scholarly journals LINKDALE: A LIGHTWEIGHT LEARNING ENVIRONMENT FOR (GEOSPATIAL) LINKED DATA

2018 ◽  
Vol XLII-4/W8 ◽  
pp. 187-190
Author(s):  
S. Ronzhin ◽  
G. Bosch ◽  
E. Folmer ◽  
R. Lemmens
Keyword(s):  
Linked Data ◽  
Query Language ◽  
Process Integration ◽  
A Priori ◽  
Sparql Query ◽  
Design Consideration ◽  
Specific Data ◽  
Domain Specific ◽  
Description Framework ◽  
Resource Description

<p><strong>Abstract.</strong> Modern software tools for managing Linked Data are often designed for skilled users. Therefore, they cannot be used for education purposes because they require substantial a priori knowledge about the Resource Description Framework and the SPARQL query language. LinkDaLe is a single page application designed to teach students the concept of Linked Data and work with linked data at the same time. In the paper we showcase the interface and functionality of LinkDaLe by triplifying data on Geo4All member organizations. The application was built and evaluated within The Business Process Integration Lab, a master programme course in 2016 and 2017 years. Positive feedback from both students and teachers proved the relevance of the proposed design consideration. LinkDaLe showed usability working with domain specific data e.g. geospatial and logistic data.</p>

scholarly journals An E-Commerce Platform for Industrialized Construction Procurement Based on BIM and Linked Data

2018 ◽  
Vol 10 (8) ◽  
pp. 2613
Author(s):  
Dandan He ◽  
Zhongfu Li ◽  
Chunlin Wu ◽  
Xin Ning
Keyword(s):  
Data Integration ◽  
Construction Industry ◽  
Resource Description Framework ◽  
Linked Data ◽  
Query Language ◽  
Rapid Development ◽  
Data Sources ◽  
Product Data ◽  
Description Framework ◽  
Resource Description

Industrialized construction has raised the requirements of procurement methods used in the construction industry. The rapid development of e-commerce offers efficient and effective solutions, however the large number of participants in the construction industry means that the data involved are complex, and problems arise related to volume, heterogeneity, and fragmentation. Thus, the sector lags behind others in the adoption of e-commerce. In particular, data integration has become a barrier preventing further development. Traditional e-commerce platform, which considered data integration for common product data, cannot meet the requirements of construction product data integration. This study aimed to build an information-integrated e-commerce platform for industrialized construction procurement (ICP) to overcome some of the shortcomings existing platforms. We proposed a platform based on Building Information Modelling (BIM) and linked data, taking an innovative approach to data integration. It uses industrialized construction technology to support product standardization, BIM to support procurement process, and linked data to connect different data sources. The platform was validated using a case study. With the development of an e-commerce ontology, industrialized construction component information was extracted from BIM models and converted to Resource Description Framework (RDF) format. Related information from different data sources was also converted to RDF format, and Simple Protocol and Resource Description Framework Query Language (SPARQL) queries were implemented. The platform provides a solution for the development of e-commerce platform in the construction industry.

Linked Data

2019 ◽  
pp. 87-113
Author(s):  
Leila Zemmouchi-Ghomari
Keyword(s):  
Linked Data ◽  
Query Language ◽  
Exciting Field ◽  
Data Resource ◽  
Simple Protocol ◽  
Web Of Data ◽  
Promising Solution ◽  
Description Framework ◽  
Resource Description ◽  
The Web

The data on the web is heterogeneous and distributed, which makes its integration a sine qua non-condition for its effective exploitation within the context of the semantic web or the so-called web of data. A promising solution for web data integration is the linked data initiative, which is based on four principles that aim to standardize the publication of structured data on the web. The objective of this chapter is to provide an overview of the essential aspects of this fairly recent and exciting field, including the model of linked data: resource description framework (RDF), its query language: simple protocol, and the RDF query language (SPARQL), the available means of publication and consumption of linked data, and the existing applications and the issues not yet addressed in research.

scholarly journals Linked Data Technologies and What Libraries Have Accomplished So Far

2018 ◽  
Vol 3 (1) ◽  
pp. 3 ◽  
Author(s):  
Yongming Wang ◽  
Sharon Q Yang
Keyword(s):  
Linked Data ◽  
Query Language ◽  
The Past ◽  
Hard Time ◽  
Library Community ◽  
The World ◽  
Technical Details ◽  
Description Framework ◽  
National Libraries ◽  
Resource Description

For the past ten years libraries have been working diligently towards Linked Data and the Semantic Web. Due to the complexity and vast scope of Linked Data, many people have a hard time to understand its technical details and its potential for the library community. This paper aims to help librarians better understand some important concepts by explaining the basic Linked Data technologies that consist of Resource Description Framework (RDF), the ontology, and the query language. It also includes an overview of the achievements by libraries around the world in their efforts to turn library data into Linked Data including those by Library of Congress, OCLC, and some other national libraries. Some of the challenges and setbacks that libraries have encountered are analyzed and discussed. In spite of the difficulties, there is no way to turn back. Libraries will have to succeed.

