Skip all navigation and go to page content
NN/LM Home About SCR | Contact SCR | Feedback |Site Map | Help | Bookmark and Share

Archive for the ‘Data’ Category

Big Data to Knowledge BD2K

Tuesday, July 23rd, 2013

The National Institutes of Health (NIH) Commonfund recently launched the Big Data to Knowledge (BD2K) imitative. The mission of the BD2K initiative is to enable biomedical scientists to capitalize more fully on the Big Data being generated by those research communities.

Big Data Tablet

With advances in technologies, these investigators are increasingly generating and using large, complex, and diverse datasets. Consequently, the biomedical research enterprise is increasingly becoming data-intensive and data-driven. However, the ability of researchers to locate, analyze, and use Big Data (and more generally all biomedical and behavioral data) is often limited for reasons related to access to relevant software and tools, expertise, and other factors. BD2K aims to develop the new approaches, standards, methods, tools, software, and competencies that will enhance the use of biomedical Big Data by supporting research, implementation, and training in data science and other relevant fields that will lead to:

  • Appropriate access to shareable biomedical data through technologies, approaches, and policies that enable and facilitate widespread data sharing, discoverability, management, curation, and meaningful re-use;
  • Development of and access to appropriate algorithms, methods, software, and tools for all aspects of the use of Big Data, including data processing, storage, analysis, integration, and visualization;
  • Appropriate protections for privacy and intellectual property;
  • Development of a sufficient cadre of researchers skilled in the science of Big Data, in addition to elevating general competencies in data usage and analysis across the biomedical research workforce.

Overall, the focus of the BD2K initiative is the development of innovative and transforming approaches as well as tools for making Big Data and data science a more prominent component of biomedical research.

As biomedical tools and technologies rapidly improve, researchers are producing and analyzing an ever-expanding amount of complex biological data. New analytics tools are needed to extract critical knowledge from this vast amount of data, and new policies must be developed to encourage data and software sharing to maximize the value of the data for all researchers across the spectrum of biomedical research. In addition, data and metadata standards to ensure data quality and uniformity must be developed, with broad input from the scientific community to ensure that these standards will have maximum utility and value.

Funding and educational opportunities are provided through the BD2K initiative.

Each day more and more data is generated. Through efforts such as the BD2K initiative it is hoped that the data can be widely used across disciplines  and lead to scientific discovery or breakthroughs, particularity in the fields of health and medicine. Health science librarians also play an important role in the organization and curation of data. With expert skills in organization of information librarians are well suited to participate with researchers in data organization processes.

Funny and Informative Data Sharing and Management Video

Tuesday, July 16th, 2013

Librarians at New York University’s Health Sciences Libraries (NYUHSL) developed a series of short videos to highlight the importance of data sharing under Federally funded awards and grants. The Librarians at NYUHSL developed the videos with funding from “information specialist” supplements to existing National Institutes of Health (NIH) research grants. The National Library of Medicine (NLM) initiated these supplements as a pilot last year. They were offered by several NIH Institutes and Centers.

The NYUHSL librarians developed three short videos using Xtranormal animation and later combined them into one. The videos, while funny, highlight the importance of data sharing and the unfortunately funny situations that can arise when data is not managed correctly.

As data sets become an increasingly important aspect of continued research across departments and divisions researchers may need assistance understanding data management policies and data sharing. Increasingly librarians have demonstrated that they can play an important role in helping researchers with the data management process and data management policy creation.

NIH Data Sharing Repositories

Wednesday, June 19th, 2013

Screenshot of NIH Data Sharing Repository

The National Institutes of Health (NIH) recently made available a list of data sharing repositories. The NIH Data Sharing Repositories is a searchable list of NIH-supported data repositories that accept submissions of appropriate data from NIH-funded investigators (and others). Also included are resources that aggregate information about biomedical data and information sharing systems.

Also available, NIH Data Sharing Policies, provide a list of data sharing policies in effect at the NIH, including policies at the NIH, IC, division, and program levels that apply to broad sets of investigators and data. Individual requests for applications (RFAs) and program announcements (PA) may specify other data sharing policies for specific projects.

The data repositories and sharing policies provided by the NIH are the work of the NIH Trans-NIH BioMedical Informatics Coordinating Committee (BMIC) which was established in the Spring of 2007 to improve communication and coordination of issues related to clinical- and bio-informatics at NIH. The Committee provides a forum for sharing information about NIH informatics programs, projects, and plans, including their relationship to activities of other federal agencies and non-government organizations.

Data sharing is becoming an important aspect of scientific research with benefits that include:

  • reinforcing open scientific inquiry,
  • encouraging diversity of analysis and opinion,
  • promoting new research, testing of new or alternative hypotheses and methods of analysis,
  • supporting studies on data collection methods and measurement,
  • facilitating education of new researchers,
  • enabling the exploration of topics not envisioned by the initial investigators,
  • permitting the creation of new datasets by combining data from multiple sources.

Benefits are not just limited to the scientific community. With data sharing everyone benefits, including investigators, funding agencies, the scientific community, and, most importantly, the public. Data sharing provides more effective use of NIH resources by avoiding unnecessary duplication of data collection. It also conserves research funds to support more investigators. The initial investigator benefits, because as the data are used and published more broadly, the initial investigator’s reputation grows.