Lisa Zilinski

Do You Have an Institutional Data Policy? A Review of the Current Landscape of Library Data Services and Institutional Data Policies

INTRODUCTION Many research institutions have developed research data services in their libraries, often in anticipation of or in response to funder policy. However, policies at the institution level are either not well known or nonexistent. METHODS This study reviewed library data services efforts and institutional data policies of 206 American universities, drawn from the July 2014 Carnegie list of universities with “Very High” or “High” research activity designation. Twenty-four different characteristics relating to university type, library data services, policy type, and policy contents were examined. RESULTS The study has uncovered findings surrounding library data services, institutional data policies, and content within the policies. DISCUSSION Overall, there is a general trend toward the development and implementation of data services within the university libraries. Interestingly, just under half of the universities examined had a policy of some sort that either specified or mentioned research data. Many of these were standalone data policies, while others were intellectual property policies that included research data. When data policies were discoverable, not behind a log in, they focused on the definition of research data, data ownership, data retention, and terms surrounding the separation of a researcher from the institution. CONCLUSION By becoming well versed on research data policies, librarians can provide support for researchers by navigating the policies at their institutions, facilitating the activities needed to comply with the requirements of research funders and publishers. This puts academic libraries in a unique position to provide insight and guidance in the development and revisions of institutional data policies. External Data or Supplements: Briney, Kristin; Goben, Abigail; Zilinski, Lisa, 2015, “Data from: Do You Have an Institutional Data Policy? A Review of the Current Landscape of Library Data Services and Institutional Data Policies”, http://dx.doi.org/10.7910/DVN/GAZPAJ , Harvard Dataverse

Evolution of Data Creation, Management, Publication, and Curation in the Research Process

Sharing research data and scholarship is of national importance because of the increased focus on maximizing return on the U.S. governments investment in research programs. Recent government policy changes have directly affected the management and accessibility of publically funded research. On January 18, 2011, the National Science Foundation, a U.S. agency that supports research and education in nonmedical fields, required that data management plans be submitted with all grant proposals. On February 22, 2013, the U.S. Presidents Office of Science and Technology Policy extended a similar requirement for all federal agencies with research and development budgets of more than

Developing Professional Skills in STEM Students: Data Information Literacy.

100 million. These requirements illustrate the need for further coordination and management of data as scholarship with traditional publications. Purdue University Libraries and its Joint Transportation Research Program (JTRP) collaborated to develop a comprehensive work flow that links technical report production with the management and publication of associated data. This paper illustrates early initiatives to integrate discrete data publications with traditional scholarly publications by leveraging new and existing repository platforms and services. The authors review government policies, past data-sharing practices, early pilot initiatives, and work flow integration between Purdues data repository, the traditional press, and institutional repository. Through the adoption of these work flows, the authors propose best practices for integrating data publishing and dissemination into the research process. The implementation of this model has the potential to assist researchers in meeting the requirements of federal funding agencies, while reducing redundancy, ensuring integrity, expanding accessibility, and increasing the return on research investment.

Data informed learning: a next phase data literacy framework for higher education

Undergraduate STEM students are increasingly expected to have some data use skills upon graduation, whether they pursue post-graduate education or move into industry. This project was an initial foray into the application of data information literacy competencies to training undergraduate students to identify markers of data and information quality. The data consumer training appeared within two courses to help students evaluate data objects, including databases and datasets available on the Internet. The application of the Data Credibility Checklist provides a foundation for developing data reuse competencies. Based upon the initial presentation of the content, it became obvious that students need very basic introductions to data concepts, including definitions for database and dataset, and the process of data object discovery.

