IMPROVED LINKED DATA INTERACTION THROUGH AN AUTOMATIC INFORMATION ARCHITECTURE

2012 ◽  
Vol 22 (03) ◽  
pp. 325-343 ◽  
Author(s):  
JOSEP MARIA BRUNETTI ◽  
ROSA GIL ◽  
JUAN MANUEL GIMENO ◽  
ROBERTO GARCIA
Keyword(s):  
User Experience ◽  
Linked Data ◽  
Open Data ◽  
Information Architecture ◽  
Data Publishing ◽  
Tabular Data ◽  
Automatic Information ◽  
Web Of Data ◽  
New Perspective ◽  
The Web

Thanks to Open Data initiatives the amount of data available on the Web is rapidly increasing. Unfortunately, most of these initiatives only publish raw tabular data, which makes its analysis and reuse very difficult. Linked Data principles allow for a more sophisticated approach by making explicit both the structure and semantics of the data. However, from the user experience viewpoint, published datasets continue to be monolithic files which are completely opaque or difficult to explore by making complex semantic queries. Our objective is to facilitate the user to grasp what kind of entities are in the dataset, how they are interrelated, which are their main properties and values, etc. Rhizomer is a data publishing tool whose interface provides a set of components borrowed from Information Architecture (IA) that facilitate getting an insight of the dataset at hand. Rhizomer automatically generates navigation menus and facets based on the kinds of things in the dataset and how they are described through metadata properties and values. This tool is currently being evaluated with end users that discover a whole new perspective of the Web of Data.

scholarly journals Improving Access to the Dutch Historical Censuses with Linked Open Data

2018 ◽  
Vol 3 (1) ◽  
pp. 13-26
Author(s):  
Albert Meroño-Peñuela ◽  
Ashkan Ashkpour ◽  
Valentijn Gilissen ◽  
Jan Jonker ◽  
Tom Vreugdenhil ◽  
...  
Keyword(s):  
Economic History ◽  
Linked Data ◽  
Census Data ◽  
Social Economic ◽  
Open Data ◽  
Data Cube ◽  
Data Publishing ◽  
Database Interface ◽  
Knowledge Intensive ◽  
The Web

The Dutch Historical Censuses (1795–1971) contain statistics that describe almost two centuries of History in the Netherlands. These censuses were conducted once every 10 years (with some exceptions) from 1795 to 1971. Researchers have used its wealth of demographic, occupational, and housing information to answer fundamental questions in social economic history. However, accessing these data has traditionally been a time consuming and knowledge intensive task. In this paper, we describe the outcomes of the cedar project, which make access to the digitized assets of the Dutch Historical Censuses easier, faster, and more reliable. This is achieved by using the data publishing paradigm of Linked Data from the Semantic Web. We use a digitized sample of 2,288 census tables to produce a linked dataset of more than 6.8 million statistical observations. The dataset is modeled using the rdf Data Cube, Open Annotation, and prov vocabularies. The contributions of representing this dataset as Linked Data are: (1) a uniform database interface for efficient querying of census data; (2) a standardized and reproducible data harmonization workflow; and (3) an augmentation of the dataset through richer connections to related resources on the Web.

SPedia

2018 ◽  
pp. 1576-1596
Author(s):  
Muhammad Ahtisham Aslam ◽  
Naif Radi Aljohani
Keyword(s):  
Knowledge Base ◽  
Open Data ◽  
Data Publishing ◽  
High Quality ◽  
Scientific Publications ◽  
Sparql Endpoint ◽  
Web Of Data ◽  
Intelligent Searching ◽  
The Web

Producing the Linked Open Data (LOD) is getting potential to publish high-quality interlinked data. Publishing such data facilitates intelligent searching from the Web of data. In the context of scientific publications, data about millions of scientific documents published by hundreds and thousands of publishers is in silence as it is not published as open data and ultimately is not linked to other datasets. In this paper the authors present SPedia: a semantically enriched knowledge base of data about scientific documents. SPedia knowledge base provides information on more than nine million scientific documents, consisting of more than three hundred million RDF triples. These extracted datasets, allow users to put sophisticated queries by employing semantic Web techniques instead of relying on keyword-based searches. This paper also shows the quality of extracted data by performing sample queries through SPedia SPARQL Endpoint and analyzing results. Finally, the authors describe that how SPedia can serve as central hub for the cloud of LOD of scientific publications.

SPedia

2017 ◽  
Vol 13 (1) ◽  
pp. 128-147 ◽  
Author(s):  
Muhammad Ahtisham Aslam ◽  
Naif Radi Aljohani
Keyword(s):  
Knowledge Base ◽  
Open Data ◽  
Data Publishing ◽  
High Quality ◽  
Scientific Publications ◽  
Sparql Endpoint ◽  
Web Of Data ◽  
Intelligent Searching ◽  
The Web

Producing the Linked Open Data (LOD) is getting potential to publish high-quality interlinked data. Publishing such data facilitates intelligent searching from the Web of data. In the context of scientific publications, data about millions of scientific documents published by hundreds and thousands of publishers is in silence as it is not published as open data and ultimately is not linked to other datasets. In this paper the authors present SPedia: a semantically enriched knowledge base of data about scientific documents. SPedia knowledge base provides information on more than nine million scientific documents, consisting of more than three hundred million RDF triples. These extracted datasets, allow users to put sophisticated queries by employing semantic Web techniques instead of relying on keyword-based searches. This paper also shows the quality of extracted data by performing sample queries through SPedia SPARQL Endpoint and analyzing results. Finally, the authors describe that how SPedia can serve as central hub for the cloud of LOD of scientific publications.

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.

Role of Vocabularies for Semantic Interoperability in Enabling the Linked Open Data Publishing

2013 ◽  
pp. 84-104
Author(s):  
Ahsan Morshed
Keyword(s):  
Open Data ◽  
Controlled Vocabulary ◽  
Data Publishing ◽  
Centralized Control ◽  
Web Of Data ◽  
Internet Information ◽  
Skills Education ◽  
Standard Terms ◽  
The Web

In the spite of explosive growth of the Internet, information relevant to users is often unavailable even when using the latest browsers. At the same time, there is an ever-increasing number of documents that vary widely in content, format, and quality. The documents often change in content and location because they do not belong to any kind of centralized control. On the other hand, there is a huge number of unknown users with extremely diverse needs, skills, education, and cultural and language backgrounds. One of the solutions to these problems might be to use standard terms with meaning; this can be termed as controlled vocabulary (CV). Though there is no specific notion of CV, we can define it as a set of concepts or preferred terms and existing relations among them. These vocabularies play very important roles classifying the information. In this chapter, we focus the role of CV for publishing the web of data on the Web.

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.

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.

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.

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