Semantic Web Standards: Legal and Social Issues and Implications

Semantic Web ◽  
2007 ◽  
pp. 413-433 ◽  
Author(s):  
Dov Greenbaum ◽  
Mark Gerstein
2018 ◽  
Vol 2 ◽  
pp. e25614 ◽  
Author(s):  
Florian Pellen ◽  
Sylvain Bouquin ◽  
Isabelle Mougenot ◽  
Régine Vignes-Lebbe

Xper3 (Vignes Lebbe et al. 2016) is a collaborative knowledge base publishing platform that, since its launch in november 2013, has been adopted by over 2 thousand users (Pinel et al. 2017). This is mainly due to its user friendly interface and the simplicity of its data model. The data are stored in MySQL Relational DBs, but the exchange format uses the TDWG standard format SDD (Structured Descriptive DataHagedorn et al. 2005). However, each Xper3 knowledge base is a closed world that the author(s) may or may not share with the scientific community or the public via publishing content and/or identification key (Kopfstein 2016). The explicit taxonomic, geographic and phenotypic limits of a knowledge base are not always well defined in the metadata fields. Conversely terminology vocabularies, such as Phenotype and Trait Ontology PATO and the Plant Ontology PO, and software to edit them, such as Protégé and Phenoscape, are essential in the semantic web, but difficult to handle for biologist without computer skills. These ontologies constitute open worlds, and are expressed themselves by RDF triples (Resource Description Framework). Protégé offers vizualisation and reasoning capabilities for these ontologies (Gennari et al. 2003, Musen 2015). Our challenge is to combine the user friendliness of Xper3 with the expressive power of OWL (Web Ontology Language), the W3C standard for building ontologies. We therefore focused on analyzing the representation of the same taxonomic contents under Xper3 and under different models in OWL. After this critical analysis, we chose a description model that allows automatic export of SDD to OWL and can be easily enriched. We will present the results obtained and their validation on two knowledge bases, one on parasitic crustaceans (Sacculina) and the second on current ferns and fossils (Corvez and Grand 2014). The evolution of the Xper3 platform and the perspectives offered by this link with semantic web standards will be discussed.


Author(s):  
Axel Polleres ◽  
Simon Steyskal

The World Wide Web Consortium (W3C) as the main standardization body for Web standards has set a particular focus on publishing and integrating Open Data. In this chapter, the authors explain various standards from the W3C's Semantic Web activity and the—potential—role they play in the context of Open Data: RDF, as a standard data format for publishing and consuming structured information on the Web; the Linked Data principles for interlinking RDF data published across the Web and leveraging a Web of Data; RDFS and OWL to describe vocabularies used in RDF and for describing mappings between such vocabularies. The authors conclude with a review of current deployments of these standards on the Web, particularly within public Open Data initiatives, and discuss potential risks and challenges.


2011 ◽  
pp. 503-521
Author(s):  
Flavius Frasincar ◽  
Jethro Borsje ◽  
Leonard Levering

This article proposes Hermes, a Semantic Webbased framework for building personalized news services. It makes use of ontologies for knowledge representation, natural language processing techniques for semantic text analysis, and semantic query languages for specifying wanted information. Hermes is supported by an implementation of the framework, the Hermes News Portal, a tool which allows users to have a personalized online access to news items. The Hermes framework and its associated implementation aim at advancing the state-of-the-art of semantic approaches for personalized news services by employing Semantic Web standards, exploiting domain information, using a word sense disambiguation procedure, and being able to express temporal constraints for the desired news items.


Author(s):  
Christopher Walton

In the introductory chapter of this book, we discussed the means by which knowledge can be made available on the Web. That is, the representation of the knowledge in a form by which it can be automatically processed by a computer. To recap, we identified two essential steps that were deemed necessary to achieve this task: 1. We discussed the need to agree on a suitable structure for the knowledge that we wish to represent. This is achieved through the construction of a semantic network, which defines the main concepts of the knowledge, and the relationships between these concepts. We presented an example network that contained the main concepts to differentiate between kinds of cameras. Our network is a conceptualization, or an abstract view of a small part of the world. A conceptualization is defined formally in an ontology, which is in essence a vocabulary for knowledge representation. 2. We discussed the construction of a knowledge base, which is a store of knowledge about a domain in machine-processable form; essentially a database of knowledge. A knowledge base is constructed through the classification of a body of information according to an ontology. The result will be a store of facts and rules that describe the domain. Our example described the classification of different camera features to form a knowledge base. The knowledge base is expressed formally in the language of the ontology over which it is defined. In this chapter we elaborate on these two steps to show how we can define ontologies and knowledge bases specifically for the Web. This will enable us to construct Semantic Web applications that make use of this knowledge. The chapter is devoted to a detailed explanation of the syntax and pragmatics of the RDF, RDFS, and OWL Semantic Web standards. The resource description framework (RDF) is an established standard for knowledge representation on the Web. Taken together with the associated RDF Schema (RDFS) standard, we have a language for representing simple ontologies and knowledge bases on the Web.


