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1 – 10 of over 1000
Article
Publication date: 7 February 2023

Nushrat Khan, Mike Thelwall and Kayvan Kousha

This study investigates differences and commonalities in data production, sharing and reuse across the widest range of disciplines yet and identifies types of improvements needed…

Abstract

Purpose

This study investigates differences and commonalities in data production, sharing and reuse across the widest range of disciplines yet and identifies types of improvements needed to promote data sharing and reuse.

Design/methodology/approach

The first authors of randomly selected publications from 2018 to 2019 in 20 Scopus disciplines were surveyed for their beliefs and experiences about data sharing and reuse.

Findings

From the 3,257 survey responses, data sharing and reuse are still increasing but not ubiquitous in any subject area and are more common among experienced researchers. Researchers with previous data reuse experience were more likely to share data than others. Types of data produced and systematic online data sharing varied substantially between subject areas. Although the use of institutional and journal-supported repositories for sharing data is increasing, personal websites are still frequently used. Combining multiple existing datasets to answer new research questions was the most common use. Proper documentation, openness and information on the usability of data continue to be important when searching for existing datasets. However, researchers in most disciplines struggled to find datasets to reuse. Researchers' feedback suggested 23 recommendations to promote data sharing and reuse, including improved data access and usability, formal data citations, new search features and cultural and policy-related disciplinary changes to increase awareness and acceptance.

Originality/value

This study is the first to explore data sharing and reuse practices across the full range of academic discipline types. It expands and updates previous data sharing surveys and suggests new areas of improvement in terms of policy, guidance and training programs.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2021-0423.

Details

Online Information Review, vol. 47 no. 6
Type: Research Article
ISSN: 1468-4527

Keywords

Article
Publication date: 15 March 2024

Beatrice Arthur and Thomas van der Walt

The purpose of this study is to investigate the current research data management practices among researchers in Ghana and their impact on data reuse and collaborative research…

Abstract

Purpose

The purpose of this study is to investigate the current research data management practices among researchers in Ghana and their impact on data reuse and collaborative research. The study aims to identify the methods used by researchers to store and preserve their research data, as well as to determine the extent to which researchers share their data with others.

Design/methodology/approach

The study uses a mixed-method research strategy to blend qualitative and quantitative data and is conducted at two public and two private universities in Ghana.

Findings

The study revealed that researchers in Ghana currently store and preserve their research data using personal devices, such as laptops, CDs and external flash drives, rather than keeping the data in university data repositories. They also do not share their research data with others, which negatively affects collaborative research. The current practice of storing data on personal devices and not sharing data with others hinders collaborative research. The study recommends that universities in Ghana revise their research policy documents to address RDM-related issues such as data storage, data preservation, data sharing and data reuse.

Research limitations/implications

The study was conducted at two public and two private universities in Ghana, but the findings were placed in a wider context through appropriate references.

Practical implications

This study emphasises the need for sound research data management procedures to support research collaboration and data reuse in Ghana. Universities should provide incentives to academics to disclose their data to encourage data sharing and collaboration.

Social implications

The government and management of universities should consciously invest in the needed technologies and equipment to implement research data management in their universities.

Originality/value

This study looks at how researchers in Ghana manage their research data and how it affects data reuse and collaborative research.

Details

Library Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-5124

Keywords

Article
Publication date: 10 March 2023

Marta Ortiz-de-Urbina-Criado, Alberto Abella and Diego García-Luna

This paper aims to highlight the importance of open data and the role that knowledge management and open innovation can play in its identification and use. Open data has great…

Abstract

Purpose

This paper aims to highlight the importance of open data and the role that knowledge management and open innovation can play in its identification and use. Open data has great potential to create social and economic value, but its main problem is that it is often not easily reusable. The aim of this paper is to propose a unique identifier for open data-sets that would facilitate search and access to them and help to reduce heterogeneity in the publication of data in open data portals.

Design/methodology/approach

Considering a model of the impact process of open data reuse and based on the digital object identifier system, this paper develops a proposal of a unique identifier for open data-sets called Open Data-set Identifier (OpenDatId).

Findings

This paper presents some examples of the application and advantages of OpenDatId. For example, users can easily consult the available content catalogues, search the data in an automated way and examine the content for reuse. It is also possible to find out where this data comes from, solving the problems caused by the increasingly frequent federation of data in open data portals and enabling the creation of additional services based on open data.

