Dataset Information

Research data management in academic institutions: A scoping review.

ABSTRACT: The purpose of this study is to describe the volume, topics, and methodological nature of the existing research literature on research data management in academic institutions.We conducted a scoping review by searching forty literature databases encompassing a broad range of disciplines from inception to April 2016. We included all study types and data extracted on study design, discipline, data collection tools, and phase of the research data lifecycle.We included 301 articles plus 10 companion reports after screening 13,002 titles and abstracts and 654 full-text articles. Most articles (85%) were published from 2010 onwards and conducted within the sciences (86%). More than three-quarters of the articles (78%) reported methods that included interviews, cross-sectional, or case studies. Most articles (68%) included the Giving Access to Data phase of the UK Data Archive Research Data Lifecycle that examines activities such as sharing data. When studies were grouped into five dominant groupings (Stakeholder, Data, Library, Tool/Device, and Publication), data quality emerged as an integral element.Most studies relied on self-reports (interviews, surveys) or accounts from an observer (case studies) and we found few studies that collected empirical evidence on activities amongst data producers, particularly those examining the impact of research data management interventions. As well, fewer studies examined research data management at the early phases of research projects. The quality of all research outputs needs attention, from the application of best practices in research data management studies, to data producers depositing data in repositories for long-term use.

SUBMITTER: Perrier L

PROVIDER: S-EPMC5441653 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Research data management in academic institutions: A scoping review.

Perrier Laure L Blondal Erik E Ayala A Patricia AP Dearborn Dylanne D Kenny Tim T Lightfoot David D Reka Roger R Thuna Mindy M Trimble Leanne L MacDonald Heather H

PloS one 20170523 5

<h4>Objective</h4>The purpose of this study is to describe the volume, topics, and methodological nature of the existing research literature on research data management in academic institutions.<h4>Materials and methods</h4>We conducted a scoping review by searching forty literature databases encompassing a broad range of disciplines from inception to April 2016. We included all study types and data extracted on study design, discipline, data collection tools, and phase of the research data life ...[more]

PMID: 28542450

Similar Datasets

Project description:INTRODUCTION:The rising popularity of social media, since their inception around 20 years ago, has been echoed in the growth of health-related research using data derived from them. This has created a demand for literature reviews to synthesise this emerging evidence base and inform future activities. Existing reviews tend to be narrow in scope, with limited consideration of the different types of data, analytical methods and ethical issues involved. There has also been a tendency for research to be siloed within different academic communities (eg, computer science, public health), hindering knowledge translation. To address these limitations, we will undertake a comprehensive scoping review, to systematically capture the broad corpus of published, health-related research based on social media data. Here, we present the review protocol and the pilot analyses used to inform it. METHODS:A version of Arksey and O'Malley's five-stage scoping review framework will be followed: (1) identifying the research question; (2) identifying the relevant literature; (3) selecting the studies; (4) charting the data and (5) collating, summarising and reporting the results. To inform the search strategy, we developed an inclusive list of keyword combinations related to social media, health and relevant methodologies. The frequency and variability of terms were charted over time and cross referenced with significant events, such as the advent of Twitter. Five leading health, informatics, business and cross-disciplinary databases will be searched: PubMed, Scopus, Association of Computer Machinery, Institute of Electrical and Electronics Engineers and Applied Social Sciences Index and Abstracts, alongside the Google search engine. There will be no restriction by date. ETHICS AND DISSEMINATION:The review focuses on published research in the public domain therefore no ethics approval is required. The completed review will be submitted for publication to a peer-reviewed, interdisciplinary open access journal, and conferences on public health and digital research.

Project description:BackgroundData provenance refers to the origin, processing, and movement of data. Reliable and precise knowledge about data provenance has great potential to improve reproducibility as well as quality in biomedical research and, therefore, to foster good scientific practice. However, despite the increasing interest on data provenance technologies in the literature and their implementation in other disciplines, these technologies have not yet been widely adopted in biomedical research.ObjectiveThe aim of this scoping review was to provide a structured overview of the body of knowledge on provenance methods in biomedical research by systematizing articles covering data provenance technologies developed for or used in this application area; describing and comparing the functionalities as well as the design of the provenance technologies used; and identifying gaps in the literature, which could provide opportunities for future research on technologies that could receive more widespread adoption.MethodsFollowing a methodological framework for scoping studies and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, articles were identified by searching the PubMed, IEEE Xplore, and Web of Science databases and subsequently screened for eligibility. We included original articles covering software-based provenance management for scientific research published between 2010 and 2021. A set of data items was defined along the following five axes: publication metadata, application scope, provenance aspects covered, data representation, and functionalities. The data items were extracted from the articles, stored in a charting spreadsheet, and summarized in tables and figures.ResultsWe identified 44 original articles published between 2010 and 2021. We found that the solutions described were heterogeneous along all axes. We also identified relationships among motivations for the use of provenance information, feature sets (capture, storage, retrieval, visualization, and analysis), and implementation details such as the data models and technologies used. The important gap that we identified is that only a few publications address the analysis of provenance data or use established provenance standards, such as PROV.ConclusionsThe heterogeneity of provenance methods, models, and implementations found in the literature points to the lack of a unified understanding of provenance concepts for biomedical data. Providing a common framework, a biomedical reference, and benchmarking data sets could foster the development of more comprehensive provenance solutions.

