Slides from the Keynote talk given at Virginia Tech Open Access Week on 20 October 2020. See the full presentation recording and panel discussion at https://vtechworks.lib.vt.edu/handle/10919/100682.
Virginia Tech's Open Access Week 2020 keynote speaker, Elizabeth (Lizzie) Gadd, Research Policy Manager (Publications) at Loughborough University in the UK, gives a talk about how what we reward through recruitment, promotion and tenure processes is not always what we actually value about research activity. The talk explores how we can pursue value-led evaluations - and how we can persuade senior leaders of their benefits.
The keynote talk is followed by a panel discussion with faculty members at Virginia Tech: Thomas Ewing (Associate Dean for Graduate Studies and Research and Professor of History), Carla Finkielstein (Associate Professor of Biological Sciences), Bikrum Gill (Assistant Professor of Political Science), and Sylvester Johnson (Professor and Director of the Center for Humanities. The panel is moderated by Tyler Walters (Dean, University Libraries).
The slides from this presentation are in Loughborough University's repository under a CC BY-NC-SA 4.0 license. https://repository.lboro.ac.uk/articles/presentation/Counting_what_counts_in_recruitment_promotion_and_tenure/13113860
This open access book is tailored to educators and librarians to teach them more about how to use and apply creative commons licenses. The book covers the basics of copyright law and licensing, as well as how to choose, find, and use creative commons licensed materials. There is an entire section of the book specifically dedicated to creative commons for educators and librarians, including chapters on open access to scholarship, open pedagogy, open educational resources, and more.
Abstract
Training materials. The DATUM for Health training programme covers both generic and discipline-specific issues, focusing on the management of qualitative, unstructured data, and is suitable for students at any stage of their PhD. It aims to provide students with the knowledge to manage their research data at every stage in the data lifecycle, from creation to final storage or destruction. They learn how to use their data more effectively and efficiently, how to store and destroy it securely, and how to make it available to a wider audience to increase its use, value and impact.
Understanding the types, processes, and frameworks of workflows and analyses is helpful for researchers seeking to understand more about research, how it was created, and what it may be used for. This lesson uses a subset of data analysis types to introduce reproducibility, iterative analysis, documentation, provenance and different types of processes. Described in more detail are the benefits of documenting and establishing informal (conceptual) and formal (executable) workflows.
Data citation is a key practice that supports the recognition of data creation as a primary research output rather than as a mere byproduct of research. Providing reliable access to research data should be a routine practice, similar to the practice of linking researchers to bibliographic references. After completing this lesson, participants should be able to define data citation and describe its benefits; to identify the roles of various actors in supporting data citation; to recognize common metadata elements and persistent data locators and describe the process for obtaining one, and to summarize best practices for supporting data citation.
Data curation primers are peer-reviewed, living documents to provide practical and concise guides on curating a specific data type or format, or addressing a particular challenge in data curation work. All the primers are developed by Data Curation Network (DCN) which is a seed funding project from the Alfred P Sloan Foundation. The target audiences of primers are data curators and/or data librarians. To date, DCN has published more than 25 primers on database, Excel, netCDF, NVivo, R, SPSS, etc.
When entering data, common goals include creating data sets that are valid, have gone through an established process to ensure quality, are organized, and reusable. This lesson outlines best practices for creating data files. It will detail options for data entry and integration, and provide examples of processes used for data cleaning, organization and manipulation.
Data management planning is the starting point in the data life cycle. Creating a formal document that outlines what you will do with the data during and after the completion of research helps to ensure that the data is safe for current and future use. This lesson describes the benefits of a data management plan (DMP), outlines the components of a DMP, details tools for creating a DMP, provides NSF DMP information, and demonstrates the use of an example DMP.
The ESIP Federation, in cooperation with NOAA and the Data Conservancy, seeks to share the community's knowledge with scientists who increasingly need to be better data managers, as well as to support workforce development for new data management professionals. Over the next several years, the ESIP Federation expects to evolve training courses which seeks to improve the understanding of scientific data management among scientists, emerging scientists, and data professionals of all sorts.
All courses are available under a Creative Commons Attribution 3.0 license that allows you to share and adapt the work as long as you cite the work according to the citation provided. Please send feedback upon the courses to shortcourseeditors@esipfed.org.