Originality/value

From an integrated perspective of knowledge management and open innovation, this paper presents a new unique identifier for open data-sets (OpenDatId) and a new concept for data-set, the FAIR Open Data-sets.

Details

Journal of Knowledge Management, vol. 27 no. 10
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 9 November 2023

Gustavo Candela, Nele Gabriëls, Sally Chambers, Milena Dobreva, Sarah Ames, Meghan Ferriter, Neil Fitzgerald, Victor Harbo, Katrine Hofmann, Olga Holownia, Alba Irollo, Mahendra Mahey, Eileen Manchester, Thuy-An Pham, Abigail Potter and Ellen Van Keer

The purpose of this study is to offer a checklist that can be used for both creating and evaluating digital collections, which are also sometimes referred to as data sets as part…

Abstract

Purpose

The purpose of this study is to offer a checklist that can be used for both creating and evaluating digital collections, which are also sometimes referred to as data sets as part of the collections as data movement, suitable for computational use.

Design/methodology/approach

The checklist was built by synthesising and analysing the results of relevant research literature, articles and studies and the issues and needs obtained in an observational study. The checklist was tested and applied both as a tool for assessing a selection of digital collections made available by galleries, libraries, archives and museums (GLAM) institutions as proof of concept and as a supporting tool for creating collections as data.

Findings

Over the past few years, there has been a growing interest in making available digital collections published by GLAM organisations for computational use. Based on previous work, the authors defined a methodology to build a checklist for the publication of Collections as data. The authors’ evaluation showed several examples of applications that can be useful to encourage other institutions to publish their digital collections for computational use.

Originality/value

While some work on making available digital collections suitable for computational use exists, giving particular attention to data quality, planning and experimentation, to the best of the authors’ knowledge, none of the work to date provides an easy-to-follow and robust checklist to publish collection data sets in GLAM institutions. This checklist intends to encourage small- and medium-sized institutions to adopt the collection as data principles in daily workflows following best practices and guidelines.

Details

Global Knowledge, Memory and Communication, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9342

Keywords

Article
Publication date: 20 November 2023

Laksmi Laksmi, Muhammad Fadly Suhendra, Shamila Mohamed Shuhidan and Umanto Umanto

This study aims to identify the readiness of institutional repositories in Indonesia to implement digital humanities (DH) data curation. Data curation is a method of managing…

Abstract

Purpose

This study aims to identify the readiness of institutional repositories in Indonesia to implement digital humanities (DH) data curation. Data curation is a method of managing research data that maintains the data’s accuracy and makes it available for reuse. It requires controlled data management.

Design/methodology/approach

The study uses a qualitative approach. Data collection was carried out through a focus group discussion in September–October 2022, interviews and document analysis. The informants came from four institutions in Indonesia.

Findings

The findings reveal that the national research repository has implemented data curation, albeit not optimally. Within the case study, one of the university repositories diligently curates its humanities data and has established networks extending to various ASEAN countries. Both the national archive repository and the other university repository have implemented rudimentary data curation practices but have not prioritized them. In conclusion, the readiness of the national research repository and the university repository stand at the high-capacity stage, while the national archive repository and the other university repository are at the established and early stages of data curation, respectively.

Research limitations/implications

This study examined only four repositories due to time constraints. Nonetheless, the four institutions were able to provide a comprehensive picture of their readiness for DH data curation management.

Practical implications

This study provides insight into strategies for developing DH data curation activities in institutional repositories. It also highlights the need for professional development for curators so they can devise and implement stronger ownership policies and data privacy to support a data-driven research agenda.

Originality/value

This study describes the preparations that must be considered by institutional repositories in the development of DH data curation activities.

Article
Publication date: 25 January 2024

Besiki Stvilia and Dong Joon Lee

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data…

Abstract

Purpose

This study addresses the need for a theory-guided, rich, descriptive account of research data repositories' (RDRs) understanding of data quality and the structures of their data quality assurance (DQA) activities. Its findings can help develop operational DQA models and best practice guides and identify opportunities for innovation in the DQA activities.

