scholarly journals Semantic Profiles for Easing SensorML Description: Review and Proposal

2019 ◽  
Vol 8 (8) ◽  
pp. 340
Author(s):  
Tagliolato Paolo ◽  
Fugazza Cristiano ◽  
Oggioni Alessandro ◽  
Carrara Paola
Keyword(s):  
Semantic Web ◽  
Earth Observation ◽  
New Family ◽  
Sensor Model ◽  
Sensor Web ◽  
The Earth ◽  
Ex Post ◽  
Validation Criteria ◽  
Web Of Data ◽  
The Web

The adoption of Sensor Web Enablement (SWE) practices by sensor maintainers is hampered by the inherent complexity of the Sensor Model Language (SensorML), its high expressiveness, and the scarce availability of editing tools. To overcome these issues, the Earth Observation (EO) community often recurs to SensorML profiles narrowing the range of admitted metadata structures and value ranges. Unfortunately, profiles frequently fall short of providing usable editing tools and comprehensive validation criteria, particularly for the difficulty of checking value ranges in the multi-tenanted domain of the Web of Data. In this paper, we provide an updated review of current practices, techniques, and tools for editing SensorML in the perspective of profile support and introduce our solution for effective profile definition. Beside allowing for formalization of a broad range of constraints that concur in defining a metadata profile, our proposal closes the gap between profile definition and actual editing of the corresponding metadata by allowing for ex-ante validation of the metadata that is produced. On this basis, we suggest the notion of Semantic Web SensorML profiles, characterized by a new family of constraints involving Semantic Web sources. We also discuss implementation of SensorML profiles with our tool and pinpoint the benefits with respect to the existing ex-post validation facilities provided by schema definition languages.

Semantic Web Standards for Publishing and Integrating Open Data

2014 ◽  
pp. 28-47
Author(s):  
Axel Polleres ◽  
Simon Steyskal
Keyword(s):  
Semantic Web ◽  
World Wide ◽  
Open Data ◽  
Standard Data ◽  
Web Standards ◽  
Web Of Data ◽  
Structured Information ◽  
Potential Risks ◽  
Rdf Data ◽  
The Web

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.

Linked Data, Towards Realizing the Web of Data

2018 ◽  
pp. 292-312
Author(s):  
Leila Zemmouchi-Ghomari
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Web Applications ◽  
Online Data ◽  
Web Of Data ◽  
Promising Solution ◽  
Basic Ideas ◽  
Online Sources ◽  
Significant Effort ◽  
The Web

Data play a central role in the effectiveness and efficiency of web applications, such as the Semantic Web. However, data are distributed across a very large number of online sources, due to which a significant effort is needed to integrate this data for its proper utilization. A promising solution to this issue is the linked data initiative, which is based on four principles related to publishing web data and facilitating interlinked and structured online data rather than the existing web of documents. The basic ideas, techniques, and applications of the linked data initiative are surveyed in this paper. The authors discuss some Linked Data open issues and potential tracks to address these pending questions.

Web Data Quality

2014 ◽  
Vol 10 (2) ◽  
pp. 1-6 ◽  
Author(s):  
Amrapali Zaveri ◽  
Andrea Maurino ◽  
Laure-Berti Equille
Keyword(s):  
Semantic Web ◽  
Data Quality ◽  
Linked Data ◽  
Web Data ◽  
Semantic Web Technologies ◽  
Future Directions ◽  
Web Technologies ◽  
Current State ◽  
Web Of Data ◽  
The Web

The standardization and adoption of Semantic Web technologies has resulted in an unprecedented volume of data being published as Linked Data (LD). However, the “publish first, refine later” philosophy leads to various quality problems arising in the underlying data such as incompleteness, inconsistency and semantic ambiguities. In this article, we describe the current state of Data Quality in the Web of Data along with details of the three papers accepted for the International Journal on Semantic Web and Information Systems' (IJSWIS) Special Issue on Web Data Quality. Additionally, we identify new challenges that are specific to the Web of Data and provide insights into the current progress and future directions for each of those challenges.

A URI is Worth a Thousand Tags

2011 ◽  
pp. 279-302 ◽  
Author(s):  
Alexandre Passant ◽  
Philippe Laublet ◽  
John G. Breslin ◽  
Stefan Decker
Keyword(s):  
Semantic Web ◽  
User Generated Content ◽  
Social Web ◽  
Enterprise 2.0 ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
The Social ◽  
Web Of Data ◽  
Accepted Practice ◽  
The Web

Although tagging is a widely accepted practice on the Social Web, it raises various issues like tags ambiguity and heterogeneity, as well as the lack of organization between tags. We believe that Semantic Web technologies can help solve many of these issues, especially considering the use of formal resources from the Web of Data in support of existing tagging systems and practices. In this article, we present the MOAT—Meaning Of A Tag—ontology and framework, which aims to achieve this goal. We will detail some motivations and benefits of the approach, both in an Enterprise 2.0 ecosystem and on the Web. As we will detail, our proposal is twofold: It helps solve the problems mentioned previously, and weaves user-generated content into the Web of Data, making it more efficiently interoperable and retrievable.

