scholarly journals Qualitative Data Sharing: Data Repositories and Academic Libraries as Key Partners in Addressing Challenges

2017 ◽  
Author(s):  
Sara Mannheimer ◽  
Amy Pienta ◽  
Dessi Kirilova ◽  
Colin Elman ◽  
Amber Wutich
Keyword(s):  
Qualitative Research ◽  
Big Data ◽  
Data Sharing ◽  
Knowledge Production ◽  
Academic Libraries ◽  
Qualitative Data ◽  
Federal Funding ◽  
Research Data ◽  
Data Repositories ◽  
Funding Agencies

Data sharing is increasingly perceived to be beneficial to knowledge production, and is therefore increasingly required by federal funding agencies, private funders, and journals. As qualitative researchers are faced with new expectations to share their data, data repositories and academic libraries are working to address the specific challenges of qualitative research data. This paper describes how data repositories and academic libraries can partner with researchers to support three challenges associated with qualitative data sharing: (1) obtaining informed consent from participants for data sharing and scholarly reuse; (2) ensuring that qualitative data are legally and ethically shared; and (3) sharing data that cannot be deidentified. This paper also describes three continuing challenges of qualitative data sharing that data repositories and academic libraries cannot specifically address—research using qualitative big data, copyright concerns, and risk of decontextualization. While data repositories and academic libraries can’t provide easy solutions to these three continuing challenges, they can partner with researchers and connect them with other relevant specialists to examine these challenges. Ultimately, this paper suggests that data repositories and academic libraries can help researchers address some of the challenges associated with ethical and lawful qualitative data sharing.

scholarly journals Qualitative Data Sharing: Data Repositories and Academic Libraries as Key Partners in Addressing Challenges

2018 ◽  
Vol 63 (5) ◽  
pp. 643-664 ◽  
Author(s):  
Sara Mannheimer ◽  
Amy Pienta ◽  
Dessislava Kirilova ◽  
Colin Elman ◽  
Amber Wutich
Keyword(s):  
Qualitative Research ◽  
Big Data ◽  
Data Sharing ◽  
Knowledge Production ◽  
Academic Libraries ◽  
Qualitative Data ◽  
Federal Funding ◽  
Research Data ◽  
Data Repositories ◽  
Funding Agencies

Data sharing is increasingly perceived to be beneficial to knowledge production, and is therefore increasingly required by federal funding agencies, private funders, and journals. As qualitative researchers are faced with new expectations to share their data, data repositories and academic libraries are working to address the specific challenges of qualitative research data. This article describes how data repositories and academic libraries can partner with researchers to support three challenges associated with qualitative data sharing: (1) obtaining informed consent from participants for data sharing and scholarly reuse, (2) ensuring that qualitative data are legally and ethically shared, and (3) sharing data that cannot be deidentified. This article also describes three continuing challenges of qualitative data sharing that data repositories and academic libraries cannot specifically address—research using qualitative big data, copyright concerns, and risk of decontextualization. While data repositories and academic libraries cannot provide easy solutions to these three continuing challenges, they can partner with researchers and connect them with other relevant specialists to examine these challenges. Ultimately, this article suggests that data repositories and academic libraries can help researchers address some of the challenges associated with ethical and lawful qualitative data sharing.

Introduction: Archiving Qualitative Data in Practice: Ethical Feedback

2021 ◽  
Vol 150 (1) ◽  
pp. 7-27
Author(s):  
Pablo Diaz
Keyword(s):  
Data Sharing ◽  
Qualitative Data ◽  
Social Science Research ◽  
Science Research ◽  
Research Data ◽  
Ethical Challenges ◽  
The Past ◽  
Open Research ◽  
Funding Agencies ◽  
The Cost

Over the past twenty years the normative framework that underpins social science research has undergone major shifts. Among the most salient changes is the growing incentive to archive, share and reuse research data. Today, many governments, funding agencies, research infrastructures and editors are pushing what is commonly known as Open Research Data (ORD). By reflecting on concrete experiences of data sharing, the different contributions to this issue point to the ethical challenges posed by this new trend. Through a fine objectivation of the archiving work, they call to take distance from the bureaucratic framework imposed by the new ethics and ORD policies and to think of data sharing as a situated, contextual and dynamic process. The cost of the exercise as well as the sensitivity of certain data and subjects suggest opting for flexible approaches that leave a certain autonomy and freedom of appraisal to researchers.