Design/methodology/approach

The study analyzed 122 data repositories' applications for the Core Trustworthy Data Repositories, interview transcripts of 32 curators and repository managers and data curation-related webpages of their repository websites. The combined dataset represented 146 unique RDRs. The study was guided by a theoretical framework comprising activity theory and an information quality evaluation framework.

Findings

The study provided a theory-based examination of the DQA practices of RDRs summarized as a conceptual model. The authors identified three DQA activities: evaluation, intervention and communication and their structures, including activity motivations, roles played and mediating tools and rules and standards. When defining data quality, study participants went beyond the traditional definition of data quality and referenced seven facets of ethical and effective information systems in addition to data quality. Furthermore, the participants and RDRs referenced 13 dimensions in their DQA models. The study revealed that DQA activities were prioritized by data value, level of quality, available expertise, cost and funding incentives.

Practical implications

The study's findings can inform the design and construction of digital research data curation infrastructure components on university campuses that aim to provide access not just to big data but trustworthy data. Communities of practice focused on repositories and archives could consider adding FAIR operationalizations, extensions and metrics focused on data quality. The availability of such metrics and associated measurements can help reusers determine whether they can trust and reuse a particular dataset. The findings of this study can help to develop such data quality assessment metrics and intervention strategies in a sound and systematic way.

Originality/value

To the best of the authors' knowledge, this paper is the first data quality theory guided examination of DQA practices in RDRs.

Details

Journal of Documentation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0022-0418

Keywords

Article
Publication date: 28 March 2023

Werner Scheltjens

Upcycling is conceptualised as a digital historical research practice aimed at increasing the scientific value of historical data collections produced in print or in electronic…

Abstract

Purpose

Upcycling is conceptualised as a digital historical research practice aimed at increasing the scientific value of historical data collections produced in print or in electronic form between the eighteenth and the late twentieth centuries. The concept of upcycling facilitates data rescue and reuse as well as the study of information creation processes deployed by previous generations of researchers.

Design/methodology/approach

Based on a selection of two historical reference works and two legacy collections, an upcycling workflow consisting of three parts (input, processing and documentation and output) is developed. The workflow facilitates the study of historical information creation processes based on paradata analysis and targets the cognitive processes that precede and accompany the creation of historical data collections.

Findings

The proposed upcycling workflow furthers the understanding of computational methods and their role in historical research. Through its focus on the information creation processes that precede and accompany historical research, the upcycling workflow contributes to historical data criticism and digital hermeneutics.

Originality/value

Many historical data collections produced between the eighteenth and the late twentieth century do not comply with the principles of FAIR data. The paper argues that ignoring the work of previous generations of researchers is not an option, because it would make current research practices more vulnerable and would result in losing access to the experiences and knowledge accumulated by previous generations of scientists. The proposed upcycling workflow takes historical data collections seriously and makes them available for future generations of researchers.

Article
Publication date: 24 October 2023

Asmita Verma and Anjula Gurtoo

The paper aims to review rules and policy guidelines worldwide around non-personal data (NPD) and evaluate the policies on criteria that allow for the use of data for economic and…

Abstract

Purpose

The paper aims to review rules and policy guidelines worldwide around non-personal data (NPD) and evaluate the policies on criteria that allow for the use of data for economic and social good. A review related to diverse policy approaches of various countries remains a research gap, and hence the analysis in the paper is designed with the intention of developing a research framework and providing policy gaps for further exploration.

Design/methodology/approach

A systematic review of academic and non-academic literature on theoretical foundations, applications of NPD for economic and social good and NPD policies and regulations was conducted to identify the evaluation criteria. A total of 32 dimensions got identified for evaluation. As second step, content analysis was used for evaluation. A total of 13 documents from 6 countries and 1 geographical region were identified for evaluation. The documents were evaluated based on the 32 dimensions spread across 5 domains that facilitate data access and sharing for economic and societal benefit.

Findings

The analysis highlights three distinct emerging perspectives on data exchange: most policy and regulatory documents acknowledge the importance of identifying different types of NPD and accordingly describing the distinct roles and responsibilities of data actors for leveraging the data; the policy and regulatory frameworks clearly focus on increasing business opportunities, data sharing cooperation and innovation; and findings also demonstrate certain gaps in the policy frameworks such as a more comprehensive discussion on data access and sharing mechanisms, particularly data sandboxes and open data, and concrete norms and rigorous standards regarding accountability, transparency, ownership and confidentiality. Furthermore, policies and regulations may include appropriate incentive structures for data providers and users to ensure unhindered and sustainable access to data for the common good.