Semantic Web Standards for Publishing and Integrating Open Data

2015 ◽  
pp. 1-20 ◽  
Author(s):  
Axel Polleres ◽  
Simon Steyskal
Keyword(s):  
Semantic Web ◽  
World Wide ◽  
Open Data ◽  
Standard Data ◽  
Web Standards ◽  
Web Of Data ◽  
Structured Information ◽  
Potential Risks ◽  
Rdf Data ◽  
The Web

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.

scholarly journals Data Linking for the Semantic Web

2011 ◽  
Vol 7 (3) ◽  
pp. 46-76 ◽  
Author(s):  
Alfio Ferrara ◽  
Andriy Nikolov ◽  
François Scharffe
Keyword(s):  
Graph Theory ◽  
Natural Language Processing ◽  
Semantic Web ◽  
Language Processing ◽  
Linked Data ◽  
Background Information ◽  
Web Of Data ◽  
Comprehensive Survey ◽  
Term Data ◽  
The Web

By specifying that published datasets must link to other existing datasets, the 4th linked data principle ensures a Web of data and not just a set of unconnected data islands. The authors propose in this paper the term data linking to name the problem of finding equivalent resources on the Web of linked data. In order to perform data linking, many techniques were developed, finding their roots in statistics, database, natural language processing and graph theory. The authors begin this paper by providing background information and terminological clarifications related to data linking. Then a comprehensive survey over the various techniques available for data linking is provided. These techniques are classified along the three criteria of granularity, type of evidence, and source of the evidence. Finally, the authors survey eleven recent tools performing data linking and we classify them according to the surveyed techniques.

A URI is Worth a Thousand Tags

2009 ◽  
Vol 5 (3) ◽  
pp. 71-94 ◽  
Author(s):  
Alexandre Passant ◽  
Philippe Laublet ◽  
John G. Breslin ◽  
Stefan Decker
Keyword(s):  
Semantic Web ◽  
User Generated Content ◽  
Social Web ◽  
Enterprise 2.0 ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
The Social ◽  
Web Of Data ◽  
Accepted Practice ◽  
The Web

Although tagging is a widely accepted practice on the Social Web, it raises various issues like tags ambiguity and heterogeneity, as well as the lack of organization between tags. We believe that Semantic Web technologies can help solve many of these issues, especially considering the use of formal resources from the Web of Data in support of existing tagging systems and practices. In this article, we present the MOAT—Meaning Of A Tag—ontology and framework, which aims to achieve this goal. We will detail some motivations and benefits of the approach, both in an Enterprise 2.0 ecosystem and on the Web. As we will detail, our proposal is twofold: It helps solve the problems mentioned previously, and weaves user-generated content into the Web of Data, making it more efficiently interoperable and retrievable.

scholarly journals Data Linking for the Semantic Web

Semantic Web ◽  
2013 ◽  
pp. 169-200 ◽  
Author(s):  
Alfio Ferraram ◽  
Andriy Nikolov ◽  
François Scharffe
Keyword(s):  
Graph Theory ◽  
Natural Language Processing ◽  
Semantic Web ◽  
Language Processing ◽  
Linked Data ◽  
Background Information ◽  
Web Of Data ◽  
Comprehensive Survey ◽  
Term Data ◽  
The Web

By specifying that published datasets must link to other existing datasets, the 4th linked data principle ensures a Web of data and not just a set of unconnected data islands. The authors propose in this paper the term data linking to name the problem of finding equivalent resources on the Web of linked data. In order to perform data linking, many techniques were developed, finding their roots in statistics, database, natural language processing and graph theory. The authors begin this paper by providing background information and terminological clarifications related to data linking. Then a comprehensive survey over the various techniques available for data linking is provided. These techniques are classified along the three criteria of granularity, type of evidence, and source of the evidence. Finally, the authors survey eleven recent tools performing data linking and we classify them according to the surveyed techniques.

GEEK

2011 ◽  
pp. 10-33
Author(s):  
Lian Shi ◽  
Diego Berrueta ◽  
Sergio Fernández ◽  
Luis Polo ◽  
Iván Mínguez ◽  
...  
Keyword(s):  
Semantic Web ◽  
Data Gathering ◽  
Enterprise Management ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Internet Communities ◽  
Person Description ◽  
Project Description ◽  
Web Of Data ◽  
The Web

Finding experts over the Web using semantics has recently received increased attention, especially its application to enterprise management. This scenario introduces many novel challenges to the Web of Data. Gathering Enterprise Expertise Knowledge (GEEK) is a research project which fosters the adoption of Semantic Web technologies within the enterprise environment. GEEK has produced a prototype that demonstrates how to extract and infer expertise by taking into account people’s participation in various online communities (forums and projects). The reuse and interlinking of existing, well-established vocabularies in the areas of person description (FOAF), Internet communities (SIOC), project description (DOAP) and vocabulary sharing (SKOS) are explored in our framework, as well as a proposal for applying customized rules and other enabling technologies to the expert finding task.

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