Publishing Statistical Data following the Linked Open Data Principles

2013 ◽  
pp. 199-226 ◽  
Author(s):  
Jose María Alvarez Rodríguez ◽  
Jules Clement ◽  
José Emilio Labra Gayo ◽  
Hania Farhan ◽  
Patricia Ordoñez de Pablos
Keyword(s):  
Linked Data ◽  
Statistical Data ◽  
Open Data ◽  
Linked Open Data ◽  
Dimensional Measure ◽  
The Web

This chapter introduces the promotion of statistical data to the Linked Open Data initiative in the context of the Web Index project. A framework for the publication of raw statistics and a method to convert them to Linked Data are also presented following the W3C standards RDF, SKOS, and OWL. This case study is focused on the Web Index project; launched by the Web Foundation, the Index is the first multi-dimensional measure of the growth, utility, and impact of the Web on people and nations. Finally, an evaluation of the advantages of using Linked Data to publish statistics is also presented in conjunction with a discussion and future steps sections.

Publishing Statistical Data following the Linked Open Data Principles

2015 ◽  
pp. 1032-1052
Author(s):  
Jose María Alvarez Rodríguez ◽  
Jules Clement ◽  
José Emilio Labra Gayo ◽  
Hania Farhan ◽  
Patricia Ordoñez de Pablos
Keyword(s):  
Linked Data ◽  
Statistical Data ◽  
Open Data ◽  
Linked Open Data ◽  
Dimensional Measure ◽  
The Web

This chapter introduces the promotion of statistical data to the Linked Open Data initiative in the context of the Web Index project. A framework for the publication of raw statistics and a method to convert them to Linked Data are also presented following the W3C standards RDF, SKOS, and OWL. This case study is focused on the Web Index project; launched by the Web Foundation, the Index is the first multi-dimensional measure of the growth, utility, and impact of the Web on people and nations. Finally, an evaluation of the advantages of using Linked Data to publish statistics is also presented in conjunction with a discussion and future steps sections.

scholarly journals The read–write Linked Data Web

2013 ◽  
Vol 371 (1987) ◽  
pp. 20120513 ◽  
Author(s):  
Tim Berners-Lee ◽  
Kieron O’Hara
Keyword(s):  
Future Development ◽  
Linked Data ◽  
Open Data ◽  
Linked Open Data ◽  
The Future ◽  
The Web

This paper discusses issues that will affect the future development of the Web, either increasing its power and utility, or alternatively suppressing its development. It argues for the importance of the continued development of the Linked Data Web, and describes the use of linked open data as an important component of that. Second, the paper defends the Web as a read–write medium, and goes on to consider how the read–write Linked Data Web could be achieved.

Consuming and producing linked open data: the case of OpenCourseWare

2014 ◽  
Vol 48 (1) ◽  
pp. 16-40 ◽  
Author(s):  
Nelson Piedra ◽  
Edmundo Tovar ◽  
Ricardo Colomo-Palacios ◽  
Jorge Lopez-Vargas ◽  
Janneth Alexandra Chicaiza
Keyword(s):  
Linked Data ◽  
Design Methodology ◽  
Open Data ◽  
Linked Open Data ◽  
Open Learning ◽  
Content Type ◽  
Educational Contents ◽  
Initial Framework

Purpose – The aim of this paper is to present an initiative to apply the principles of Linked Data to enhance the search and discovery of OpenCourseWare (OCW) contents created and shared by the universities. Design/methodology/approach – This paper is a case study of how linked data technologies can be applied for the enhancement of open learning contents. Findings – Results presented under the umbrella of OCW-Universia consortium, as the integration and access to content from different repositories OCW and the development of a query method to access these data, reveal that linked data would offer a solution to filter and select semantically those open educational contents, and automatically are linked to the linked open data cloud. Originality/value – The new OCW-Universia integration with linked data adds new features to the initial framework including improved query mechanisms and interoperability.