scholarly journals A survey of the state of research data services in 35 U.S. academic libraries, or "Wow, what a sweeping question"

2019 ◽  
Vol 5 ◽  
Author(s):  
Matthew Murray ◽  
Megan O'Donnell ◽  
Mark Laufersweiler ◽  
John Novak ◽  
Betty Rozum ◽  
...  
Keyword(s):  
United States ◽  
Academic Libraries ◽  
The United States ◽  
Research Data ◽  
The State ◽  
Executive Summary ◽  
Data Repositories ◽  
Data Services ◽  
Survey Questions ◽  
State Of Research

This report shares the results of a Spring 2018 survey of 35 academic libraries in the United States in regard to the research data services (RDS) they offer. An executive summary presents key findings while the results section provides detailed information on the answers to specific survey questions related to data repositories, metadata, workshops, and polices.

Big Data Sharing Among Academics

2013 ◽  
pp. 177-194 ◽  
Author(s):  
Jeonghyun Kim
Keyword(s):  
Big Data ◽  
Social Science ◽  
Case Studies ◽  
Data Sharing ◽  
Physical Science ◽  
Life Science ◽  
Social Research ◽  
Data Repositories ◽  
Current Technology ◽  
Oceanographic Data

The goal of this chapter is to explore the practice of big data sharing among academics and issues related to this sharing. The first part of the chapter reviews literature on big data sharing practices using current technology. The second part presents case studies on disciplinary data repositories in terms of their requirements and policies. It describes and compares such requirements and policies at disciplinary repositories in three areas: Dryad for life science, Interuniversity Consortium for Political and Social Research (ICPSR) for social science, and the National Oceanographic Data Center (NODC) for physical science.

scholarly journals Openness in Big Data and Data Repositories

2019 ◽  
Vol 11 (3) ◽  
pp. 255-273 ◽  
Author(s):  
Vicki Xafis ◽  
Markus K. Labude
Keyword(s):  
Big Data ◽  
Ethical Issues ◽  
Open Science ◽  
Research Data ◽  
Data Repositories ◽  
Ethics Framework ◽  
Full Explanation ◽  
Health Related Research ◽  
Health Related ◽  
Privacy And Confidentiality

Abstract There is a growing expectation, or even requirement, for researchers to deposit a variety of research data in data repositories as a condition of funding or publication. This expectation recognizes the enormous benefits of data collected and created for research purposes being made available for secondary uses, as open science gains increasing support. This is particularly so in the context of big data, especially where health data is involved. There are, however, also challenges relating to the collection, storage, and re-use of research data. This paper gives a brief overview of the landscape of data sharing via data repositories and discusses some of the key ethical issues raised by the sharing of health-related research data, including expectations of privacy and confidentiality, the transparency of repository governance structures, access restrictions, as well as data ownership and the fair attribution of credit. To consider these issues and the values that are pertinent, the paper applies the deliberative balancing approach articulated in the Ethics Framework for Big Data in Health and Research (Xafis et al. 2019) to the domain of Openness in Big Data and Data Repositories. Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end.

Big data adoption in academic libraries: a literature review

2020 ◽  
Vol 37 (4) ◽  
pp. 1-5
Author(s):  
Nove E. Variant Anna ◽  
Endang Fitriyah Mannan
Keyword(s):  
Big Data ◽  
Data Management ◽  
Academic Libraries ◽  
Data Analytics ◽  
Academic Library ◽  
Big Data Analytics ◽  
Research Data ◽  
Management Policy ◽  
Content Type ◽  
Scopus Database

