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The purpose of this article is to provide an overview of development and recent focus on digital curation and ties it to larger cyberinfrastructure initiatives.

Provides a useful viewpoint on the development and recent focus on digital curation.

Digital curation is the active involvement of information professionals in the management, including the preservation, of digital data for future use. While there have been people doing different aspects of data curation and digital preservation for decades, recent events have brought a number of ideas, organizations, and individuals together to focus more intently on digital curation. Reports in the US by the National Science Foundation and the American Council of Learned Societies and in the UK by Dr Liz Lyon of UKOLN have pointed out the aspects of digital curation which need to be in place to ensure that digital objects can be maintained, preserved, and remain available for future use. These reports along with increased research focus at conferences and the emergence of new educational programs have led to the emergence of digital curation and made digital curators a new entry into the information professions. Increasingly, digital curation is becoming an umbrella concept that includes digital preservation, data curation, electronic records management, and digital asset management.

This article discusses and defines digital curation and notes how this theme has permeated in recent reports, conferences, and educational offerings.

The article synthesizes current digital curation efforts and helps to define this new concept for information professionals.

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.

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.

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.

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.

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.

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

This article aims to summarize the employers' requirements of scientific data specialists and the status quo of LIS education organizations' training system for scientific data specialists. It also focuses on the matching analysis between the course content and the responsibilities as well as requirements of scientific data specialists. Moreover, in order to provide some indications for LIS education of scientific data specialists in China, it presents the training objectives and modes.

Some job portals for librarians and the comprehensive job portals are investigated as information sources and the keywords such as “scientific data management”, “data service”, “data curation”, “e-Science”, “e-Research”, “data specialist” are selected to retrieval library-released job advertisements for scientific data specialists to understand the library's requirements towards scientific data specialists' core capabilities. Meanwhile the course catalogues of all iSchools' web sites are searched directly in order to find if scientific data courses are provided.

Libraries value teamwork ability, communication ability, interpersonal ability and a good use of data curation tools as the core competences for scientific data specialists. Candidates who possess a second advanced degree, who understand libraries, who hold demonstrated knowledge of metadata standards, and who emphasize details, under the same condition, are more likely to be considered first. Libraries do not have a unified title for scientific data specialists yet. The current curriculums of iSchools mainly cover research method, data science, data management and data service, data statistic and analysis, data warehouse, information studies and technologies, and so on.

This unique study explores some required qualifications of science data specialist surveyed by job openings, including the core skills, position requirements, responsibilities of the job, and some qualifications. It also investigates the related curriculum setting of iSchool universities through course descriptions. This study is very useful for curriculum development in Chinese LIS education of scientific data specialists including required core courses and selected electives, and to promote the practice of data service in Chinese academic libraries.

The purpose of this paper is to understand the landscape of data curation services among public and academic libraries in the USA, with a focus on library capacity for providing data curation services.

The authors conducted an online survey by employing stratified sampling from the American Library Directory. A total of 198 responses were analyzed.

The authors’ findings provide insight into the current landscape of libraries’ data curation services. The survey participants evaluated six capacity dimensions for both public and academic libraries – value, financial, administrative, technical infrastructure, human resources and network. The ratings the participants gave to these capacity dimensions were significantly different between academic and public libraries.

This study suggests several areas in which libraries will benefit from further developing their capacity to successfully run data curation services.

This is among the first research study to address the concept of capacity in the context of libraries’ data curation services.

This study aims to present the results of a survey of library and information science (LIS) schools' websites used to determine if the number of data curation courses offered is adequate to address the needs of the so‐called “data deluge”. Many authors have identified a gap in the education of LIS students for data curation.

This study surveyed the websites of LIS schools in North America to identify data curation courses. It reviewed and analyzed course descriptions, objectives and syllabi (when available) as well as compared course objectives, requirements, topics, assignments, and projects of the identified courses.

Of the 52 LIS schools in North America's websites examined in this study, 16 institutions offered courses on data curation. The increase in the number of schools offering courses in data curation showed that LIS schools are responding to the demand for data curation professionals. More LIS schools need to add data curation to their curriculum. LIS schools currently offering data curation courses should continue to work together to determine the optimal course objectives and learning outcomes.

Although there are several papers focused on particular data curation programs at a few universities, there are no papers that provide an overall view of the status of data curation education in higher education institutions today. This research will be of value and interest to LIS educators and professionals to determine if there is adequate education in place and to identify and evaluate the current state of data curation education.

The purpose of this paper is to understand genomics scientists’ perceptions in data quality assurances based on their domain knowledge.

The study used a survey method to collect responses from 149 genomics scientists grouped by domain knowledge. They ranked the top-five quality criteria based on hypothetical curation scenarios. The results were compared using χ2 test.

