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.

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 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.

scholarly journals A Linked Data approach to evaluate Open Education Resources

2021 ◽  
Vol 15 ◽  
pp. 19-22
Author(s):  
Davide Taibi ◽  
Giovanni Fulantelli ◽  
Stefan Dietze ◽  
Besnik Fetahu
Keyword(s):  
Web 2.0 ◽  
Linked Data ◽  
Open Data ◽  
Online Resources ◽  
Open Education ◽  
Social Environments ◽  
Education Resources ◽  
The Social ◽  
Open Education Resources ◽  
The Web

The social environments based on the Web 2.0 paradigm have modified the way people behave on the Web. One of the direct consequences of this change is that the amount of online resources produced and shared by users has increased considerably. Amongst them, it is possible to find materials that can be exploited for educational purposes. For example, YouTube, Flickr, Slideshare, more and more often collect resources that can be used in educational contexts. In this scenario, finding methods to support the evaluation of the educational relevance of online resources is becoming one of the greatest challenges faced by the educational technologists today. In this paper we propose an approach for the evaluation of the relevance of educational resources based on recent advancements of Linked Open Data.

scholarly journals Publicação e consumo de dados abertos conectados acadêmicos

2018 ◽  
Vol 1 (42) ◽  
pp. 136
Author(s):  
André Alencar ◽  
Douglas Xavier ◽  
Luiz Carlos Chaves ◽  
Damires Yluska Souza
Keyword(s):  
Linked Data ◽  
Open Data ◽  
Semantic Technologies ◽  
Academic Institutions ◽  
Academic Unit ◽  
Data Publication ◽  
Source Data ◽  
Data Consumption ◽  
Data Visualizations ◽  
The Web

<p>Nowadays, the Web may be considered an adequate ecosystem for publication and open data consumption . Published datasets may provide open and, additionally, linked data, which results in the use of semantic technologies such as recommended vocabularies and their connection with other datasets. Taking into account a data scope from the Academic Unit of Informatics at IFPB-Campus João Pessoa, a set of open and linked data was created and published for consumption. This dataset includes information obtained from the Lattes Platform and from some internal data regarding teachers, projects, courses and areas of expertise. Source data went through a process of extraction, transformation and load based on the use of an ontology, named “Ontology for University and Academic Institutions” (OUAI), which was developed in this work. As a result, the dataset was published in the RDF model and was made available for consumption through an endpoint. Based ondata consumption, the OpenUAI application was developed as a means to provide data visualizations on the unit activities and people. This work presents the process regarding the data publication and consumption, the ontology created to help matters, the OpenUAI application and some results obtained with the performed evaluation.</p>

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.

Relationships in semantic data cubes

2020 ◽  
Author(s):  
Alexandr Mansurov ◽  
Olga Majlingova
Keyword(s):  
Linked Data ◽  
Statistical Data ◽  
Open Data ◽  
Data Cube ◽  
Semantic Description ◽  
Data Cubes ◽  
Related Data ◽  
Semantic Data ◽  
Web Standards ◽  
Description Framework

&lt;p&gt;&lt;span&gt;Linked data is a method for publishing structured data in a way that &lt;/span&gt;also expresses its semantics. This semantic description is implemented &lt;span&gt;by the use of vocabularies, which are usually specified by the W3C as web standards. However, anyone can create and register their vocabulary &lt;/span&gt;and register it in an open catalogue like LOV.&lt;/p&gt;&lt;p&gt;&lt;span&gt;There are many situations where it would be useful to be able to publish multi-dimensional data, such as statistics, on the web in such a way that it can be linked to related data sets and concepts. The Data Cube vocabulary provides a means to do this using the W3C RDF (Resource Description Framework) standard. The model underpinning the Data Cube vocabulary is compatible with the cube model that underlies SDMX (Statistical Data and Metadata eXchange), an ISO standard for exchanging &lt;/span&gt;and sharing statistical data and metadata among organizations [1].&lt;br&gt;&lt;br&gt;Given the dispersed nature of linked data, we want to infer &lt;span&gt;relationships between Linked Open Data datasets based on their semantic description. &lt;/span&gt;&lt;span&gt;In particular we are interested in geospatial relationships.&lt;br&gt;&lt;br&gt;&lt;/span&gt; We show a generic approach for relationships in semantic data cubes using the same taxonomies, related dimensions, as well as through &lt;span&gt;structured geographical datasets. Good results were achieved using &lt;/span&gt;structural geographical ontologies in combination with the generic &lt;span&gt;approach for taxonomies.&lt;/span&gt;&lt;/p&gt;&lt;div&gt; &lt;div&gt;&amp;#160;&lt;/div&gt; &lt;/div&gt;&lt;p&gt;&lt;span&gt;&lt;br&gt;[1]&amp;#160; &amp;#160; &amp;#160;Cyganiak, Reynolds, Tennison:&amp;#160; The RDF Data Cube Vocabulary, W3C Recommendation, 16 January 2014, &lt;br&gt;&lt;/span&gt;&lt;/p&gt;

scholarly journals Classification on the Web: an analysis of Dewey Linked Data

2020 ◽  
Vol 9 (2) ◽  
pp. e092
Author(s):  
Kazumi Tomoyose ◽  
Ana Carolina Simionato Arakaki
Keyword(s):  
Linked Data ◽  
World Wide ◽  
Information Science ◽  
Open Data ◽  
Library And Information Science ◽  
Web Environment ◽  
The World ◽  
Data Context ◽  
Positive Factor ◽  
The Web

With the availability of information in the World Wide Web its access and retrieval by the users is facilitated, and the Library and Information Science (LIS) field’s knowledge and techniques can be applied to this environment in order to help with the process. The present study is descriptive, qualitative and exploratory, based on bibliographical sources, in which it was explored how the Classification discipline interacts with Linked Data, focusing on the analysis of Dewey Linked Data. From four catalogs analyzed, referred to in the literature as adhering to Dewey Linked Data, only two actually has links in their records redirecting to the system. Despite this, its presence in The Linked Open Data Cloud appears as a positive factor in its dissemination, since it boosts its visibility. It is concluded that the Classification discipline allows the thematic standardization of information resources, so that there is uniformity in the Web environment and quality retrieval of information, while promoting interoperability between data in the Linked Data context. The standardization of metadata values using classifications optimizes the representation of information and its retrieval in the Web, while also providing the reuse of data. In addition, studies that align the area of Library and Information Science with the Semantic Web and its technologies can provide new perspectives for the area, as well as contemplate the users’ always changing needs, thus, fulfilling the objective of the field.

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.

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