Purpose The purpose of this paper is to analyse the publication of big data in the library from Scopus database by looking at the writing time period of the papers, author's country, the most frequently occurring keywords, the article theme, the journal publisher and the group of keywords in the big data article. The methodology used in this study is a quantitative approach by extracting data from Scopus database publications with the keywords “big data” and “library” in May 2019. The collected data was analysed using Voxviewer software to show the keywords or terms. The results of the study stated that articles on big data have appeared since 2012 and are increasing in number every year. The big data authors are mostly from China and America. Keywords that often appear are based on the results of terminology visualization are including, “big data”, “libraries”, “library”, “data handling”, “data mining”, “university libraries”, “digital libraries”, “academic libraries”, “big data applications” and “data management”. It can be concluded that the number of publications related to big data in the library is still small; there are still many gaps that need to be researched on the topic. The results of the research can be used by libraries in using big data for the development of library innovation. Design/methodology/approach The Scopus database was accessed on 24 May 2019 by using the keyword “big data” and “library” in the search box. The authors only include papers, which title contain of big data in library. There were 74 papers, however, 1 article was dropped because of it not meeting the criteria (affiliation and abstract were not available). The papers consist of journal articles, conference papers, book chapters, editorial and review. Then the data were extracted into excel and analysed as follows (by the year, by the author/s’s country, by the theme and by the publisher). Following that the collected data were analysed using VOX viewer software to see the relationship between big data terminology and library, terminology clustering, keywords that often appear, countries that publish big data, number of big data authors, year of publication and name of journals that publish big data and library articles (Alagu and Thanuskodi, 2019). Findings It can be concluded that the implementation of big data in libraries is still in an early stage, it is shown from the limited number of practical implementation of big data analytics in library. Not many libraries that use big data to support innovation and services since there were lack of librarian skills of big data analytics. The library manager’s view of big data is still not necessary to do. It is suggested for academic libraries to start their adoption of big data analytics to support library services especially research data. To do so, librarians can enhance their skills and knowledge by following some training in big data analytics or research data management. The information technology infrastructure also needs to be upgraded since big data need big IT capacity. Finally, the big data management policy should be made to ensure the implementation goes well. Originality/value This paper discovers the adoption and implementation of big data in library, many papers talk big data in business and technology context. This is offering new idea for many libraries especially academic library about the adoption of big data to support their services. They can adopt the big data analytics technology and technique that suitable for their library.

scholarly journals The Metaphors of Candidte Philosophy Group Teacher Regarding the Concept of ‘Mind’

2019 ◽  
Vol 8 (1) ◽  
pp. 148
Author(s):  
Ekrem Ziya Duman
Keyword(s):  
Qualitative Research ◽  
Data Collection ◽  
Qualitative Data ◽  
Basic Element ◽  
Research Data ◽  
Data Collection Tool ◽  
Research Designs ◽  
Second Category ◽  
Academic Year ◽  
Qualitative Data Collection

The purpose of the current study was to determine what the metaphors of the candidate philosophy group teachers regarding the concept of mind and understand the related metaphors by means of gathering the metaphors expressed under certain categories. Phenomenology, one of the qualitative research designs, was used in the current study. The working group was made up of the students having pedagogical formation at Gazi University in the academic year of 2017-2018 and the last year students studying Philosophy Group Teaching at Gazi University. In this sense, the study was applied to total 85 people. Qualitative data collection techniques were used in the research. Data collection tool was applied to the participants by the researchers. In this sense, 62 valid metaphors were produced out of 85 candidate teachers. The metaphors produced were gathered under 10 categories as mind as a guide, mind as a basic element, mind as suitability for the purpose, mind as a working and developing structure, mind as a storage, mind as showing the reality, mind as an illuminator, mind as a valuable competence, mind as a limitless competence and the unclassified.In the order of metaphors produced mostly by the candidate philosophy group teachers participating the research, mind as a guide was in the first place at the rate of 17.3%. Mind as a basic element was in the second category with a rate of 16% and it was followed by mind as suitability for the purpose and mind as a working and developing structure with a rate of 12%.

scholarly journals Children’s analysis processes when analysing qualitative research data: a missing piece to the qualitative research puzzle

2017 ◽  
Vol 18 (3) ◽  
pp. 290-306 ◽  
Author(s):  
Jenna K Gillett-Swan
Keyword(s):  
Qualitative Research ◽  
Qualitative Data ◽  
Research Process ◽  
Research Data ◽  
Social Actors ◽  
Analysis Process ◽  
Data Collection And Analysis ◽  
Researching With Children ◽  
Insight Into