Scientists with domain knowledge of biology, bioinformatics, and computational science did not reach a consensus in ranking data quality criteria. Findings showed that biologists cared more about curated data that can be concise and traceable. They were also concerned about skills dealing with information overloading. Computational scientists on the other hand value making curation understandable. They paid more attention to the specific skills for data wrangling.

This study takes a new approach in comparing the data quality perceptions for scientists across different domains of knowledge. Few studies have been able to synthesize models to interpret data quality perception across domains. The findings may help develop data quality assurance policies, training seminars, and maximize the efficiency of genome data management.

The purpose of this paper is to define and describe digital curation, an emerging field of theory and practice in the information professions that embraces digital preservation, data curation, and management of information assets over their lifecycle. It dissects key issues and debates in the area while arguing that digital curation is a vital strategy for dealing with the so-called data deluge.

This paper explores digital curation’s potential to provide an improved return on investment in data work.

A vital counterweight to the problem of data loss, digital curation also adds value to trusted data assets for current and future use. This paper unpacks data, the research enterprise, the roles and responsibilities of digital curation professionals, the data lifecycle, metadata, sharing and reuse, scholarly communication (cyberscholarship, publication and citation, and rights), infrastructure (archives, centers, libraries, and institutional repositories), and overarching issues (standards, governance and policy, planning and data management plans, risk management, evaluation, and metrics, sustainability, and outreach).

A critical discussion that focusses on North America and the UK, this paper synthesizes previous findings and conclusions in the area of digital curation. It has value for digital curation professionals and researchers as well as students in library and information science who may deal with data in the future. This paper helps potential stakeholders understand the intellectual and practical framework and the importance of digital curation in adding value to scholarly (science, social science, and humanities) and other types of data. This paper suggests the need for further empirical research, not only in exploring the actual sharing and reuse practices of various sectors, disciplines, and domains, but also in considering the the data lifecycle, the potential role of archivists, funding and sustainability, outreach and awareness-raising, and metrics.

The purpose of this study was to identify the digital curation practices in institutional repositories (IRs) in South India.

A voluntary survey was conducted among the IR managers of 23 South Indian IRs, and the response rate was 87%.

This study found that the active participation of South Indian IRs was only seen in a few digital curation activities. However, of the 33 digital curation activities analyzed, the active participation of repositories was only seen in ten digital curation activities. The performance of preservation activities was extremely low, and disagreements were recorded by the survey participants toward several digital curation activities. The most disagreed digital curation activities were emulation and cease data curation. All the participants had assigned metadata and allowed file downloads in their repositories. Raman Research Institute had provided a good number of digital curation services in their IR.

This is an in-depth study investigating the digital curation practice currently underway in South Indian IRs, and the researcher could not find similar studies in this niche.

Budgeting data curation tasks in research projects is difficult. In this paper, we investigate the time spent on data curation, more specifically on cleaning and documenting quantitative data for data sharing. We develop recommendations on cost factors in research data management.

We make use of a pilot study conducted at the GESIS Data Archive for the Social Sciences in Germany between December 2016 and September 2017. During this period, data curators at GESIS - Leibniz Institute for the Social Sciences documented their working hours while cleaning and documenting data from ten quantitative survey studies. We analyse recorded times and discuss with the data curators involved in this work to identify and examine important cost factors in data curation, that is aspects that increase hours spent and factors that lead to a reduction of their work.

We identify two major drivers of time spent on data curation: The size of the data and personal information contained in the data. Learning effects can occur when data are similar, that is when they contain same variables. Important interdependencies exist between individual tasks in data curation and in connection with certain data characteristics.

The different tasks of data curation, time spent on them and interdependencies between individual steps in curation have so far not been analysed.

As libraries become more involved in curating research data, reference librarians will need to be trained in conducting data interviews with researchers to better understand their data and associated needs. This article seeks to identify and provide definitions for the basic terms and concepts of data curation for librarians to properly frame and carry out a data interview using the Data Curation Profiles (DCP) Toolkit.

The DCP Toolkit is a semi‐structured interview designed to assist librarians in identifying the data curation needs of researchers. The components of the DCP Toolkit were analyzed to determine the base level of knowledge needed for librarians to conduct effective data interviews. Specific concepts, definitions, and examples were sought through a review of articles, case studies, practitioner resources and from the experiences of the Purdue University Libraries.

Data curation concepts and terminology are not yet well‐defined and often vary across, or even within fields of study. This research informed the development of a workshop to train librarians in using the DCP Toolkit. The definitions and concepts addressed in the workshop include: data, data set, data lifecycle, data curation, data sharing, and roles for reference librarians.

Conducting a data interview can be a daunting task given the complexity of data curation and the lack of shared definitions. Practical tools and training are needed to help librarians develop capacity in data curation.

This article provides practical information for public service librarians to help them conceptualize and conduct a data interview with researchers.