scholarly journals A Framework for Exploration and Visualization of SPARQL Endpoint Information

2020 ◽  
Vol 1 (1) ◽  
pp. 39-69
Author(s):  
Maria Krommyda
Keyword(s):  
Query Language ◽  
Sparql Query ◽  
Data Schema ◽  
Query Result ◽  
Main Challenge ◽  
Integrated Platform ◽  
Data Provision ◽  
Description Framework ◽  
User Friendly ◽  
Resource Description

Widely accepted standards, such as the Resource Description Framework, have provided unified ways for data provision aiming to facilitate the exchange of information between machines. This information became of interest to a wider audience due to its volume and variety but the available formats are posing significant challenges to users with limited knowledge of the Semantic Web. The SPARQL query language alleviates this barrier by facilitating the exploration of this information and many data providers have created dedicated SPARQL endpoints for their data. Many efforts have been dedicated to the development of systems that will provide access and support the exploration of these endpoints in a semantically correct and user friendly way. The main challenge of such approaches is the diversity of the information contained in the endpoints, which renders holistic or schema specific solutions obsolete. We present here an integrated platform that supports the users to the querying, exploration and visualization of information contained in SPARQL endpoints. The platform handles each query result independently based only on its characteristics, offering an endpoint and data schema agnostic solution. This is achieved through a Decision Support System, developed based on a knowledge base containing information experimentally collected from many endpoints, that allows us to provide case-specific visualization strategies for SPARQL query results based exclusively on features extracted from the result.

scholarly journals PROVIDING GEOGRAPHIC DATASETS AS LINKED DATA IN SDI

2016 ◽  
Vol XLI-B2 ◽  
pp. 583-586 ◽  
Author(s):  
E. Hietanen ◽  
L. Lehto ◽  
P. Latvala
Keyword(s):  
Information Content ◽  
Linked Data ◽  
Web Browser ◽  
Data Format ◽  
Spatial Objects ◽  
Ontology Language ◽  
Geographic Datasets ◽  
Description Framework ◽  
Data Objects ◽  
Resource Description

In this study, a prototype service to provide data from Web Feature Service (WFS) as linked data is implemented. At first, persistent and unique Uniform Resource Identifiers (URI) are created to all spatial objects in the dataset. The objects are available from those URIs in Resource Description Framework (RDF) data format. Next, a Web Ontology Language (OWL) ontology is created to describe the dataset information content using the Open Geospatial Consortium’s (OGC) GeoSPARQL vocabulary. The existing data model is modified in order to take into account the linked data principles. The implemented service produces an HTTP response dynamically. The data for the response is first fetched from existing WFS. Then the Geographic Markup Language (GML) format output of the WFS is transformed on-the-fly to the RDF format. Content Negotiation is used to serve the data in different RDF serialization formats. This solution facilitates the use of a dataset in different applications without replicating the whole dataset. In addition, individual spatial objects in the dataset can be referred with URIs. Furthermore, the needed information content of the objects can be easily extracted from the RDF serializations available from those URIs. &lt;br&gt;&lt;br&gt; A solution for linking data objects to the dataset URI is also introduced by using the Vocabulary of Interlinked Datasets (VoID). The dataset is divided to the subsets and each subset is given its persistent and unique URI. This enables the whole dataset to be explored with a web browser and all individual objects to be indexed by search engines.

scholarly journals Biotea, semantics for Pubmed Central

2017 ◽  
Author(s):  
Alexander Garcia ◽  
Federico Lopez ◽  
Leyla Garcia ◽  
Olga Giraldo ◽  
Victor Bucheli ◽  
...  
Keyword(s):  
Linked Data ◽  
Scientific Literature ◽  
Query Language ◽  
Biomedical Ontology ◽  
Sparql Query ◽  
Biomedical Literature ◽  
Automatic Annotation ◽  
Pubmed Central ◽  
Web Technologies ◽  
Aggregate Content

A significant portion of biomedical literature is represented in a manner that makes it difficult for consumers to find or aggregate content through a computational query. One approach to facilitate reuse of the scientific literature is to structure this information as linked data using standardized web technologies. In this paper we present the second version of Biotea, a semantic, linked data version of the open-access subset of PubMed Central that has been enhanced with specialized annotation pipelines that uses existing infrastructure from the National Center for Biomedical Ontology. We expose our models, services, software and datasets. Our infrastructure enables manual and semi-automatic annotation, resulting data are represented as RDF-based linked data and can be readily queried using the SPARQL query language. We illustrate the utility of our system with several use cases. Availability: Our datasets, methods and techniques are available at http://biotea.github.io

scholarly journals MuSe: a multi-level storage scheme for big RDF data using MapReduce

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Tanvi Chawla ◽  
Girdhari Singh ◽  
Emmanuel S. Pilli
Keyword(s):  
Linked Data ◽  
State Of The Art ◽  
Query Execution ◽  
Hadoop Mapreduce ◽  
Storage Scheme ◽  
The Common ◽  
Multi Level ◽  
Rdf Data ◽  
Description Framework ◽  
Resource Description