Automating data sharing through authoring tools

Accessing, using and managing data is increasingly recognized as an important learning outcome in higher education. Approaches to data literacy have typically been informed by information literacy. New approaches to information literacy have emerged that address how information is used in the different disciplinary contexts in which people learn and work. Successful approaches to data literacy will also need to address contextual concerns. Informed learning is an approach to information literacy that purposefully addresses contextual concerns by suggesting pedagogic strategies for enabling students to use information in ways that support discipline‐focused learning outcomes. As part of an ongoing investigation, we advance data informed learning as a framework for data literacy in higher education that emphasizes how data are used to learn and communicate within disciplinary learning contexts. Drawing from informed learning, we outline principles and characteristics of data informed learning, and suggest future directions to investigate ways that data are used in real‐world environments.

Data narratives: Increasing scholarly value

In the current scientific publishing landscape, there is a need for an authoring workflow that easily integrates data and code into manuscripts and that enables the data and code to be published in reusable form. Automated embedding of data and code into published output will enable superior communication and data archiving. In this work, we demonstrate a proof of concept for a workflow, org-mode, which successfully provides this authoring capability and workflow integration. We illustrate this concept in a series of examples for potential uses of this workflow. First, we use data on citation counts to compute the h-index of an author, and show two code examples for calculating the h-index. The source for each example is automatically embedded in the PDF during the export of the document. We demonstrate how data can be embedded in image files, which themselves are embedded in the document. Finally, metadata about the embedded files can be automatically included in the exported PDF, and accessed by computer programs. In our customized export, we embedded metadata about the attached files in the PDF in an Info field. A computer program could parse this output to get a list of embedded files and carry out analyses on them. Authoring tools such as Emacs + org-mode can greatly facilitate the integration of data and code into technical writing. These tools can also automate the embedding of data into document formats intended for consumption.

Linguistics / Etymology - University of South Florida

Data narratives or data stories have emerged as a new form of the scholarly communication focused on data. In this paper, we explore the potential value of data narratives and the requirements for data stories to enhance scholarly communication. We examine three types of data stories that form a continuum from the less to the more structured: the DataONE data stories, the Data Curation Profiles, and the Data Descriptors from the journal Scientific Data. We take the position that these data stories will increase the value of scholarly communication if they are linked to the datasets and to the publications that describe results, and have instructional value.

Opportunities and Challenges of Data Publication: A Case Study from Purdue

Notes The profile was completed prior to the start of the researchers’ experiment. The experiment is not scheduled to begin until the Fall semester of 2012. Since the researchers are still in the planning stages of the research, the scope of the profile may be modified significantly as the research progresses. Any modifications of this document will be subject to version control, and annotations require a minimum of creator name, data, and identification of related source documents.

Carbon Disclosure Project Report 2008 S&P 500

Beginning in 2011, there have been several policy changes directly affecting the management, preservation, and accessibility of publically funded research and resulting research data in the United States. On January 18, 2011 the National Science Foundation (NSF) required data management plans to be submitted with all grant proposals (National Science Foundation, 2013). On February 22, 2013, the Office of Science and Technology Policy of the President of the United States extended a similar requirement to all federal agencies that have a research and development budget of more than

Assessing Perceived Usability of the Data Curation Profile Toolkit Using the Technology Acceptance Model

100 million (Holdren, 2013). These requirements illustrate the need for further coordination and management of data as scholarship and traditional scholarship in integrated publishing solutions. The case study presented in this paper will illustrate an early initiative at Purdue University to integrate discrete data publications with traditional scholarly publications through leveraging new and existing repository platforms and services (Zilinski, Scherer, Bullock, Horton, & Matthews). Examination of the case study will involve a discussion of workflow integration between Purdue’s data repository, the Purdue University Research Repository (PURR); its traditional press, the Purdue University Press (PUP); and the institutional repository, Purdue e-Pubs. Publications and Data: Changes in Public Policy Changes in Public Policy There have been several recent policy changes directly affecting the management, preservation, and accessibility of publically funded research and resulting research data in the United States. In March 2002, the National Institutes of Health (NIH) shared a draft statement on sharing research data and invited comments on the statement. In February 2003, the NIH finalized their statement on research data, stating all investigator initiated applications with direct costs greater than