Children’s role in the research process is often limited to a passive role as subject, recipient or object of data rather than as active contributor. The sociology of childhood considers children to be competent social actors and advocates for them to be recognised as such. This recognition is yet to filter into mainstream research agendas with children often remaining a passive provider to research that seeks to elicit their perspectives. This article presents an examination of the processes that children use when analysing their own qualitative research data as observed within a qualitative research project. It provides insight into the ability to increase the richness of data obtained when researching with children, by including their perspectives and contributions in the data analysis process. Children’s capacity as capable and competent contributors to research beyond the more passive role of participant is described and the ways that children can have a greater participatory role in qualitative data collection and analysis processes are discussed.

scholarly journals Perceptions and Attitudes toward Data Sharing among Dental Researchers

2018 ◽  
Vol 4 (1) ◽  
pp. 68-75 ◽  
Author(s):  
H. Spallek ◽  
S.M. Weinberg ◽  
M. Manz ◽  
S. Nanayakkara ◽  
X. Zhou ◽  
...  
Keyword(s):  
Data Management ◽  
Data Sharing ◽  
International Association ◽  
Improve Patient Care ◽  
Research Data ◽  
Research Subjects ◽  
Data Repositories ◽  
Use Of Data ◽  
Share Data ◽  
Past Experiences

Introduction: Increasing attention is being given to the roles of data management and data sharing in the advancement of research. This study was undertaken to explore opinions and past experiences of established dental researchers as related to data sharing and data management. Methods: Researchers were recruited from the International Association for Dental Research scientific groups to complete a survey consisting of Likert-type, multiple-choice, and open-ended questions. Results: All 42 respondents indicated that data sharing should be promoted and facilitated, but many indicated reservations or concerns about the proper use of data and the protection of research subjects. Many had used data from data repositories and received requests for data originating from their studies. Opinions varied regarding restrictions such as requirements to share data and the time limits of investigator rights to keep data. Respondents also varied in their methods of data management and storage, with younger respondents and those with higher direct costs of their research tending to use dedicated experts to manage their data. Discussion: The expressed respondent support for research data sharing, with the noted concerns, complements the idea of developing managed data clearinghouses capable of promoting, managing, and overseeing the data-sharing process. Knowledge Transfer Statement: Researchers can use the results of this study to evaluate and improve management and sharing of research data. By encouraging and facilitating the data-sharing process, research can advance more efficiently, and research findings can be implemented into practice more rapidly to improve patient care and the overall oral health of populations.

scholarly journals Publishing descriptions of non-public clinical datasets: guidance for researchers, repositories, editors and funding organisations

2015 ◽  
Author(s):  
Iain Hrynaszkiewicz ◽  
Varsha Khodiyar ◽  
Andrew L Hufton ◽  
Susanna-Assunta Sansone
Keyword(s):  
Clinical Research ◽  
Data Sharing ◽  
Peer Review Process ◽  
Open Data ◽  
Data Access ◽  
Research Data ◽  
Future Research ◽  
Patient Privacy ◽  
Journal Articles ◽  
Data Repositories

AbstractSharing of experimental clinical research data usually happens between individuals or research groups rather than via public repositories, in part due to the need to protect research participant privacy. This approach to data sharing makes it difficult to connect journal articles with their underlying datasets and is often insufficient for ensuring access to data in the long term. Voluntary data sharing services such as the Yale Open Data Access (YODA) and Clinical Study Data Request (CSDR) projects have increased accessibility to clinical datasets for secondary uses while protecting patient privacy and the legitimacy of secondary analyses but these resources are generally disconnected from journal articles – where researchers typically search for reliable information to inform future research. New scholarly journal and article types dedicated to increasing accessibility of research data have emerged in recent years and, in general, journals are developing stronger links with data repositories. There is a need for increased collaboration between journals, data repositories, researchers, funders, and voluntary data sharing services to increase the visibility and reliability of clinical research. We propose changes to the format and peer-review process for journal articles to more robustly link them to data that are only available on request. We also propose additional features for data repositories to better accommodate non-public clinical datasets, including Data Use Agreements (DUAs).

Sign in / Sign up

Export Citation Format

Share Document