The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.
In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.
An annotation is extra information associated with a particular point in a document or other piece of information. It can be a note that includes a comment or explanation. Annotations are sometimes presented in the margin of book pages. For annotations of different digital media, see web annotation and text annotation.
Neelie Kroes is a retired Dutch politician of the People's Party for Freedom and Democracy (VVD) and businessperson who served as European Commissioner from 22 November 2004 to 1 November 2014.
E-procurement is the business-to-business or business-to-consumer or business-to-government purchase and sale of supplies, work, and services through the Internet as well as other information and networking systems, such as electronic data interchange and enterprise resource planning.
In information science, an upper ontology is an ontology that consists of very general terms that are common across all domains. An important function of an upper ontology is to support broad semantic interoperability among a large number of domain-specific ontologies by providing a common starting point for the formulation of definitions. Terms in the domain ontology are ranked under the terms in the upper ontology, e.g., the upper ontology classes are superclasses or supersets of all the classes in the domain ontologies.
The CIDOC Conceptual Reference Model (CRM) provides an extensible ontology for concepts and information in cultural heritage and museum documentation. It is the international standard (ISO 21127:2023) for the controlled exchange of cultural heritage information. Galleries, libraries, archives, museums (GLAMs), and other cultural institutions are encouraged to use the CIDOC CRM to enhance accessibility to museum-related information and knowledge.
In computing, linked data is structured data which is interlinked with other data so it becomes more useful through semantic queries. It builds upon standard Web technologies such as HTTP, RDF and URIs, but rather than using them to serve web pages only for human readers, it extends them to share information in a way that can be read automatically by computers. Part of the vision of linked data is for the Internet to become a global database.
A relationship extraction task requires the detection and classification of semantic relationship mentions within a set of artifacts, typically from text or XML documents. The task is very similar to that of information extraction (IE), but IE additionally requires the removal of repeated relations (disambiguation) and generally refers to the extraction of many different relationships.
DBpedia is a project aiming to extract structured content from the information created in the Wikipedia project. This structured information is made available on the World Wide Web using OpenLink Virtuoso. DBpedia allows users to semantically query relationships and properties of Wikipedia resources, including links to other related datasets.
Sir Nigel Richard Shadbolt is Principal of Jesus College, Oxford, and Professorial Research Fellow in the Department of Computer Science, University of Oxford. He is chairman of the Open Data Institute which he co-founded with Tim Berners-Lee. He is also a visiting professor in the School of Electronics and Computer Science at the University of Southampton. Shadbolt is an interdisciplinary researcher, policy expert and commentator. His research focuses on understanding how intelligent behaviour is embodied and emerges in humans, machines and, most recently, on the Web, and has made contributions to the fields of Psychology, Cognitive science, Computational neuroscience, Artificial Intelligence (AI), Computer science and the emerging field of Web science.
Amit Sheth is a computer scientist at University of South Carolina in Columbia, South Carolina. He is the founding Director of the Artificial Intelligence Institute, and a Professor of Computer Science and Engineering. From 2007 to June 2019, he was the Lexis Nexis Ohio Eminent Scholar, director of the Ohio Center of Excellence in Knowledge-enabled Computing, and a Professor of Computer Science at Wright State University. Sheth's work has been cited by over 48,800 publications. He has an h-index of 106, which puts him among the top 100 computer scientists with the highest h-index. Prior to founding the Kno.e.sis Center, he served as the director of the Large Scale Distributed Information Systems Lab at the University of Georgia in Athens, Georgia.
In computer science, information science and systems engineering, ontology engineering is a field which studies the methods and methodologies for building ontologies, which encompasses a representation, formal naming and definition of the categories, properties and relations between the concepts, data and entities of a given domain of interest. In a broader sense, this field also includes a knowledge construction of the domain using formal ontology representations such as OWL/RDF. A large-scale representation of abstract concepts such as actions, time, physical objects and beliefs would be an example of ontological engineering. Ontology engineering is one of the areas of applied ontology, and can be seen as an application of philosophical ontology. Core ideas and objectives of ontology engineering are also central in conceptual modeling.
YAGO is an open source knowledge base developed at the Max Planck Institute for Informatics in Saarbrücken. It is automatically extracted from Wikipedia and other sources.
Knowledge extraction is the creation of knowledge from structured and unstructured sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL, the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge or the generation of a schema based on the source data.
UMBEL is a logically organized knowledge graph of 34,000 concepts and entity types that can be used in information science for relating information from disparate sources to one another. It was retired at the end of 2019. UMBEL was first released in July 2008. Version 1.00 was released in February 2011. Its current release is version 1.50.
In natural language processing, linguistics, and neighboring fields, Linguistic Linked Open Data (LLOD) describes a method and an interdisciplinary community concerned with creating, sharing, and (re-)using language resources in accordance with Linked Data principles. The Linguistic Linked Open Data Cloud was conceived and is being maintained by the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation, but has been a point of focal activity for several W3C community groups, research projects, and infrastructure efforts since then.
The Bahama Leaks are 1.3 million internal files from the company register of the Bahamas. After the release of the Panama Papers in 2016, an unknown source handed over internal data from the national corporate registry of the Bahamas to Frederik Obermaier and Bastian Obermayer, who analyzed them with the help of the International Consortium of Investigative Journalists (ICIJ). At the same time, ICIJ, Süddeutsche Zeitung and other media partners published detailed reporting before they published an online database of offshore entities.
In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the semantics or relationships underlying these entities.
The Vadalog system is a Knowledge Graph Management System (KGMS) that offers a language for performing complex logic reasoning tasks over knowledge graphs. At the same time, Vadalog delivers a platform to support the entire spectrum of data science tasks: data integration, pre-processing, statistical analysis, machine learning, algorithmic modeling, probabilistic reasoning and temporal reasoning. Its language is based on an extension of the rule-based language Datalog, Warded Datalog±, a high-performance language using an aggressive termination control strategy. Vadalog can support the entire spectrum of data science activities and tools. The system can read from and connect to multiple sources, from relational databases, such as PostgreSQL and MySQL, to graph databases, such as Neo4j, as well as make use of machine learning tools, and a web data extraction tool, OXPath. Additional Python libraries and extensions can also be easily integrated into the system.
