This activity uses data collected from DART (Deep-ocean Assessment and Reporting of Tsunamis) stations in the Pacific following the 2011 tsunami generated off the coast of Japan. Students are required to map the wave front after 5, 10, and 15 hours to better understand the speed and propagation of the tsunami wave.

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Companion Site for Harvard Medical School Canvas Network MOOC Best Practices for Biomedical Research Data Management. This Open Science Framework project site includes all the materials contained in the Canvas course including: readings and resources; slide presentations; video lectures; activity outlines; research case studies and questions; and quiz questions with answer guide.

Biomedical research today is not only rigorous, innovative and insightful, it also has to be organized and reproducible. With more capacity to create and store data, there is the challenge of making data discoverable, understandable, and reusable. Many funding agencies and journal publishers are requiring publication of relevant data to promote open science and reproducibility of research.

In order to meet to these requirements and evolving trends, researchers and information professionals will need the data management and curation knowledge and skills to support the access, reuse and preservation of data.

This course is designed to address present and future data management needs.

This activity modifies a typical density laboratory exercise to fit within a lecture session. Students are asked to compare the densities of six different rocks/minerals collected from six different environments. Based on the brief description of each rock the students are asked to first predict which rock has the highest density and which rock has the lowest density. The students are then asked to construct a hypothesis and test their hypothesis by calculating the density of the rocks. Students are then asked to apply information from lecture to place each rock in the appropriate layer of the Earth.

(Note: this resource was added to OER Commons as part of a batch upload of over 2,200 records. If you notice an issue with the quality of the metadata, please let us know by using the 'report' button and we will flag it for consideration.)

Simmons University and academic health sciences libraries across the USA are partnering to offer a post-master’s certificate program in the area of Inter-Professional Informationist (IPI), for the purpose of bridging the gap between traditional and emergent skills in health sciences librarianship and increasing the diversity in the workforce. A small cohort of librarians in the program will complete seven IPI courses, and partner institutions will connect them with researchers and clinical leaders who will mentor their capstone. This project was made possible in part by the Institute of Museum and Library Services with the Laura Bush 21st Century Librarian Program Grant [RE-17-19-0032-19]. Simmons University, School of Library and Information Science, College of Organizational, Computational and Information Science provides cost-share of the project.

One of the courses included in the IPI program is “Scientific Research Data Management” was taught Fall 2020 by Elaine Martin and Julie Goldman. This course had been an elective in the Simmons School of Library and Information Science curriculum for many years, but underwent a redesign to include and address many of the newer emerging areas related to data services in libraries. For example, the course included “Special Topics” that included Data Curation, Data Skills, Reproducibility, and Informationists. While basic understanding of data management is critical for librarians to work with researchers, there are these emerging areas where librarians can provide even more specialized help to their communities. It is one of the IPI’s project’s goals to bridge the gap between traditional and emergent skills in health sciences librarianship.

This Open Science Framework project site includes curriculum materials for Simmons IPI LIS-532U-OL Scientific Research Data Management (course offered Fall 2020). This course serves as an introduction to the field of scientific data management, and aims to help prepare information professionals and information students for engaging with scientists.