Project description:ObjectivesTo chart the global literature on gender equity in academic health research.DesignScoping review.ParticipantsQuantitative studies were eligible if they examined gender equity within academic institutions including health researchers.Primary and secondary outcome measuresOutcomes related to equity across gender and other social identities in academia: (1) faculty workforce: representation of all genders in university/faculty departments, academic rank or position and salary; (2) service: teaching obligations and administrative/non-teaching activities; (3) recruitment and hiring data: number of applicants by gender, interviews and new hires for various rank; (4) promotion: opportunities for promotion and time to progress through academic ranks; (5) academic leadership: type of leadership positions, opportunities for leadership promotion or training, opportunities to supervise/mentor and support for leadership bids; (6) scholarly output or productivity: number/type of publications and presentations, position of authorship, number/value of grants or awards and intellectual property ownership; (7) contextual factors of universities; (8) infrastructure; (9) knowledge and technology translation activities; (10) availability of maternity/paternity/parental/family leave; (11) collaboration activities/opportunities for collaboration; (12) qualitative considerations: perceptions around promotion, finances and support.ResultsLiterature search yielded 94 798 citations; 4753 full-text articles were screened, and 562 studies were included. Most studies originated from North America (462/562, 82.2%). Few studies (27/562, 4.8%) reported race and fewer reported sex/gender (which were used interchangeably in most studies) other than male/female (11/562, 2.0%). Only one study provided data on religion. No other PROGRESS-PLUS variables were reported. A total of 2996 outcomes were reported, with most studies examining academic output (371/562, 66.0%).ConclusionsReviewed literature suggest a lack in analytic approaches that consider genders beyond the binary categories of man and woman, additional social identities (race, religion, social capital and disability) and an intersectionality lens examining the interconnection of multiple social identities in understanding discrimination and disadvantage. All of these are necessary to tailor strategies that promote gender equity.Trial registration numberOpen Science Framework: https://osf.io/8wk7e/.

Project description:BackgroundThe ownership of patient information in the context of big data is a relatively new problem, which is not yet fully recognized by the medical academic community. The problem is interdisciplinary, incorporating legal, ethical, medical, and aspects of information and communication technologies, requiring a sophisticated analysis. However, no previous scoping review has mapped existing studies on the subject.ObjectiveThis study aims to map and assess published studies on patient data ownership in the context of big data as viewed by the academic community.MethodsA scoping review was conducted based on the 5-stage framework outlined by Arksey and O'Malley and further developed by Levac, Colquhoun, and O'Brien. The organization and reporting of results of the scoping review were conducted according to PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses and its extensions for Scoping Reviews). A systematic and comprehensive search of 4 scientific information databases, PubMed, ScienceDirect, Scopus, and Springer, was performed for studies published between January 2000 and October 2019. Two authors independently assessed the eligibility of the studies and the extracted data.ResultsThe review included 32 eligible articles authored by academicians that correspond to 3 focus areas: problem (ownership), area (health care), and context (big data). Five major aspects were studied: the scientific area of publications, aspects and academicians' perception of ownership in the context of big data, proposed solutions, and practical applications for data ownership issues in the context of big data. The aspects in which publications consider ownership of medical data are not clearly distinguished but can be summarized as ethical, legal, political, and managerial. The ownership of patient data is perceived primarily as a challenge fundamental to conducting medical research, including data sales and sharing, and to a lesser degree as a means of control, problem, threat, and opportunity also in view of medical research. Although numerous solutions falling into 3 categories, technology, law, and policy, were proposed, only 3 real applications were discussed.ConclusionsThe issue of ownership of patient information in the context of big data is poorly researched; it is not addressed consistently and in its integrity, and there is no consensus on policy decisions and the necessary legal regulations. Future research should investigate the issue of ownership as a core research question and not as a minor fragment among other topics. More research is needed to increase the body of knowledge regarding the development of adequate policies and relevant legal frameworks in compliance with ethical standards. The combined efforts of multidisciplinary academic teams are needed to overcome existing gaps in the perception of ownership, the aspects of ownership, and the possible solutions to patient data ownership issues in the reality of big data.

Dataset Information

Research data management in academic institutions: A scoping review.

Publications

Research data management in academic institutions: A scoping review.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets