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Context-Based Search Engine for Datasets

Technology #20140194-20150025

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Web 2.0MetadataDataset
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Researchers
Jaideep Srivastava, PhD
Professor, Department of Computer Science and Engineering
External Link (dmr.cs.umn.edu)
Ayush Singhal
Graduate Student, College of Science and Engineering
Ravindra Kasturi
Graduate Student, College of Science and Engineering
Managed By
Andrew Morrow
Technology Licensing Officer
Patent Protection

US Patent Pending US20160034512

US Patent Pending US20160034514

Need for Automated Context Generator

Given the emphasis put on empirical evidence in modern science, scientific datasets are a huge component of publications and research documents. Much of this data is useful to future studies, and needs proper data annotation so that the datasets can be found in an online search. Unfortunately, most datasets lack annotations and context that facilitate searching. The need for proper annotation can be met by an automated context generator.

Adding Metadata to Scientific Datasets

A search engine design has been developed that automatically adds context and annotations to research datasets to make them searchable.  Annotations and other metadata are generated through open source information clearly related to the surrounding publication. Searches result in datasets ranked by their annotations’ relevance to user query. Truly in the spirit of Web 2.0, this search engine will ease research and avoid expensive research repetition.

Context-Based Search Engine

This technology provides the base necessary to create a commercial product for searching scientific datasets and improve future searching of the dataset.

BENEFITS AND FEATURES OF CONTEXT-BASED SEARCH ENGINE:

  • Thoroughly annotates obscure datasets to avoid expensive research repetition
  • Provides search engine designed to rank by the relatedness of annotation and user query
  • Expandable beyond dataset annotation to report annotation, intra-organizational document tagging, etc.

Phase of Development Patent Pending