Federated Access to Heterogeneous Information Resources in the Neuroscience Information Framework (NIF)

Abstract

The overarching goal of the NIF (Neuroscience Information Framework) project is to be a one-stop-shop for Neuroscience. This paper provides a technical overview of how the system is designed. The technical goal of the first version of the NIF system was to develop an information system that a neuroscientist can use to locate relevant information from a wide variety of information sources by simple keyword queries. Although the user would provide only keywords to retrieve information, the NIF system is designed to treat them as concepts whose meanings are interpreted by the system. Thus, a search for term should find a record containing synonyms of the term.The system is targeted to find information from web pages, publications, databases, web sites built upon databases, XML documents and any other modality in which such information may be published. We have designed a system to achieve this functionality. A central element in the system is an ontology called NIFSTD (for NIF Standard) constructed by amalgamating a number of known and newly developed ontologies. NIFSTD is used by our ontology management module, called OntoQuest to perform ontology-based search over data sources. The NIF architecture currently provides three different mechanisms for searching heterogeneous data sources including relational databases, web sites, XML documents and full text of publications. Version 1.0 of the NIF system is currently in beta test and may be accessed through http://nif.nih.gov.

Computational Ontologies in Orthopaedic Surgery

“…This can be applicable in clinical practice, research and medical education and training [3,11,19]. The data can be represented in a machine-readable way [15] which can facilitate interoperability across multiple databases and provide integrated results from different biomedical resources [18] thus enabling sharing and reuse of data [28] and also making the data relevant for longer periods of time. Ontology-driven information systems facilitate improved and faster decisionmaking by enabling integration of multiple disciplines.…”

“…For example, the NeuroLex [13,15] ontology classifies neuroscience concepts into hierarchies and defines interrelationships among them. It is denoted in the following manner: the class ''neuron'' is a sub-class of the class ''cell'' and defines relations between them such as ''neuron is a cell''.…”

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“…Recent prospectus using XML Recently Gupta and colleagues [12] developed Neuroscience Information Framework (NIF) a one-stop-shop for neuroscience. This system is targeted to find information from web pages, publications, databases, web sites built upon databases, XML documents and any other modality in which such information may be published.…”

BIOMIST: A Platform for Biomedical Data Lifecycle Management of Neuroimaging Cohorts

“…This scalable web architecture makes it possible to serve brain imaging and associated data to distant users over the web or store data in the cloud, as best exemplified with XNAT at the Human Connectome Project. Naturally, with this multiplication of like-minded, yet idiosyncratic web applications for neuroimaging data management, came the need for database federation and interoperability, and for a common lexicon across different systems, such as shared ontologies (Gupta et al, 2008).…”