2020 ◽  
pp. 016555152093438
Author(s):  
Jose L. Martinez-Rodriguez ◽  
Ivan Lopez-Arevalo ◽  
Ana B. Rios-Alvarado

The Semantic Web provides guidelines for the representation of information about real-world objects (entities) and their relations (properties). This is helpful for the dissemination and consumption of information by people and applications. However, the information is mainly contained within natural language sentences, which do not have a structure or linguistic descriptions ready to be directly processed by computers. Thus, the challenge is to identify and extract the elements of information that can be represented. Hence, this article presents a strategy to extract information from sentences and its representation with Semantic Web standards. Our strategy involves Information Extraction tasks and a hybrid semantic similarity measure to get entities and relations that are later associated with individuals and properties from a Knowledge Base to create RDF triples (Subject–Predicate–Object structures). The experiments demonstrate the feasibility of our method and that it outperforms the accuracy provided by a pattern-based method from the literature.


Author(s):  
Khalid Saleh Aloufi

<span>Open data are available from various private and public institutions in different resource formats. There are already great number of open data that are published using open data portals, where datasets and resources are mainly presented in tabular or sheet formats. However, such formats have some barriers with application developments and web standards. One of the web recommenced standards for semantic web application is RDF. There are various research efforts have been focused on presenting open data in RDF formats. However, no framework has transformed tabular open data into RDFs considering the HTML tags and properties of the resources and datasets. Therefore, a methodology is required to generate RDF resources from this type of open data resources. This methodology applies data transformations of open data from a tabular format to RDF files for the Saudi Open Data Portal. The methodology successfully transforms open data resources in sheet format into RDF resources. Recommendations and future work are given to enhance the development of building open data.</span>


2019 ◽  
Vol 19 (01) ◽  
pp. e05
Author(s):  
Marcos daniel Zarate ◽  
Carlos Buckle ◽  
Renato Mazzanti ◽  
Gustavo Samec

Scientific publication services are changing drastically, researchers demand intelligent search services to discover and relate scientific publications. Publishersneed to incorporate semantic information to better organize their digital assets and make publications more discoverable. In this paper, we present the on-going work to publish a subset of scientific publications of CONICET Digital as Linked Open Data. The objective of this work is to improve the recovery andreuse of data through Semantic Web technologies and Linked Data in the domain of scientific publications.To achieve these goals, Semantic Web standards and reference RDF schema’s have been taken into account (Dublin Core, FOAF, VoID, etc.). The conversion and publication process is guided by the methodological guidelines for publishing government linked data. We also outline how these data can be linked to other datasets DBLP, WIKIDATA and DBPEDIA on the web of data. Finally, we show some examples of queries that answer questions that initially CONICET Digital does not allow


2018 ◽  
Vol 62 (1) ◽  
pp. 4 ◽  
Author(s):  
Yuji Tosaka ◽  
Jung-ran Park

This study uses data from a large original survey (nearly one thousand initial respondents) to present how the cataloging and metadata community is approaching new and emerging data standards and technologies. The data analysis demonstrates strong professional-development interest in Semantic Web and Linked Data applications. With respect to continuing education topics, Linked Data technology, BIBFRAME, and an overview of current and emerging data standards and technologies ranked high. The survey data illustrate that personal continuing education interests often varied from reported institutional needs. These results reflect the fact that library services and projects in these emerging areas have not yet progressed beyond the exploratory stage. They also suggest that cataloging and metadata professionals expect to be able to exercise a mixture of core professional skill sets including teamwork, communication, and subject analysis, and the ability to adapt and accommodate Semantic Web standards and technologies, digital libraries, and other innovations in cataloging and metadata services.


2014 ◽  
Author(s):  
Egon Willighagen

Background. Semantic Web technologies are increasingly used in biological database systems. The improved expressiveness show advantages in tracking provenance and allowing knowledge to be more explicitly annotated. The list of semantic web standards needs a complementary set of tools to handle data in those formats to use them in bioinformatics workflows. Methods. The approach proposed in this paper uses the Apache Jena library to create an environment where semantic web technologies can be use in the statistical environment R. The code is exposed as two R packages available from the Comprehensive R Archive Network (CRAN). The RJava library and a custom convenience class is used to bridge between R and the Jena library. Results. We here present two examples showing how the Resource Description Framework (RDF) and SPARQL query standards can be employed in R. The first example takes input on BRCA1 SNPs from a BioMart and converts this into a RDF data set. The second example runs a query on an experimental remote SPARQL end point provided by Uniprot, and searches textual annotations of proteins encoded by the BRCA1 gene. The third example shows how the package can be used to handle RDF returned by OpenTox web services. Discussion. The two provided library bring basic semantic web technologies to R. While only a subset of Apache Jena is currently exposed, it provides key methods to deal with RDF data and resources. The libraries are freely available from the CRAN under the Affero GNU Public License version 3: http://cran.r-project.org/web/packages/rrdf/.


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