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Cancer registry and big data exchange
Published in Jun Deng, Lei Xing, Big Data in Radiation Oncology, 2019
Zhenwei Shi, Leonard Wee, Andre Dekker
The Semantic Web (also known as “Linked Data”) is an extension of the Web via many standards by the World Wide Web Consortium (W3C). The standards boost the development of data formats and communication protocols on the Web. Among the various data formats in the Semantic Web, Resource Description Framework (RDF) is the most fundamental format and is commonly used. The rationale behind the RDF data model is that any arbitrary statement about resources within the web can be represented by a simple triple (i.e., subject, predicate, and object). Any levels of complexity in the descriptions of resources are possible using multiple lines of triples. The subject and object here can be considered as two resources. The predicate is the property of the subject and represents the relation between the subject and object. For example, a patient’s survival age, biological sex, and type of carcinoma can be described in the RDF format. Figure 11.4 shows the virtual representation of this ontology.
Data Sharing and Toxicity Modelling
Published in Tiziana Rancati, Claudio Fiorino, Modelling Radiotherapy Side Effects, 2019
Zhenwei Shi, Rianne Fijten, Zhen Zhou, Andre Dekker, Leonard Wee
For the abovementioned distributed learning methodology to work, the local data needs to be parsed in a format that is fully machine-readable and machine-understandable (i.e., objectively semanticized). This is achieved by defining domain ontologies conforming to the standard of the Semantic Web. The Semantic Web is an extension of the internet in which data is intentionally designed to be interpreted by machines rather than humans. In order to achieve machine-readability of the data, structured data is labelled with a publicly accessible semantic ontology. Machine learning algorithms can thus access this via a universal Resource Description Framework (RDF) and the SPARQL Protocol and RDF Query Language (SPARQL). Both sources use Uniform Resource Identifier (URIs) as links between expert semantic meaning and actual physical resources, so that data published through a web “endpoint” is amenable to queries by both machines and people.
Developing General Models and Theories of Addiction
Published in Hanna Pickard, Serge H. Ahmed, The Routledge Handbook of Philosophy and Science of Addiction, 2019
Robert West, Simon Christmas, Janna Hastings, Susan Michie
What is the Semantic Web? One way to answer this question is to chart the development of the Semantic Web from the Worldwide Web (www). The Worldwide Web has revolutionised our lives by making information available from a vast range of sources. It defines a technological framework for locating and exchanging diverse content types – for example, text, images, and films. At the heart of this framework is the Uniform Resource Locator (URL), a unique ‘address’ for each of the billions of different web pages. These URLs are stored as a code that means nothing to human readers, but a system of ‘domain names’ has been developed to link them to a name that humans can read and understand. These also have to be unique. Thus www.addictionjournal.org is a domain name for the journal Addiction that uniquely points to the journal’s home page. Web pages use URLs to link to other pages to create the Worldwide Web.
A new wave of innovation in Semantic web tools for drug discovery
Published in Expert Opinion on Drug Discovery, 2019
Samantha Kanza, Jeremy Graham Frey
Much of today’s scientific knowledge and data has progressed from being kept in the heads of scientists, through being written down in books, to being put into a digital form that (depending on its openness and format) can be searched and consumed much faster than on paper. However, just because something is in a digital form, does not mean it is necessarily going to be useful. Humans process data to turn it into meaningful information, which enables them to build knowledge; the semantic web provides these capabilities by offering the mechanisms to markup data in a linked format, using ontologies to add context and meaning. These techniques have been used in drug discovery to improve the knowledge representation of drug discovery data, thus providing enhanced knowledge bases that can be used to explore undiscovered links and be used in conjunction with other technologies.
Guiding principles for the use of knowledge bases and real-world data in clinical decision support systems: report by an international expert workshop at Karolinska Institutet
Published in Expert Review of Clinical Pharmacology, 2020
Mikael Hoffmann, Robert Vander Stichele, David W Bates, Johanna Björklund, Steve Alexander, Marine L Andersson, Ane Auraaen, Marion Bennie, Marja-Liisa Dahl, Birgit Eiermann, Werner Hackl, Tora Hammar, Paul Hjemdahl, Sabine Koch, Ilkka Kunnamo, Herve Le Louët, Papapetrou Panagiotis, Lembit Rägo, Michael Spedding, Hanna M Seidling, Dina Demner-Fushman, Lars L Gustafsson
The term semantic web introduced by the World Wide Web Consortium (W3C) [55] refers to the internet with an abundance of linked data. Several factual knowledge bases have been made available online, offering computerized reasoning on different data sets [56]. These databases can potentially provide input to CDSSs that uses artificial intelligence to generate new knowledge. Today these systems are often nontransparent for the users, and their validity for use in healthcare has to be demonstrated.