Transformation Approach of Open Web Data to Linked Open Data

2021 ◽  
Author(s):  
Amina Meherehera ◽  
Imane Mekideche ◽  
Leila Zemmouchi-Ghomari ◽  
Abdessamed Réda Ghomari
Keyword(s):  
Linked Data ◽  
Open Data ◽  
Linked Open Data ◽  
Web Data ◽  
Semantic Web Technologies ◽  
Automatic Interpretation ◽  
Transformation Approach ◽  
Web Of Data ◽  
Machine Readable ◽  
The Web

A large amount of data available over the Web and, in particular, the open data have, generally, heterogeneous formats and are not machine-readable. One promising solution to overcome the problems of heterogeneity and automatic interpretation is the Linked Data initiative, which aims to provide unified practices for publishing and contextually to link data on the Web, by using World Wide Web Consortium standards and the Semantic Web technologies. LinkedIn data promote the Web’s transformation from a web of documents to a web of data, ensuring that machines and software agents can interpret the semantics of data correctly and therefore infer new facts and return relevant web data search results. This paper presents an automatic generic transformation approach that manipulates several input formats of open web data to linked open data. This work aims to participate actively in the movement of publishing data compliant with linked data principles.

scholarly journals ARALD: Arabic Annotation Using Linked Data

2021 ◽  
Vol 26 (2) ◽  
pp. 143-149
Author(s):  
Abdelghani Bouziane ◽  
Djelloul Bouchiha ◽  
Redha Rebhi ◽  
Giulio Lorenzini ◽  
Noureddine Doumi ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Knowledge Base ◽  
Language Processing ◽  
Linked Data ◽  
Open Data ◽  
Arabic Language ◽  
Linked Open Data ◽  
Main Challenge ◽  
The Web

The evolution of the traditional Web into the semantic Web makes the machine a first-class citizen on the Web and increases the discovery and accessibility of unstructured Web-based data. This development makes it possible to use Linked Data technology as the background knowledge base for unstructured data, especially texts, now available in massive quantities on the Web. Given any text, the main challenge is determining DBpedia's most relevant information with minimal effort and time. Although, DBpedia annotation tools, such as DBpedia spotlight, mainly targeted English and Latin DBpedia versions. The current situation of the Arabic language is less bright; the Web content of the Arabic language does not reflect the importance of this language. Thus, we have developed an approach to annotate Arabic texts with Linked Open Data, particularly DBpedia. This approach uses natural language processing and machine learning techniques for interlinking Arabic text with Linked Open Data. Despite the high complexity of the independent domain knowledge base and the reduced resources in Arabic natural language processing, the evaluation results of our approach were encouraging.

Europeana no Linked Open Data: conceitos de Web Semântica na dimensão aplicada das humanidades digitais

2017 ◽  
Vol 12 (2) ◽  
Author(s):  
Caio Saraiva Coneglian ◽  
José Eduardo Santarem Segundo
Keyword(s):  
Linked Data ◽  
Open Data ◽  
Linked Open Data

O surgimento de novas tecnologias, tem introduzido meios para a divulgação e a disponibilização das informações mais eficientemente. Uma iniciativa, chamada de Europeana, vem promovendo esta adaptação dos objetos informacionais dentro da Web, e mais especificamente no Linked Data. Desta forma, o presente estudo tem como objetivo apresentar uma discussão acerca da relação entre as Humanidades Digitais e o Linked Open Data, na figura da Europeana. Para tal, utilizamos uma metodologia exploratória e que busca explorar as questões relacionadas ao modelo de dados da Europeana, EDM, por meio do SPARQL. Como resultados, compreendemos as características do EDM, pela utilização do SPARQL. Identificamos, ainda, a importância que o conceito de Humanidades Digitais possui dentro do contexto da Europeana.Palavras-chave: Web semântica. Linked open data. Humanidades digitais. Europeana. EDM.Link: https://periodicos.ufsc.br/index.php/eb/article/view/1518-2924.2017v22n48p88/33031

scholarly journals Awareness of Linked Open Data Among the Employees of Polish Libraries, Archives, and Museums

