Cooperative and collaborative data and resource discovery platforms for scientific communities – The Neuroscience Information Framework (NIF) and SciCrunch

 

Date: Thursday, February 12, 2015
Time: 10:00 AM – 11:00 AM (PST); 1:00 PM – 2:00 PM (EST)

 

Presenter

Jeffrey S. Grethe, Ph.D.
Associate Director, Center for Research in Biological Systems
University of California, San Diego

Abstract

Data and information on research resources are everywhere, in numerous repositories and download sites, and more floods in every day. What’s a researcher to do? In order to be able to use shared data, the first fundamental rule is that you have to be able to find it. We have search engines like Google for web documents, PubMed and Google Scholar for articles, NCBI for selected genomics resources. The Neuroscience Information Framework (NIF; neuinfo.org) was instantiated in 2006 in response to a Broad Agency Announcement from the NIH Blueprint for Neuroscience Research citing an overwhelming need for an ”information framework for identifying, locating, and characterizing neuroscience information”. NIF was tasked with surveying the neuroscience resource landscape and developing a resource description framework and search strategy for locating, accessing and utilizing research resources, defined here as data, databases, tools, materials, literature, networks, terminologies, or information that can accelerate the pace of neuroscience research and discovery. NIF adds value to these existing biomedical resources by increasing their discoverability, accessibility, visibility, utility and interoperability, regardless of their current design or capabilities and without the need for extensive redesign of their components or information models. Unlike more general search engines, NIF provides deeper access to a more focused set of resources that are relevant to neuroscience, provides search strategies tailored to neuroscience, and also provides access to content that is traditionally “hidden” from web search engines. To accomplish this, NIF has deployed an infrastructure allowing a wide variety of resources to be searched and discovered at multiple levels of integration, from superficial discovery based on a limited description of the resource (NIF Registry), to deep content query (NIF Data Federation). It is currently one of the largest sources of biomedical information on the web, currently searching over 13,000 research resources in its Registry, and the contents of 250+ data resources comprising more than 800 million records in its Data Federation.

Building on the NIF infrastructure, SciCrunch was designed to help communities of researchers create their own portals to provide access to resources, databases and tools of relevance to their research areas. A data portal that searches across hundreds of databases can be created in minutes. Communities can choose from our existing SciCrunch data sources and also add their own. SciCrunch was designed to break down the traditional types of portal silos created by different communities, so that communities can take advantage of work done by others and share their expertise as well. SciCrunch currently supports a diverse collection of communities in addition to NIF, each with their own data needs: CINERGI – focuses on constructing a community inventory and knowledge base on geoscience information resources; NIDDK Information Network (dkNET) – serves the needs of basic and clinical investigators by providing seamless access to large pools of data relevant to the mission of The National Institute of Diabetes, Digestive and Kidney Disease (NIDDK); Research Identification Initiative (RII) – aims to promote research resource identification, discovery, and reuse.

Biography

Dr. Jeffrey S. Grethe, Ph.D. is a Principal Investigator (MPI) for the Neuroscience Information Framework (NIF; http://neuinfo.org) and the NIDDK Information Network (dkNET; http://dknet.org) in the Center for Research in Biological Systems (CRBS; http://crbs.ucsd.edu) at the University of California, San Diego. Following a B.S. in Applied Mathematics from the University of California, Irvine, he received a doctorate in neurosciences with a focus on neuroinformatics and computational modeling from the University of Southern California. Throughout his career, he has been involved in enabling collaborative research, data sharing and discovery through the application of advanced informatics approaches. This started at USC with his involvement in the Human Brain Project and continues today with his work on NIF, dkNET and with standards bodies such as the International Neuroinformatics Coordinating Facility.

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