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Mike Chelen

NIF - 0 views

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    The Neuroscience Information Framework (NIF) is a dynamic inventory of web-based neurosciences data, resources, and tools that scientists and students can access via any computer connected to the Internet. An initiative of the NIH Blueprint for Neuroscience Research, the NIF will advance neuroscience research by enabling discovery and access to public research data and tools worldwide through an open source, networked environment.
Mike Chelen

Neuroscience Information Framework (Main.WebHome) - Neuroscience Information Framework ... - 0 views

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    The advent of the World Wide Web has led to an explosion in the number of diverse resources available to neuroscientists. Despite the availability of powerful search engines, locating these diverse resources has become increasingly difficult and time consuming. The NIF project utilizes both advanced machine-based search technologies and old-fashioned human legwork to provide access to neuroscience-relevant resources on the Web. Resources include research materials, Web pages, software tools, data sets, literature and general information. The NIF has developed technologies that allow a user to search across these different types of resources, all from a single interface. A unique feature of the NIF is the ability to issue direct queries against multiple databases simultaneously, retrieving content that is largely hidden from traditional search engines. A second unique feature is an extensive vocabulary covering major neuroscience domains for describing and searching these resources. The NIF takes advantage of advances in knowledge engineering to broaden and refine searches based on related concepts. The NIF beta test site was developed to gain feedback on the NIF search interface and content. Users will be asked to search the NIF, explore the vocabularies, and answer a questionnaire about their experience.
Mike Chelen

Neuroscience Information Framework - 0 views

shared by Mike Chelen on 15 Dec 08 - Cached
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    Through its resource registry and concept based query system, NIF enhances neuroscience research by enabling discovery and access to research data and tools worldwide.
Mike Chelen

SWAN (Semantic Web Applications in Neuromedicine) Project - 0 views

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    SWAN (Semantic Web Applications in Neuromedicine) is a Web-based collaborative program that aims to organize and annotate scientific knowledge about Alzheimer disease (AD) and other neurodegenerative disorders. Its goal is to facilitate the formation, development and testing of hypotheses about the disease. The ultimate goal of this project is to create tools and resources to manage the evolving universe of data and information about AD in such a way that researchers can easily comprehend their larger context ("what hypothesis does this support or contradict?"), compare and contrast hypotheses ("where do these two hypotheses agree and disagree?"), identify unanswered questions and synthesize concepts and data into ever more comprehensive and useful hypotheses and treatment targets for this disease. The SWAN project is designed to allow the community of AD researchers to author, curate and connect a diversity of data and ideas about AD via secure personal and public SWAN workspaces, using the emerging Semantic Web paradigm for deep interconnection of data, information and knowledge. We are initially focusing on developing a fully public Web resource deployed as part of the Alzheimer Research Forum web site (www.alzforum.org). After the public resource has been launched, we will also develop secure personal workspaces (MySWAN) and semi-private lab workspaces (LabSWAN). An essential component of this project is development of an initial, core knowledge base within SWAN, which will provide immediate value to researchers at the time of deployment. This is a critically important part of our strategy to ensure that the SWAN system gains wide adoption and active participation by the AD research community. As part of our development strategy, we are also recruiting a "beta test" community of AD researchers to enter their own hypotheses, add commentaries and citations, and provide feedback on the technology and content. SWAN is being developed by a collaborative team from
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