What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Database
- Software
The scientist’s investigation covers issues in Ontology, Semantic Web, Information retrieval, World Wide Web and Ontology.
His biological study spans a wide range of topics, including Data mining and Natural language processing.
As a part of the same scientific family, Peter Haase mostly works in the field of Semantic Web, focusing on Semantic similarity and, on occasion, Context, Layer, Similarity, Data access layer and External Data Representation.
He specializes in Information retrieval, namely Query language.
Peter Haase works mostly in the field of World Wide Web, limiting it down to concerns involving Semantics and, occasionally, Peer-to-peer, Network topology and Semantic network.
The concepts of his Upper ontology study are interwoven with issues in Ontology-based data integration and Process ontology.
His most cited work include:
- OWL 2 Web Ontology Language: structural specification and functional-style syntax (538 citations)
- FedX: optimization techniques for federated query processing on linked data (254 citations)
- Consistent evolution of OWL ontologies (219 citations)
What are the main themes of his work throughout his whole career to date?
Peter Haase mainly investigates Ontology, World Wide Web, Information retrieval, Semantic Web and Process ontology.
His Upper ontology, OWL-S and Ontology alignment study, which is part of a larger body of work in Ontology, is frequently linked to Ontology, bridging the gap between disciplines.
In his work, Web Ontology Language is strongly intertwined with Natural language processing, which is a subfield of Upper ontology.
His research combines Context and World Wide Web.
His Semantic Web research includes themes of Web service, Description logic and Unified Modeling Language.
His study explores the link between Process ontology and topics such as Ontology-based data integration that cross with problems in Data science.
He most often published in these fields:
- Ontology (42.38%)
- World Wide Web (33.11%)
- Information retrieval (27.81%)
What were the highlights of his more recent work (between 2011-2020)?
- Information retrieval (27.81%)
- World Wide Web (33.11%)
- Big data (4.64%)
In recent papers he was focusing on the following fields of study:
His main research concerns Information retrieval, World Wide Web, Big data, RDF and Software engineering.
His work on Ontology and Relational database as part of general Information retrieval research is frequently linked to Schema, thereby connecting diverse disciplines of science.
His work on Semantic Web, Semantic Web Stack and Semantic computing as part of general World Wide Web study is frequently connected to Ask price, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His work in the fields of Semantic Web, such as Semantic analytics, overlaps with other areas such as History.
His Big data research is multidisciplinary, incorporating perspectives in Scalability, Query Rewriting, Data science and Library science.
Many of his research projects under Software engineering are closely connected to Reuse with Reuse, tying the diverse disciplines of science together.
Between 2011 and 2020, his most popular works were:
- Optique: Zooming in on Big Data (82 citations)
- Optique: Towards OBDA Systems for Industry (42 citations)
- Scalable End-User Access to Big Data (38 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Database
- Software
His scientific interests lie mostly in Big data, Information retrieval, Scalability, Relational database and Database.
In the subject of general Information retrieval, his work in Ontology is often linked to Reuse, thereby combining diverse domains of study.
The Ontology study combines topics in areas such as Query language, Query Rewriting and Usability.
His study in Scalability is interdisciplinary in nature, drawing from both Software engineering, Systems architecture, Architecture specification and Web Ontology Language.
His Relational database study combines topics in areas such as Semantic technology and RDF.
His work on Measure and Analytics is typically connected to Scale as part of general Database study, connecting several disciplines of science.
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