a research study to collect information on research data management practices was distributed to multiple health sciences listservs in the university and posted on the library’s home page and Molecular Biology blog. A reminder was sent once during the 17-day survey period. No incentives were offered. Text provided as the “other” answer in multiple choice and open-ended questions was categorized independently by the three authors, who reached agreement on any discrepancies for final coding

Data Discovery Collaboration (DDC)

The Data Discovery Collaboration (DDC) is a multi-institutional consortium that works together in order to address concerns around data discovery through discussions of metadata, outreach, software development, and systems and metadata interoperability. This OSF project holds documents related to ongoing and completed projects at the DDC that we want to share with the public. If you want to learn more about our members, our structure, or joining, please visit our website, datadiscoverycollaboration.org Contributors listed here are the administrators of the OSF page. Contributors to the documents include all members of the DDC

Data Curation through Catalogs: A Repository-Independent Model for Data Discovery

Institutional data repositories are the acknowledged gold standard for data curation platforms in academic libraries. But not every institution can sustain a repository, and not every dataset can be archived due to legal, ethical, or authorial constraints. Data catalogs—metadata-only indices of research data that provide detailed access instructions and conditions for use—are one potential solution, and may be especially suitable for "challenging" datasets. This article presents the strengths of data catalogs for increasing the discoverability and accessibility of research data. The authors argue that data catalogs are a viable alternative or complement to data repositories, and provide examples from their institutions' experiences to show how their data catalogs address specific curatorial requirements. The article also reports on the development of a community of practice for data catalogs and data discovery initiatives