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Journal articles on the topic 'RDF triples'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

Chystiakova, I. S. "Mapping of the descriptive logic into RDF using binary relational data model." PROBLEMS IN PROGRAMMING, no. 1 (March 2021): 056–83. http://dx.doi.org/10.15407/pp2021.01.056.

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This paper is dedicated to the data integration problem. To establish relationships between data models is one of the key tasks in this solution. The descriptive logic and the relational data model are at the heart of a study. They have been used to create a mapping method on the theoretical level. The binary relational data model has been developed as a part of a mapping method. The previous studies are continued in this paper to prove on practice a mapping creation method between the descriptive logic and the binary relational data model. The method uses the binary relational data model as a

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Bai, Luyi, Nan Li, and Huilei Bai. "An integration approach of multi-source heterogeneous fuzzy spatiotemporal data based on RDF." Journal of Intelligent & Fuzzy Systems 40, no. 1 (2021): 1065–82. http://dx.doi.org/10.3233/jifs-201258.

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With the growing importance of the fuzzy spatiotemporal data in information application, there is an increasing need for researching on the integration method of multi-source heterogeneous fuzzy spatiotemporal data. In this paper, we first propose a fuzzy spatiotemporal RDF graph model based on RDF (Resource Description Framework) that proposed by the World Wide Web Consortium (W3C) to represent data in triples (subject, predicate, object). Secondly, we analyze and classify the related heterogeneous problems of multi-source heterogeneous fuzzy spatiotemporal data, and use the fuzzy spatiotempo

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Santipantakis, Giorgos, Konstantinos Kotis, Apostolos Glenis, George Vouros, Christos Doulkeridis, and AKRIVI VLACHOU. "RDF-Gen: generating RDF triples from big data sources." Knowledge and Information Systems 64 (August 13, 2022): 2985–3015. https://doi.org/10.1007/s10115-022-01729-x.

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Transforming disparate and heterogeneous data sources that provide large volumes of data in high velocity into a common form allows integrated and enriched views on data and thus provides further opportunities to advance the effectiveness and accuracy of data analysis and prediction tasks. This paper presents the RDF-Gen approach for transforming data provided by archival and streaming data sources, provided in various formats, into RDF triples, according to a set of ontological specifications. RDF-Gen introduces a generic mechanism which supports the transformation of data efficiently (i.e.,

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Sneha, Kumari, Pandey Dr.Rajiv, Singh Amit, and Pathak Himanshu. "SPARQL: SEMANTIC INFORMATION RETRIEVAL BY EMBEDDING PREPOSITIONS." International Journal of Network Security & Its Applications (IJNSA) 6, no. 1 (2014): 49–57. https://doi.org/10.5281/zenodo.6360935.

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Semantic web document representation is formulated using RDF/OWL. RDF representation is in the form of triples & OWL in form of ontologies. The above representation leads to a data set which needs to be queried using software agents, machines. W3C has recommended SPARQL to be the de facto query language for RDF. This paper proposes to suggest a model to enable SPARQL to make search efficient, easier and produce meaningful search distinguished on the basis of preposition. An RDF data source primarily consist of data that is represented in the form of a Triple pattern which has an appropriat

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Soliman, Hatem, Izhar Ahmed Khan, and Yasir Hussain. "Learning to transfer knowledge from RDF Graphs with gated recurrent units." Intelligent Data Analysis 26, no. 3 (2022): 679–94. http://dx.doi.org/10.3233/ida-215919.

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The Internet is a vital part of today’s ecosystem. The speedy evolution of the Internet has brought up practical issues such as the problem of information retrieval. Several methods have been proposed to solve this issue. Such approaches retrieve the information by using SPARQL queries over the Resource Description Framework (RDF) content which requires a precise match concerning the query structure and the RDF content. In this work, we propose a transfer learning-based neural learning method that helps to search RDF graphs to provide probabilistic reasoning between the queries and their resul

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Soliman, Hatem, Izhar Ahmed Khan, and Yasir Hussain. "Learning to transfer knowledge from RDF Graphs with gated recurrent units." Intelligent Data Analysis 26, no. 3 (2022): 679–94. http://dx.doi.org/10.3233/ida-215919.

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The Internet is a vital part of today’s ecosystem. The speedy evolution of the Internet has brought up practical issues such as the problem of information retrieval. Several methods have been proposed to solve this issue. Such approaches retrieve the information by using SPARQL queries over the Resource Description Framework (RDF) content which requires a precise match concerning the query structure and the RDF content. In this work, we propose a transfer learning-based neural learning method that helps to search RDF graphs to provide probabilistic reasoning between the queries and their resul

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Natarajan, Senthilselvan, Subramaniyaswamy Vairavasundaram, Yuvaraja Teekaraman, Ramya Kuppusamy, and Arun Radhakrishnan. "Schema-Based Mapping Approach for Data Transformation to Enrich Semantic Web." Wireless Communications and Mobile Computing 2021 (November 10, 2021): 1–15. http://dx.doi.org/10.1155/2021/8567894.