AbstractResource Description Framework (RDF) model owing to its flexible structure is increasingly being used to represent Linked data. The rise in amount of Linked data and Knowledge graphs has resulted in an increase in the volume of RDF data. RDF is used to model metadata especially for social media domains where the data is linked. With the plethora of RDF data sources available on the Web, scalable RDF data management becomes a tedious task. In this paper, we present MuSe—an efficient distributed RDF storage scheme for storing and querying RDF data with Hadoop MapReduce. In MuSe, the Big RDF data is stored at two levels for answering the common triple patterns in SPARQL queries. MuSe considers the type of frequently occuring triple patterns and optimizes RDF storage to answer such triple patterns in minimum time. It accesses only the tables that are sufficient for answering a triple pattern instead of scanning the whole RDF dataset. The extensive experiments on two synthetic RDF datasets i.e. LUBM and WatDiv, show that MuSe outperforms the compared state-of-the art frameworks in terms of query execution time and scalability.

scholarly journals Stalking the Resources for Security in Linked Data Applications Using Resource Description Framework

2020 ◽  
Vol 25 (6) ◽  
pp. 793-801
Author(s):  
Maturi Sreerama Murty ◽  
Nallamothu Nagamalleswara Rao
Keyword(s):  
Resource Description Framework ◽  
Linked Data ◽  
Work Rate ◽  
Provenance Information ◽  
Information Reconciliation ◽  
Global Positioning ◽  
Source Data ◽  
Description Framework ◽  
Alternate Routes ◽  
Resource Description

Following the accessibility of Resource Description Framework (RDF) resources is a key capacity in the establishment of Linked Data frameworks. It replaces center around information reconciliation contrasted with work rate. Exceptional Connected Data that empowers applications to improve by changing over legacy information into RDF resources. This data contains bibliographic, geographic, government, arrangement, and alternate routes. Regardless, a large portion of them don't monitor the subtleties and execution of each sponsored resource. In such cases, it is vital for those applications to track, store and scatter provenance information that mirrors their source data and introduced tasks. We present the RDF information global positioning framework. Provenance information is followed during the progress cycle and oversaw multiple times. From that point, this data is appropriated utilizing of this concept URIs. The proposed design depends on the Harvard Library Database. The tests were performed on informational indexes with changes made to the qualities??In the RDF and the subtleties related with the provenance. The outcome has quieted the guarantee as in it pulls in record wholesalers to make significant realities that develop while taking almost no time and exertion.

scholarly journals Transitioning from XML to RDF: Considerations for an effective move towards Linked Data and the Semantic Web

2016 ◽  
Vol 35 (1) ◽  
pp. 51 ◽  
Author(s):  
Juliet L. Hardesty
Keyword(s):  
Semantic Web ◽  
Linked Data ◽  
Academic Library ◽  
Data Sets ◽  
Markup Language ◽  
Digital Repository ◽  
Extensible Markup ◽  
Description Framework ◽  
Meaningful Relationships ◽  
Resource Description

Metadata, particularly within the academic library setting, is often expressed in eXtensible Markup Language (XML) and managed with XML tools, technologies, and workflows. Managing a library’s metadata currently takes on a greater level of complexity as libraries are increasingly adopting the Resource Description Framework (RDF). Semantic Web initiatives are surfacing in the library context with experiments in publishing metadata as Linked Data sets and also with development efforts such as BIBFRAME and the Fedora 4 Digital Repository incorporating RDF. Use cases show that transitions into RDF are occurring in both XML standards and in libraries with metadata encoded in XML. It is vital to understand that transitioning from XML to RDF requires a shift in perspective from replicating structures in XML to defining meaningful relationships in RDF. Establishing coordination and communication among these efforts will help as more libraries move to use RDF, produce Linked Data, and approach the Semantic Web.

scholarly journals Towards Interactive Analytics over RDF Graphs

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 34 ◽  
Author(s):  
Maria-Evangelia Papadaki ◽  
Nicolas Spyratos ◽  
Yannis Tzitzikas
Keyword(s):  
Query Language ◽  
Proposed Model ◽  
Aggregate Queries ◽  
Rdf Data ◽  
Description Framework ◽  
Rdf Graphs ◽  
High Level ◽  
Resource Description ◽  
Functional Algebra ◽  
Continuous Accumulation

The continuous accumulation of multi-dimensional data and the development of Semantic Web and Linked Data published in the Resource Description Framework (RDF) bring new requirements for data analytics tools. Such tools should take into account the special features of RDF graphs, exploit the semantics of RDF and support flexible aggregate queries. In this paper, we present an approach for applying analytics to RDF data based on a high-level functional query language, called HIFUN. According to that language, each analytical query is considered to be a well-formed expression of a functional algebra and its definition is independent of the nature and structure of the data. In this paper, we investigate how HIFUN can be used for easing the formulation of analytic queries over RDF data. We detail the applicability of HIFUN over RDF, as well as the transformations of data that may be required, we introduce the translation rules of HIFUN queries to SPARQL and we describe a first implementation of the proposed model.

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