2022 ◽  
Vol 59 (2(118)) ◽  
pp. 7-25
Author(s):  
Dorota Siwecka
Keyword(s):  
Linked Data ◽  
Open Data ◽  
Linked Open Data ◽  
Survey Method ◽  
Doctorate Degree ◽  
Research Libraries ◽  
The People ◽  
Central Statistical ◽  
Central Statistical Office ◽  
The Subject

Purpose/Thesis: This article presents the results of a survey conducted in January 2021 among employees of Polish libraries, museums, and archives, examining their awareness of open linked data technologies. The research had a pilot character and its results will be used to improve the questionnaire and to conduct research on a wider scale. Approach/Methods: The survey method was used in the study. Results and conclusions: On the basis of answers received, it can be concluded that open linked data is not yet very well-known among employees of Polish libraries, museums, and archives. Those most aware of technologies allowing for machine understanding of content shared on the Web are doctorate degree-holders employed in research libraries. Furthermore, awareness of the projects using LOD technologies does not correlate with awareness of these technological solutions. Research limitations: The number of respondents (415) constitutes 1% of all the people employed in libraries, archives, and museums in Poland (based on data provided by the Central Statistical Office of Poland). This is not a large number, but considering the variety among the respondents, the sample can be considered representative. Originality/Value: The awareness of Linked Open Data among employees of Polish libraries, archives, and museums has not been the subject of any study so far. In fact, this type of research has not been conducted in other countries either.

Creation and Integration of Reference Ontologies for Efficient LOD Management

2012 ◽  
pp. 162-199 ◽  
Author(s):  
Mariana Damova ◽  
Atanas Kiryakov ◽  
Maurice Grinberg ◽  
Michael K. Bergman ◽  
Frédérick Giasson ◽  
...  
Keyword(s):  
Real Life ◽  
Open Data ◽  
Real Data ◽  
Heterogeneous Data ◽  
Linked Open Data ◽  
Data Space ◽  
Upper Level ◽  
Reference Knowledge ◽  
Global Data ◽  
The Web

The chapter introduces the process of design of two upper-level ontologies—PROTON and UMBEL—into reference ontologies and their integration in the so-called Reference Knowledge Stack (RKS). It is argued that RKS is an important step in the efforts of the Linked Open Data (LOD) project to transform the Web into a global data space with diverse real data, available for review and analysis. RKS is intended to make the interoperability between published datasets much more efficient than it is now. The approach discussed in the chapter consists of developing reference layers of upper-level ontologies by mapping them to certain LOD schemata and assigning instance data to them so they cover a reasonable portion of the LOD datasets. The chapter presents the methods (manual and semi-automatic) used in the creation of the RKS and gives examples that illustrate its advantages for managing highly heterogeneous data and its usefulness in real life knowledge intense applications.

Linked Open Statistical Metadata

2017 ◽  
pp. 297-320
Author(s):  
Franck Cotton ◽  
Daniel Gillman
Keyword(s):  
Semantic Web ◽  
Resource Description Framework ◽  
Statistical Data ◽  
Open Data ◽  
Statistical Analyses ◽  
Statistical Literacy ◽  
Statistical Process ◽  
Description Framework ◽  
Resource Description ◽  
The Web

Linked Open Statistical Metadata (LOSM) is Linked Open Data (LOD) applied to statistical metadata. LOD is a model for identifying, structuring, interlinking, and querying data published directly on the web. It builds on the standards of the semantic web defined by the W3C. LOD uses the Resource Description Framework (RDF), a simple data model expressing content as predicates linking resources between them or with literal properties. The simplicity of the model makes it able to represent any data, including metadata. We define statistical data as data produced through some statistical process or intended for statistical analyses, and statistical metadata as metadata describing statistical data. LOSM promotes discovery and the meaning and structure of statistical data in an automated way. Consequently, it helps with understanding and interpreting data and preventing inadequate or flawed visualizations for statistical data. This enhances statistical literacy and efforts at visualizing statistics.

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