Amit Sheth

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Amit Sheth
Born Gujarat, India
Residence Dayton, Ohio
Alma mater Ohio State University, Birla Institute of Technology and Science
Occupation Director of Kno.e.sis Center
Title Professor at Wright State University
Website Amit Sheth

Dr. Amit Sheth is a computer scientist at Wright State University in Dayton, Ohio. He is the Lexis Nexis Ohio Eminent Scholar for Advanced Data Management and Analysis. [1] Up to September 2015, Sheth's work has been cited by 31,622 publications.[2] He has an h-index of 88,[2] which puts him among the top 100 computer scientists with the highest h-index.[3] Prior to founding the Knoesis center, he served as the director of the Large Scale Distributed Information Systems lab, at the University of Georgia in Athens, Georgia.

Education

Sheth received his Bachelors in Engineering from Birla Institute of Technology and Science in Computer Science in 1981. He received his MS and Ph.D in Computer Science from the Ohio State University in 1983 and 1985 respectively.

Research

Semantic interoperability/integration and semantic web

Sheth has investigated, demonstrated, and advocated comprehensive use of metadata. He explored syntactical, structural, and semantic metadata; recently, he has pioneered ontology-driven approaches to metadata extraction and semantic analytics. He was among the first researchers to utilize description logics based ontologies for schema and information integration (a decade before W3C adopted a DL-based ontology representation standard) and first to deliver a keynote about Semantic Web Application in Search.[4][5] His work on multi-ontology query processing includes the most cited paper on the topic (over 881 citations [6]). In 1996, he introduced the powerful concept of Metadata Reference Link (MREF) for associating metadata to hypertext that links documents on the Web, and described an RDF-based realization in 1998, long before RDF was adopted as a W3C recommendation. A part of his recent work has focussed on information extraction from text to generate semantic metadata in the form of RDF. In his work, semantic metadata extracted from biological text is made up of complex knowledge structures (complex entities and relationships) that reflect complex interactions in biomedical knowledge.[7] Sheth has recently proposed a realization of Dr. Vannevar Bush's MEMEX vision as the Relationship Web[8] based on the semantic metadata extracted from text. He has written many articles regarding this. Sheth and co-inventors were awarded the first known patent for commercial semantic web application in browsing, searching, profiling, personalization and advertising[9] which led to the First Semantic Semantic Search company “Talee” founded by him.

Workflow management and semantic web services

In the early 1990s, he initiated research in the formal modeling, scheduling, and correctness of workflows. His METEOR project demonstrated the value of research with real-world applications; its tools were used in graduate courses in several countries, and its technology was licensed to create a commercial product.

The follow-on METEOR-S project has been highly influential. He led the research (later joined by IBM) that resulted in the W3C submission of WSDL-S (Semantic Annotation of WSDL), the basis for SAWSDL, a W3C recommendation for adding semantics to WSDL and XML Schema.

He currently guides the development of SA-REST, which supports microformat-based annotation of popular RESTful services and WebAPIs. For both SAWSDL and SA-REST, he has provided leadership in the community-based process followed by W3C. He coauthored a 1995 paper in the journal of Distributed & Parallel Databases (Springer),which is one of the most cited papers in the area of workflow management literature, with more than 2100 citations, as well as the most cited among over 430 papers published in that journal.[10]

Information integration

  • Federated and multidatabase architectures for integration and interoperability of heterogeneous databases, organized along the dimensions of distribution, heterogeneity, and autonomy
  • Schema and view integration, with new and practical integration techniques and tools including the first tool on schema integration (1987) developed in the United States
  • Quality and integrity of data in multiple databases, defining the concept of polytransaction and multidatabase consistency specification with innovative ticketing method for multidatabase concurrency control.

His 1990 ACM Computing Surveys paper, with over 3244 citations, [11] is the most cited in this area, the second most cited paper in the broader area of distributed database, and the second most cited paper among over 1000 published in that important journal. He offered the first tutorial on heterogeneous database integration at the International Conference on Data Engineering in 1987.

Richer relationship identification on linked open data

Sheth has been a strong proponent of identifying richer and broader set of relationship such as meronomy and causality on the Semantic Web. His idea of a "relationship web"[12] is inspired from the vision of memex given by Vannevar Bush . Since the inception of linked data he has placed a heavy emphasis on the utilization of schema knowledge and information present in the web and linked data for the purpose. These ideas lead to a system called BLOOMS[13] for the identification of schema level relationships between datasets belonging to Linked data. Another related system called PLATO allows for identification of partonomical relationship between entities on linked data.

Semantics and social data

In the early 2009 he initiated and framed the issue of social media analysis in a broad set of semantic dimensions he called "Spatio-Temporal-Thematic" (STT). He emphasised the analysis of social data from the perspective of people, content, sentiment analysis and emotions. This idea lead to a system called Twitris,[14] which employs dynamically evolving semantic models[15] produced by the semantic web project Doozer[16] for this purpose. Twitris system can identify people's emotions (such as: joy, sadness, anger, fear, etc.) from their social media posts [17] by applying machine learning techniques with millions of self-labeled emotion tweets.[18]

Awards

  • IBM Faculty Award 2004[21]
  • National Merit Scholar, Government of India, 1975

References

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