Revision as of 09:14, 8 November 2015

KnowledgeWiki A semantic platform for creating, integrating and curating knowledge graphs. Federated Semantic Services Platform for Open Materials Science and Engineering : Building a semantic infrastructure to create domain models for material science domain, provide semantic search over the multi model data sources and enable the exchanging of material science data via Linked Data.

People

Graduate Students: Nishita Jaykumar, PavanKalyan Yallamelli, Vinh Nguyen, Sarasi Lalithsena
External Collaborators: Clare Paul AFRL/RX PI
Faculty: Amit P. Sheth (Advisor), Krishnaprasad Thirunarayan
Past Members:

Introduction

The White House’s Materials Genome Initiate (MGI) seeks to substantially improve the process of new material discovery and development, and shorten the time to deployment. Two of the core components of this initiative - new and sophisticated computer modeling technologies and next-generation experimental tools - received initial federal research support through 2012. The third major component is that of developing solutions for broader access to scientific data about materials to aid in achieving the goal of faster development of new materials at lower costs.

Our approach recognizes the need for providing easy access to large amounts of highly distributed and heterogeneous data – including unstructured (scientific literature or publications), semi-structured and structured data. We recognize the need to support a variety of data as well as resources that provide data using APIs and Web services. We recognize the need for tools to be able to easily exchange data. We also recognize the need for integrated provenance (i.e., data lineage) to support data quality and relevance, and access control for organizations to share information when desired and yet keep valuable intellectual property confidential. To address these requirements, we will use recent advances in semantic web (standards, search and query processing techniques and tools, Web of Data or Linked Open Data) and semantic services computing, along with integral support for provenance and access control. In a complementary effort during the first year, the development of domain models and knowledge bases (ontologies, taxonomies, and vocabularies), will be carried out with support from ARFL’s Materials and Manufacturing Directorate.

This three-year project will undertake three broad classes of tasks. The first related to creating semantic infrastructure including ability to create semantic metadata for a variety of data types utilizing domain models and knowledge bases. The second relates to semantic search for all varieties of data, including resources with services based access. The third relates to development of a novel semantic data exchange scheme for materials science (termed Linked Open Materials Data) by developing an open data based approach.

Approach

We identified that Semantic Mediawiki is the ideal tool for the task at hand. There are 11 Templates and 28 properties that we determined to be necessary for capturing the data in Material Science.

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