Analyzing broken links on the web of data: An experiment with DBpedia

Rajabi, Enayat; Sánchez‐Alonso, Salvador; Sicilia, Miguel–Ángel

doi:10.1002/asi.23109

Cited by 20 publications

(9 citation statements)

References 10 publications

(7 reference statements)

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“…On one hand, not necessarily every published dataset in the LOD cloud is registered and curated at that repository. On the other hand, the availability of SPARQL endpoints may vary over time [ 6 ], therefore, the obtained sample cannot be guaranteed to be comprehensive, but at least it represents a snapshot in time of collecting datasets from the LOD cloud.…”

Section: Data Collectionmentioning

confidence: 99%

Class and Instance Equivalences in the Web of Linked Data: Distribution and Graph Structure

Sánchez‐Alonso

Sicilia

Rajabi

et al. 2021

Metadata and Semantic Research

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The Web of Linked Open Data (LOD) is a decentralized effort in publishing datasets using a set of conventions to make them accesssible, notably thought RDF and SPARQL. Links across nodes in published datasets are thus critical in getting value for the LOD cloud as a collective effort. Connectivity among the datasets can occur through these links. Equivalence relationship is one of the fundamental links that connects different schemas or datasets, and is used to assert either class or instance equivalence. In this article, we report an empirical study on the equivalences found in over 59 million triples from datasets accessible via SPARQL endpoints in open source data portals. Metrics from graph analysis have been used to examine the relationships between repositories and determine their relative importance as well as their ability to facilitate knowledge discovery.

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Section: Data Collectionmentioning

confidence: 99%

Class and Instance Equivalences in the Web of Linked Data: Distribution and Graph Structure

Sánchez‐Alonso

Sicilia

Rajabi

et al. 2021

Metadata and Semantic Research

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“…Open data helps develop the innovation potential of governments, businesses and entrepreneurs that can provide economic, social and scientific gains [3]- [5]. Additionally, some authors highlight the new opportunities for innovation in public and private sectors that big and open linked data have created [6], [7]; for example, facilitating the generation of new software applications by interconnecting data from different sources on the web [8].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

A Research Agenda on Open Data Impact Process for Open Innovation

Corrales-Garay

Ortiz‐de‐Urbina‐Criado

Mora-Valentín

2020

IEEE Access

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Open data and open innovation are two topics currently attracting the attention of academics. But no previous studies consider these fields in combination while using a bibliometric approach. Thus, the aim of this paper is to understand the relationship between open innovation and open data. Two research questions have been formulated: 1) What are the main topics studied in the literature that combine both lines of research? and 2) How can the open innovation paradigm be integrated in the open data impact process? To address the first question, a co-word analysis is used to identify the main topics investigated in the open innovation and open data literature. Based on our results, to answer the second research question, the topics are grouped and analyzed considering a model of the open data impact process. Finally, some future research lines to analyze the open data impact process for open innovation are presented. For example, future research could focus on questions such as (1) What kind of applications can be created through the reuse of open data?; and (2) How do open innovation processes influence the reuse of open data? INDEX TERMS Open data, open innovation, co-word analysis, theoretical model. the Ph.D. degree in management from Rey Juan Carlos University, Spain. She is currently an Associate Professor of management with Rey Juan Carlos University. Her research has been published in the

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“…These researches raise the need for tools to detect possible quality problems and ambiguities produced by redundancy, inconsistencies and lack of completeness of data and links. Open link problems and strategy in order to solve this problem are described in [16,17]. Quantity of linked data available as of July 2009 and the number of links between RDF dataset are shown in [18].…”

Section: Introductionmentioning

confidence: 99%

Confidence level evaluation of LOD resources on CKAN instances

Cubides¹,

Gaona-García²,

Montenegro-Marín³

et al. 2019

Vis. Electron.

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Linked Open Data has been an initiative aimed at offering principles for the interconnection of data through machine-readable structures and knowledge representation schemes. At present, there are platforms that allow consuming LOD resources, being CKAN one of the most relevant on a large community made up of governmental organizations, NGOs, among others. However, the resources consumption lacks minimum criteria to determine their validity such as level of trust, quality, linkage and usability of the data; aspects that require a previous systematic analysis on the set of published data. To support this process of analysis and determination of the mentioned criteria, this paper has as purpose to present a method that allows analyzing the dataset current state obtained from the different instances published in CKAN, with the aim of evaluating the levels of trust that can offer from their sources. Finally, it presents results, conclusions and future work from the use of the tool for the dataset consumption belonging to certain instances ascribed to the CKAN platform.

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Analyzing broken links on the web of data: An experiment with DBpedia

Cited by 20 publications

References 10 publications

Class and Instance Equivalences in the Web of Linked Data: Distribution and Graph Structure

Class and Instance Equivalences in the Web of Linked Data: Distribution and Graph Structure

A Research Agenda on Open Data Impact Process for Open Innovation

Confidence level evaluation of LOD resources on CKAN instances

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