Читать книгу El manejo de datos. Aproximación desde los estudios de la información - Georgina Araceli Torres Vargas - Страница 9

The primary objective of the IFLA LTR project was to identify the roles and responsibilities of RDM practitioners working in multiple countries. The study also focused on the terminology used to describe the emerging practices and new professional roles. The study was designed using a mixed-method approach and consisted of three phases:

 Comprehensive literature review and data mining to analyze the terminology used to describe the emerging practices and new professional roles

 Quantitative content analysis of job announcements for data curators and RDM librarians

 Semi-structured interviews with professionals working as data librarians, data curators, or research data managers.

The quantitative phase of the study concentrated on the content analysis of job announcements derived from a variety of library and information science job posting sites, including International Association for Social Science Information Services and Technology (IASSIST), and Code4Lib. The goal of the content analysis was to examine the titles, roles, responsibilities, qualifications, and competencies listed in the advertised positions. The data set included 441 job advertisements. Most of the analyzed positions (73.6%) were based in the United States. However, the data set also had some international coverage. The widest distribution came from Europe with 17 European countries in the sample.

The findings from the quantitative analysis of job announcements indicate a wide variation in titles used to identify positions. There was no single title standing out as a standard for the discipline. The most common titles included librarianship in some form, such as Data Services Librarians, Digital Scholarship Librarians, or Research Data Management Librarians. The positions were frequently advertised under a wide variety of titles often with additional data-related responsibilities, such as data science or data reference services. In the analyzed data set, RDM services were located primarily (84.2%) in universities and academic libraries. The range of responsibilities also reflects the influence of librarianship with the top responsibilities in public services including instruction, reference, and outreach. However, a degree in librarianship was required in only 27% of the job advertisements.

In the qualitative phase, semi-structured interviews were conducted with professionals working as data librarians, data experts, datacurators, or research data managers. The goal of interviews was to gain insight into the practice of research data management and to examine the services from the perspective of the professionals working in the field. The interviews were conducted with 26 professionals from Australia, Canada, U.S. and six countries in Western Europe. The study participants were employed at 24 organizations, including:

 Academic libraries (19)

 Campus-wide research data service centers (3)

 University departments (2)

 Data archive (1)

 Research center (1).

All participants held Masters degrees, including 15 had Masters in Library and Information Science (MLIS). Ten participants had PhDs in a variety of disciplines, including biology, environmental science, history, information science, medical informatics, or philosophy. The participants held different position titles although many of their responsibilities and job functions overlapped. Several participants, working mostly in Europe, did not have MLIS but had advanced disciplinary degrees and prior research experience. The variety of titles confirmed the findings from the quantitative phase of the study.

Despite the differences in position titles and terminology, the study found a sense of a shared purpose or even mission among the participants. The professionals across institutional and national settings emphasized that their primary roles and responsibilities involved assisting researchers in meeting funder requirements, improving data management practices, and ultimately contributing to a more efficient research process and better-quality data. Several participants mentioned the end-goal of “making data more usable” (P-L, Interview), and efforts to advocate the FAIR data principles. The participants emphasized that although assisting researchers with meeting funder’s requirements was one of the immediate goals, they also wanted to improve research practices, as stated by Participant V, “that’s really what we want to be leading to, it’s not just about compliance but actually trying to change research culture and get people to think it’s good research practice” (P-V, Interview).

The types of RDM services identified in this study encompassed both consultative and technical services. The concept of the research data lifecycle played a central role in organizing and structuring services. All professionals participating in this study were engaged in consultative services, outreach, and open access advocacy. The consultative, informational services were typically offered at the beginning of the research cycle in the form of one-on-one consultations, workshops and seminars for faculty and graduate students, or online tutorials and guidelines. The consultative services focused on offering guidance and support in:

 Meeting compliance with funders’ requirements

 Developing data management plans (DMP)

 Following data management best practices

 Adhering to data citation standards

 Promoting open access and data sharing

A smaller number of participants assisted researchers with technical aspects of depositing data in repositories and archival storage. Technical services were usually offered at the end of the research data life cycle. Technical infrastructure and the level of support depended on institutional settings. Technical services involved offering support in:

 Data management

 Data formats and file naming conventions

 Data cleaning and verification

 Data conversion

 Data description and documentation

 Metadata creation using standardized schemas

 Data deposit/publishing

 Ingest into repository systems

 Assigning identifiers

 Data anonymization

 Data security

 Archiving and preservation

The participating information professionals often acted as mediators between different stakeholders building networks of expertise and community around good research practices. Their work required some technical skills and knowledge of new technological solutions since they often made recommendations to researchers and led RDM initiatives at their institutions. The new and evolving character of the positions required expertise in multiple areas and the ability to adapt to the changing environment. Specific technical expertise and the level of required skills depended on institutional settings. The study participants emphasized that it’s often impossible for one person to fulfill all the necessary skills and competences found in job descriptions. The lack of technical skills and hands-on experience with databases and scripting was mentioned for professionals with library backgrounds.

RDM services were primarily located in academic libraries as part of research and consultation departments or digital scholarship units. University libraries represented that largest group in the sample but the type of services, the stage of its development, and the level of support for researchers varied greatly between the sites. In the early stage of RDM development, academic libraries usually focused on needs assessment, outreach, training, and open access advocacy and provided consulting services on developing DMPs, metadata, and data curation practices. Academic libraries with more advanced RDM services offered not only assistance with DMPs, metadata, but also with data citation, data sharing and with technical aspects of depositing data in repositories.

The study, however, demonstrated that academic libraries are not the only centers of RDM services on university campuses. It identified new organizational strategies, including embedded services, distributed networks of RDM expertise, and multi-purpose research data services centers. In the embedded model, librarians were working on the faculty-led research projects and research labs throughout the university. They provided support not only at the beginning and end of the research cycle, but also shared expertise and advice on best data management practices throughout the research projects. Distributed networks often had formal structures and were comprised of professionals with expertise in RDM, IT, copyright, research ethics, and scholarly communication. Academic librarians often served as coordinators and referred researchers to the relevant “pockets of expertise” in the campus network. Distributed networks represented efforts in community building around improving data management practices and opening data.

Campus-wide research data service centers represent a new model that reflects an evolution of services and recognition that a more comprehensive suite of skills and expertise is necessary to support data management. Three cases were identified in the sample – one in the United States and two in Europe. Both European data service centers have evolved from RDM services originally located at academic libraries. These new interdisciplinary initiatives involved cross-campus collaboration and cooperation of several units, including the university library, IT department, legal services, and office for research. Research data service centers tended to be multi-purpose and provided university research communities not only with the expertise, tools, and infrastructure necessary to manage research data but also offered support for other forms of scholarly activities. Academic librarians were employed there along IT specialists and legal experts.

The findings of the study indicate that RDM is an evolving sociotechnical practice that involves not only technical systems and services structured around research data life cycle but also a range of social activities. The work of RDM professionals in improving data management practices and advocating open access occurs on multiple levels, starting with individual researchers and their teams, building networks at their institutions, and then expanding to regional, national, and international communities. The theme of shared values and changing research culture was discussed by participants from multiple countries, pointing to the emerging international character of the RDM profession. Community building emerged as an essential requirement for research data management and involved a shared understanding of the benefits of managed data and the impact of open data on scholarship and society.