What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- The Internet
Ontology, Semantic Web, World Wide Web, Data science and Context are his primary areas of study.
His Ontology research is multidisciplinary, incorporating perspectives in Ontology and Semantic similarity.
His biological study spans a wide range of topics, including Semantics, Metadata and Basic Formal Ontology.
His research in Semantic similarity intersects with topics in Annotation, Semantic computing, Similarity and Ontology-based data integration.
In most of his Semantic Web studies, his work intersects topics such as Web service.
His study in Data science is interdisciplinary in nature, drawing from both Genetics, Data exchange, Data integration, OBO Foundry and Workflow.
His most cited work include:
- The minimum information about a genome sequence (MIGS) specification. (986 citations)
- Investigating semantic similarity measures across the Gene Ontology: the relationship between sequence and annotation. (760 citations)
- Taverna: lessons in creating a workflow environment for the life sciences (601 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Ontology, World Wide Web, Data science, Semantic Web and Information retrieval.
His study brings together the fields of Ontology and Ontology.
His studies in World Wide Web integrate themes in fields like Semantics and Workflow.
His work often combines Data science and Context studies.
His study in the field of Semantic Web Stack and Semantic grid is also linked to topics like Resource.
Information retrieval is closely attributed to Annotation in his research.
He most often published in these fields:
- Ontology (38.31%)
- World Wide Web (30.52%)
- Data science (16.88%)
What were the highlights of his more recent work (between 2015-2020)?
- Ontology (38.31%)
- Ontology (11.04%)
- World Wide Web (30.52%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Ontology, Ontology, World Wide Web, Domain and Information retrieval.
His Ontology research incorporates elements of Software engineering and Source code.
His Ontology research is multidisciplinary, relying on both Syntax and Biological Ontologies.
His Information retrieval research includes elements of Identifier and Usability.
The concepts of his Open Biomedical Ontologies study are interwoven with issues in Bootstrapping and Data science.
His Data science research includes themes of Annotation, Correctness, Software analytics and Database design.
Between 2015 and 2020, his most popular works were:
- The Ontology for Biomedical Investigations (124 citations)
- Minimum information about tolerogenic antigen-presenting cells (MITAP): a first step towards reproducibility and standardisation of cellular therapies (33 citations)
- Minimum Information about T Regulatory Cells: A Step toward Reproducibility and Standardization. (25 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- The Internet
Phillip Lord mostly deals with Ontology, Penetrance, Mitochondrial DNA, Haplogroup and Genetics.
The study incorporates disciplines such as Domain, World Wide Web and Natural language processing in addition to Ontology.
His World Wide Web research integrates issues from Ontology for Biomedical Investigations and Ontology alignment.
Phillip Lord interconnects OWL-S, Ontology-based data integration and Process ontology in the investigation of issues within Upper ontology.
His studies in Web Ontology Language integrate themes in fields like Ontology and Biological Ontologies.
His work carried out in the field of Ontology brings together such families of science as Metadata, Bioinformatics, Open Biomedical Ontologies, Text mining and Syntax.
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