Neuroscience Information Framework (NIF)

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Informatics and new web technologies (e.g. ontologies, social networking and community wikis) are becoming increasingly important to biomedical researchers. The sharing of research data and information pertaining to resources (i.e. tools, data, materials and people) across a research community adds tremendous value to the efforts of that community. An initiative of the NIH Blueprint for Neuroscience Research, the Neuroscience Information Framework (NIF; enables discovery and access to such public research data, contained in databases and structured web resources (e.g. queryable web services) that are sometimes referred to as the deep or hidden web, and resources through an open source dynamic inventory of biomedical resources that are annotated and integrated with a unified system of biomedical terminology.

The NIF provides simultaneous search across multiple types of information sources to connect biomedical researchers to available resources. These sources include the: (1) NIF Registry: A human-curated registry of neuroscience-relevant resources annotated with the NIF vocabulary; (2) NIF Literature: A full text indexed corpus derived from open access literature, full index of PubMed, and specialized bibliographic databases; (3) NIF Database Federation: A federation of independent databases registered to the NIF, allowing for direct search, discovery and integration of database content.  Over the past year, NIF has continued to grow significantly in content, providing access to over 3700 resources through the Registry and more than 30 million database records contained within more than 70 independent databases in the data federation, making NIF the largest source of neuroscience resources on the web. 

Search and annotation of resources and resource content is enhanced through the utilization of a comprehensive modular ontology (NIFSTD; To enable broad community contribution to NIFSTD, NeuroLex ( is available as a wiki that provides an easy entry point for the community. NeuroLex takes advantage of the Semantic Mediawiki open source software to provide an easily accessible interface for viewing and contributing to the lexicon.


Maryann E. Martone
Jeffrey S. Grethe
Amarnath Gupta
Anita Bandrowski
Gordon M. Shepherd
David Van Essen
Giorgio Ascoli
Paul W. Sternberg

Associated Institutions

University of California San Diego
Yale University
George Mason University
Washington University St. Louis
California Institute of Technology

Resource URL
Application Domains
  • Biology
  • Clinical
  • Clinical records
  • Genomics
  • Literature
Other Resource Type
Software Subtype
  • Annotation
  • Document/information retrieval
  • Query tools / business intelligence
  • Text mining
Programming Languages
  • Java
  • Perl
  • Ruby
Operating Systems
  • Linux
  • OS X
  • Unix
  • Windows
Included Components
  • Application Programming Interface
  • Graphical User Interface
  • Library of modular components
  • Plug-in to other software
Dataset Subtype
  • Human annotated
  • Machine annotated
  • Structured data
  • Unstructured data
Data Model Subtype
  • Flat file
  • Object oriented
  • Object relational
  • Relational
  • Warehouse (star or schema)
Online Resource Subtype
  • Registry / repository
Knowledge Base Subtype
  • Controlled vocabulary
  • Ontology
  • Standards
Intended User Types
  • Clinician
  • Clinical researcher
  • Informatics researcher
  • NLP researcher or developer
  • Software developer

Gupta A, Bug W, Marenco L, Qian X, Condit C, Rangarajan A, Müller HM, Miller PL, Sanders B, Grethe JS, Astakhov V, Shepherd G, Sternberg PW, Martone ME. Federated Access to Heterogeneous Information Resources in the Neuroscience Information Framework (NIF). Neuroinformatics. 2008 Sep;6(3):205-17. Epub 2008 Oct 29. PMID: 18958629; PMCID: PMC2689790

Akil, Huda, Maryann E. Martone, and David C. Van Essen. Challenges and Opportunities in Mining Neuroscience Data. Science 11 February 2011: 331(6018): 708-712. DOI: 10.1126/science.1199305

Available Documentation
  • API
  • Included demo/tutorial data
  • PDF documentation
  • Screenshots
  • Text/pictures
  • Tutorial
  • Video
  • Video demonstration
  • Web page/HTML documentation
Licensing Type
Open source
Date of Latest Version