The Data Management Skillbuilding Hub is a repository for open educational resources regarding data management, meaning that it is a collection of learning resources freely contributed by anyone willing to share them. Materials such as lessons, best practices, and videos, are stored in the DataONEorg GitHub repository as well as searchable through the Data Management Training Clearinghouse. We invite you submit your own educational resources so that the Data Management Skillbuilding Hub can remain an up-to-date and sustainable educational tool for all to benefit from. You can easily contribute learning materials to the Skillbuilding Hub via GitHub online.
Quality assurance and quality control are phrases used to describe activities that prevent errors from entering or staying in a data set. These activities ensure the quality of the data before it is collected, entered, or analyzed, as well as actively monitoring and maintaining the quality of data throughout the study. In this lesson, we define and provide examples of quality assurance, quality control, data contamination and types of errors that may be found in data sets. After completing this lesson, participants will be able to describe best practices in quality assurance and quality control and relate them to different phases of data collection and entry.
When first sharing research data, researchers often raise questions about the value, benefits, and mechanisms for sharing. Many stakeholders and interested parties, such as funding agencies, communities, other researchers, or members of the public may be interested in research, results and related data. This lesson addresses data sharing in the context of the data life cycle, the value of sharing data, concerns about sharing data, and methods and best practices for sharing data.
Some research funders have a mandate for data resulting from their funded research to be shared. This presentation provides a general definition of data sharing and how scholars can identify and follow data sharing mandates.
Data Tree is a free online course with all you need to know for research data management, along with ways to engage and share data with business, policymakers, media and the wider public. The self-paced training course will take 15 to 20 hours to complete in eight structured modules. The course is packed with video, quizzes and real-life examples of data management, along with valuable tips from experts in data management, data sharing and science communication. The training course materials will be available for structured learning, but also to dip into for immediate problem solving.
Data Tree is funded by the Natural Environment Research Council (NERC) through the National Productivity Investment Fund (NPIF), delivered by the Institute for Environmental Analytics and Stats4SD and supported by the Institute of Physics.
Those workshops help to gain new skills in research data management. Created by MIT Libraries, under CC-BY license, others can adapt and utilize this resources to develop thier own slides in teaching data management.
In this deep dive session, we discuss the current model of scholarly publishing, and highlight the challenges and limitations of this model of research dissemination. We then focus on the value of open access and elaborate on different open access levels (Gold, Bronze, and Green), before discussing how preprints/postprints may be leveraged to promote open access.
Bryan Cook and Stacy Shaw provide an introduction to preprints with a focus on their contributions and limitations in the context of current models of scholarly publishing. We discuss various "levels" of open access publishing (Gold, Bronze, and Green), and how the use of preprints can supplement some of the limitations of these common open access publishing models. Research on the use of preprints are highlighted, and we discuss how preprints/postprints may be leveraged to promote open access.
Differentiating open access and open educational resource can be a challenge in some contexts. Excellent resources such as "How Open Is It?: A Guide for Evaluating the Openness of Journals" (CC BY) https://sparcopen.org/our-work/howopenisit created by SPARC, PLOS, and OASPA greatly aid us in understanding the relative openness of journals. However, visual resources to conceptually differentiate open educational resources (OER) from resources disseminated using an open access approach do not currently exist. Until now.
This one page introductory guide differentiates OER and OA materials on the basis of purpose (teaching vs. research), method of access (analog and digital), and in terms of the relative freedoms offered by different levels of Creative Commons licenses, the most common open license. Many other open licenses, including open software licenses also exist.
Digital culture is changing. Social technologies are impacting how scholars work, learn and engage with one another both inside and outside of their institutions. In postsecondary education, it is becoming increasingly vital to share your work and practice online. Open and digital channels help colleagues solicit advice, seek out support/collaboration, offer free professional development, share information and resources, and learn in networked communities with common interests. Besides developing a digital presence, higher education staff, administrators and scholars are utilizing social media and digital technologies to support their work, add to their professional development, engage with peers, learn in the collective and publicly in digital spaces and places. Using openly licensed content, this OER helps fill the gap between the digital divide and familiarizes users with the digital publishing world. By using this OER, students and professional scholars alike will gain insight into how to use digital publishing tools to their advantage, have a better understanding of the challenges surrounding digital publishing, and learn how to create and engage in innovative and collaborative digital projects.