A Data Sharing Story

International Journal of Digital Curation, 2018

In response to widespread concerns about the integrity of research published in scholarly journals, several initiatives have emerged that are promoting research transparency through access to data underlying published scientific findings. Journal editors, in particular, have made a commitment to research transparency by issuing data policies that require authors to submit their data, code, and documentation to data repositories to allow for public access to the data. In the case of the American Journal of Political Science (AJPS) Data Replication Policy, the data also must undergo an independent verification process in which materials are reviewed for quality as a condition of final manuscript publication and acceptance. Aware of the specialized expertise of the data archives, AJPS called upon the Odum Institute Data Archive to provide a data review service that performs data curation and verification of replication datasets. This article presents a case study of the collaboration b...

researchremix.org

Science progresses by building upon previous research. Progress can be most rapid, efficient, and focused when raw datasets from previous studies are available for reuse. To facilitate this practice, funders and journals have begun to request and require that investigators share their primary datasets with other researchers. Unfortunately, it is difficult to evaluate the effectiveness of these policies. This study aims to develop foundations for evaluating data sharing and reuse decisions in the biomedical literature by developing tools to answer the following research questions, within the context of biomedical gene expression datasets: What is the prevalence of biomedical research data sharing? Biomedical research data reuse? What features are most associated with an investigator's decision to share or reuse a biomedical research dataset? Does sharing or reusing data contribute to the impact of a research article, independently of other factors? What do the results suggest for developing efficient, effective policies, tools, and initiatives for promoting data sharing and reuse? I suggest a novel approach to identifying publications that share and reuse datasets, through the application of natural language processing techniques to the full text of primary research articles. Using these classifications and extracted covariates, univariate and multivariate analysis will assess which features are most important to data sharing and reuse prevalence, and also estimate the contribution that sharing data and reusing data make to a publication's research impact. I hope the results will inform the development of effective policies and tools to facilitate this important aspect of scientific research and information exchange.

2018

In one of the largest surveys of researchers about research data (with over 7,700 respondents), Springer Nature finds widespread data sharing associated with published works and a desire from researchers that their data are discoverable.<br><br>This whitepaper examines the results of this survey and discusses the challenges that researchers face in sharing their data. The whitepaper looks at data sharing attitudes globally, as well as in relation to region, subject and seniority.<br><br>Infographic: https://doi.org/10.6084/m9.figshare.5996786

This study examines characteristics of data sharing and data re-use in Genetics and Heredity, where data citation is most common. This study applies an exploratory method because data citation is a relatively new area. The Data Citation Index (DCI) on the Web of Science was selected because DCI provides a single access point to over 500 data repositories worldwide and to over two million data studies and datasets across multiple disciplines and monitors quality research data through a peer review process. We explore data citations for Genetics and Heredity, as a case study by examining formal citations recorded in the DCI and informally by sampling a selection of papers for implicit data citations within publications. Citer-based analysis is conducted in order to remedy self-citation in the data citation phenomena. We explore 148 sampled citing articles in order to identify factors that influence data sharing and data re-use, including references, main text, supplementary data/information, acknowledgments, funding information, author information, and web/author resources. This study is unique in that it relies on a citer-based analysis approach and by analyzing peer-reviewed and published data, data repositories, and citing articles of highly productive authors where data sharing is most prevalent. This research is intended to provide a methodological and practical contribution to the study of data citation.

2017

It is increasingly common for researchers to make their data freely available. This is often a requirement of funding agencies but also consistent with the principles of open science, according to which all research data should be shared and made available for reuse. Once data is reused, the researchers who have provided access to it should be acknowledged for their contributions, much as authors are recognised for their publications through citation. Hyoungjoo Park and Dietmar Wolfram have studied characteristics of data sharing, reuse, and citation and found that current data citation practices do not yet benefit data sharers, with little or no consistency in their format. More formalised citation practices might encourage more authors to make their data available for reuse.

Science, Technology, & Human Values

This paper presents reports on discussions among an international group of science and technology studies (STS) scholars who convened at the US National Science Foundation (January 2015) to think about data sharing and open STS. The first report, which reflects discussions among members of the Society for Social Studies of Science (4S), relates the potential benefits of data sharing and open science for STS. The second report, which reflects discussions among scholars from many professional STS societies (i.e., European Association for the Study of Science and Technology [ EASST], 4S, Society for the History of Technology [ SHOT], History of Science Society [ HSS], and Philosophy of Science Association [ PSA]), focuses on practical and conceptual issues related to managing, storing, and curating STS data. As is the case for all reports of such open discussions, a scholar’s presence at the meeting does not necessarily mean that they agree with all aspects of the text to follow.

Scientific Data

Data sharing is one of the cornerstones of modern science that enables large-scale analyses and reproducibility. We evaluated data availability in research articles across nine disciplines in Nature and Science magazines and recorded corresponding authors’ concerns, requests and reasons for declining data sharing. Although data sharing has improved in the last decade and particularly in recent years, data availability and willingness to share data still differ greatly among disciplines. We observed that statements of data availability upon (reasonable) request are inefficient and should not be allowed by journals. To improve data sharing at the time of manuscript acceptance, researchers should be better motivated to release their data with real benefits such as recognition, or bonus points in grant and job applications. We recommend that data management costs should be covered by funding agencies; publicly available research data ought to be included in the evaluation of application...

Science and Engineering Ethics, 2010

Advances in science are the combined result of the efforts of a great many scientists, and in many cases, their willingness to share the products of their research. These products include data sets, both small and large, and unique research resources not commercially available, such as cell lines and software programs. The sharing of these resources enhances both the scope and the depth of research, while making more efficient use of time and money. However, sharing is not without costs, many of which are borne by the individual who develops the research resource. Sharing, for example, reduces the uniqueness of the resources available to a scientist, potentially influencing the originator's perceived productivity and ultimately his or her competitiveness for jobs, promotions, and grants. Nevertheless, for most researchers-particularly those using public funds-sharing is no longer optional but must be considered an obligation to science, the funding agency, and ultimately society at large. Most funding agencies, journals, and professional societies now require a researcher who has published work involving a unique resource to make that resource available to other investigators. Changes could be implemented to mitigate some of the costs. The creator of the resource This paper is based on a presentation made at the conference ''New Capabilities, Emerging Issues, and Responsible Conduct in Data Management'' jointly sponsored by the U.S. Office of Research Integrity and the University of Maryland Baltimore and held in Baltimore, Maryland on September 28-29, 2006. This paper and associated references reflects the state of the field at that time.

Nature, 2022

J ournals and funding bodies increasingly require manuscript authors to share data on request or make the information publicly available. It's a big ask from a technical standpoint, but some straightforward strategies can simplify the process. Scientific papers rarely include all the data used to justify the conclusions, even in the supplementary material. Authors might fear getting scooped, or that other researchers will use the raw data to make fresh discoveries, or they might wish to protect the privacy of study participants. Or, more probably, authors have neither the time nor the expertise to package the data for others to view and understand. Such reticence costs the research community. Data transparency allows others to repeat analyses and catch mistakes or fraudulent Despite agreeing to make raw data available, some authors fail to comply. The right strategies and platforms can ease the task.