Originality/value

To the best of the authors’ knowledge, this paper represents one of the first research contributions evaluating global data policies focused on NPD in the context of its increasing use as a public good. The paper first identifies evaluation criteria for the analysis on public and social good, and, thus, provides a conceptual framework for future research. Additionally, the analysis identifies the broad domains of policy analysis on social and public good for data economics.

Details

Digital Policy, Regulation and Governance, vol. 26 no. 1
Type: Research Article
ISSN: 2398-5038

Keywords

Open Access
Article
Publication date: 31 October 2023

Neema Florence Mosha and Patrick Ngulube

The study aims to investigate the utilisation of open research data repositories (RDRs) for storing and sharing research data in higher learning institutions (HLIs) in Tanzania.

Abstract

Purpose

The study aims to investigate the utilisation of open research data repositories (RDRs) for storing and sharing research data in higher learning institutions (HLIs) in Tanzania.

Design/methodology/approach

A survey research design was employed to collect data from postgraduate students at the Nelson Mandela African Institution of Science and Technology (NM-AIST) in Arusha, Tanzania. The data were collected and analysed quantitatively and qualitatively. A census sampling technique was employed to select the sample size for this study. The quantitative data were analysed using the Statistical Package for the Social Sciences (SPSS), whilst the qualitative data were analysed thematically.

Findings

Less than half of the respondents were aware of and were using open RDRs, including Zenodo, DataVerse, Dryad, OMERO, GitHub and Mendeley data repositories. More than half of the respondents were not willing to share research data and cited a lack of ownership after storing their research data in most of the open RDRs and data security. HILs need to conduct training on using trusted repositories and motivate postgraduate students to utilise open repositories (ORs). The challenges for underutilisation of open RDRs were a lack of policies governing the storage and sharing of research data and grant constraints.

Originality/value

Research data storage and sharing are of great interest to researchers in HILs to inform them to implement open RDRs to support these researchers. Open RDRs increase visibility within HILs and reduce research data loss, and research works will be cited and used publicly. This paper identifies the potential for additional studies focussed on this area.

Article
Publication date: 19 April 2023

Aasif Mohammad Khan, Fayaz Ahmad Loan, Umer Yousuf Parray and Sozia Rashid

Data sharing is increasingly being recognized as an essential component of scholarly research and publishing. Sharing data improves results and propels research and discovery…

Abstract

Purpose

Data sharing is increasingly being recognized as an essential component of scholarly research and publishing. Sharing data improves results and propels research and discovery forward. Given the importance of data sharing, the purpose of the study is to unveil the present scenario of research data repositories (RDR) and sheds light on strategies and tactics followed by different countries for efficient organization and optimal use of scientific literature.

Design/methodology/approach

The data for the study is collected from registry of RDR (re3data registry) (re3data.org), which covers RDR from different academic disciplines and provides filtration options “Search” and “Browse” to access the repositories. Using these filtration options, the researchers collected metadata of repositories i.e. country wise contribution, content-type data, repository language interface, software usage, metadata standards and data access type. Furthermore, the data was exported to Google Sheets for analysis and visualization.

Findings

The re3data registry holds a rich and diverse collection of data repositories from the majority of countries all over the world. It is revealed that English is the dominant language, and the most widely used software for the creation of data repositories are “DataVerse”, followed by “Dspace” and “MySQL”. The most frequently used metadata standards are “Dublin Core” and “Datacite metadata schema”. The majority of repositories are open, with more than half of the repositories being “disciplinary” in nature, and the most significant data sources include “scientific and statistical data” followed by “standard office documents”.

Research limitations/implications

The main limitation of the study is that the findings are based on the data collected through a single registry of repositories, and only a few characteristic features were investigated.

Originality/value

The study will benefit all countries with a small number of data repositories or no repositories at all, with tools and techniques used by the top repositories to ensure long-term storage and accessibility to research data. In addition to this, the study provides a global overview of RDR and its characteristic features.

Details

Information Discovery and Delivery, vol. 52 no. 1
Type: Research Article
ISSN: 2398-6247

Keywords

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