Data Science Areas of Activity

Librarians and information professionals can support research, conduct data science, and promote health in a variety of ways.

We have identified the following three broad areas of activity in support of data-driven research and health, where the skills and expertise of the library community could be most helpful.

A. Accelerating Discovery through Data Science

This area is most closely connected to NLM Strategic Plan Goal 1.2 (“Advance Research and Development in Biomedical Informatics and Data Science”), and specifically describes efforts to directly pursue new discovery in the fields of health and biomedicine through data-driven research and development.

Historically, librarians and information professionals have primarily played a useful support role in the research enterprise (see Area C, below). However, librarians’ facility for organizing and interpreting information and data, proficiency with working with a wide variety of types of data (e.g. bibliographic data, usage data, etc.), and tradition of “building bridges” between concepts, fields, researchers, and organizations (both within their own institutions and beyond) may make them uniquely suited to participate more directly in the data-driven research process, especially for interdisciplinary research that involves forging connections between research efforts in different fields.

Additionally, many librarians are increasingly leveraging new data-driven techniques to accelerate discovery in their own research. From using text mining and machine learning to facilitate the process of creating systematic reviews to conducting bibliometric analyses to gain new understanding of the current state of research in particular scientific fields, applying data science methods to the study of science and research can generate new insights and help shape future research.

B. Advancing Health and Healthcare Through the Application of Data-Centric Clinical Informatics

This area includes the operation, maintenance, and support of information systems in clinical settings, and connects to NLM Strategic Plan Goal 1 (“accelerate discovery and advance health by providing the tools for data-driven research”) more broadly.

Hospital and clinical librarians are positioned to contribute to these efforts, especially in cases where clinical data is being used as an input to data-driven research, which is directly connected to NLM Strategic Plan Goal 1.1 (“Connect the resources of a digital research enterprise”).

C. Supporting the Research Enterprise with Effective Research Data Management

This area covers activities related to efficiently, effectively and securely organizing, storing, preserving and sharing data collected and used in biomedical research. This includes the organization and facilitation of access to information, and is deeply connected to the ideals of Open Science, which is why it is historically the most connected to the traditional librarianship skill set.

This area also can serve as a bridge to or between the other two areas listed above: data-driven research (area A) requires the development and execution of comprehensive and mature data management plans; and effective research data management is key in the responsible use of clinical information as a substrate for research, both in ensuring the privacy and security of data, and in working with those who manage clinical information systems (area B) to extract potential research data.

Where UEP and NNLM Can Build Capacity

The following list enumerates skills and competencies which may be useful or necessary in pursuing the above areas of activity. Many of these skills are already present in the librarian/information professional community, and are ready to be developed further. Other competencies are similar or related to skills traditionally found in the library community, and offer an opportunity for librarians to grow into new or expanded roles.

This list is roughly organized into categories following the research process, from gathering open source data, to conceptualizing and conducting data-driven research, to managing and sharing research data. Many of the skills listed overlap categories, and may be relevant in many phases of the research process.

NLM offerings that relate to the listed competencies are noted in brackets.

The Area(s) of Activity (outlined on the previous tab) to which each skill is relevant is noted with a check mark.

Notes

This list is not exhaustive, and omits many skills or competencies that librarians and information professionals may require to do their jobs effectively. The list above focuses on the skills presented in the first three broad areas identified in the OSI workshop report (Data Skills, Computational Skills, and Research and Subject Matter Knowledge), which primarily include skills that are uniquely relevant to supporting data-driven research and health, with a particular emphasis on technical areas that require a foundation of computational literacy. These are areas where UEP sees the most immediate opportunities for building capacity in the library community.

Additionally, the list is not intended to be viewed as a mandatory set of prerequisites. Rather, the list should be viewed as aspirational, as a menu of possible areas of professional development and capacity-building. A well-rounded health sciences librarian might have particular expertise in one or more of these competencies, plus a basic understanding and familiarity with several others; not every librarian should expect to need expert-level abilities in every one of these skills.