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Modern web wants the data to be in Resource Description Framework (RDF) format, a machine-readable form that is easy to share and reuse data without human intervention. However, most of the information is still available in relational form. The existing conventional methods transform the data from RDB to RDF using instance-level mapping, which has not yielded the expected results because of poor mapping. Hence, in this paper, a novel schema-based RDB-RDF mapping method (relational database to Resource Description Framework) is proposed, which is an improvised version for transforming the relat

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RAMANUJAM, SUNITHA, VAIBHAV KHADILKAR, LATIFUR KHAN, MURAT KANTARCIOGLU, BHAVANI THURAISINGHAM, and STEVEN SEIDA. "UPDATE-ENABLED TRIPLIFICATION OF RELATIONAL DATA INTO VIRTUAL RDF STORES." International Journal of Semantic Computing 04, no. 04 (2010): 423–51. http://dx.doi.org/10.1142/s1793351x10001073.

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The current buzzword in the Internet community is the Semantic Web initiative proposed by the W3C to yield a Web that is more flexible and self-adapting. However, for the Semantic Web initiative to become a reality, heterogeneous data sources need to be integrated in order to enable access to them in a homogeneous manner. Since a vast majority of data currently resides in relational databases, integrating relational data sources with semantic web technologies is at the top of the list of activities required to realize the semantic web vision. Several efforts exist that publish relational data

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Elzein, Nahla Mohammed, Mazlina Abdul Majid, Ibrahim Abaker Targio Hashem, Ashraf Osman Ibrahim, Anas W. Abulfaraj, and Faisal Binzagr. "JQPro:Join Query Processing in a Distributed System for Big RDF Data Using the Hash-Merge Join Technique." Mathematics 11, no. 5 (2023): 1275. http://dx.doi.org/10.3390/math11051275.

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In the last decade, the volume of semantic data has increased exponentially, with the number of Resource Description Framework (RDF) datasets exceeding trillions of triples in RDF repositories. Hence, the size of RDF datasets continues to grow. However, with the increasing number of RDF triples, complex multiple RDF queries are becoming a significant demand. Sometimes, such complex queries produce many common sub-expressions in a single query or over multiple queries running as a batch. In addition, it is also difficult to minimize the number of RDF queries and processing time for a large amou

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Perera, Rivindu, Parma Nand, and Gisela Klette. "RealText-lex: A Lexicalization Framework for RDF Triples." Prague Bulletin of Mathematical Linguistics 106, no. 1 (2016): 45–68. http://dx.doi.org/10.1515/pralin-2016-0011.

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Abstract The online era has made available almost cosmic amounts of information in the public and semi-restricted domains, prompting development of corresponding host of technologies to organize and navigate this information. One of these developing technologies deals with encoding information from free form natural language into a structured form as RDF triples. This representation enables machine processing of the data, however the processed information can not be directly converted back to human language. This has created a need to be able to lexicalize machine processed data existing as tr

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Bouchiha, Djelloul, Mimoun Malki, Abdullah Alghamdi, and Khalid Alnafjan. "Htab2RDF: Mapping HTML Tables to RDF Triples." Computing and Informatics 36, no. 6 (2017): 1467–91. http://dx.doi.org/10.4149/cai_2017_6_1467.

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Wang, Dong, Lei Zou, and Dongyan Zhao. "gst-store: Querying Large Spatiotemporal RDF Graphs." Data and Information Management 1, no. 2 (2017): 84–103. http://dx.doi.org/10.1515/dim-2017-0008.

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Abstract The Simple Protocol and RDF Query Language (SPARQL) query language allows users to issue a structural query over a resource description framework (RDF) graph. However, the lack of a spatiotemporal query language limits the usage of RDF data in spatiotemporal-oriented applications. As the spatiotemporal information continuously increases in RDF data, it is necessary to design an effective and efficient spatiotemporal RDF data management system. In this paper, we formally define the spatiotemporal information-integrated RDF data, introduce a spatiotemporal query language that extends th

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Ahmad Khan, Aatif, and Sanjay Kumar Malik. "Assessing Large-Scale, Cross-Domain Knowledge Bases for Semantic Search." Mehran University Research Journal of Engineering and Technology 39, no. 3 (2020): 595–602. http://dx.doi.org/10.22581/muet1982.2003.14.

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Semantic Search refers to set of approaches dealing with usage of Semantic Web technologies for information retrieval in order to make the process machine understandable and fetch precise results. Knowledge Bases (KB) act as the backbone for semantic search approaches to provide machine interpretable information for query processing and retrieval of results. These KB include Resource Description Framework (RDF) datasets and populated ontologies. In this paper, an assessment of the largest cross-domain KB is presented that are exploited in large scale semantic search and are freely available on

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Vaisman, Alejandro, and Kevin Chentout. "Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels." ISPRS International Journal of Geo-Information 8, no. 8 (2019): 353. http://dx.doi.org/10.3390/ijgi8080353.

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This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be disp

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STALMANN, KAI, DENNIS WEGENER, MARTIN DOERR, HERMANN JOSEF HILL, and NATALJA FRIESEN. "SEMANTIC-BASED RETRIEVAL OF CULTURAL HERITAGE MULTIMEDIA OBJECTS." International Journal of Semantic Computing 06, no. 03 (2012): 315–27. http://dx.doi.org/10.1142/s1793351x12400107.

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Today's search interfaces typically offer keyword searches and facets for the retrieval of cultural heritage multimedia objects. Facets, however, are usually based on a static set of metadata fields. This set is often called an indexing profile. Graph-based repositories based on predicates about resources allow for more precise semantics. They offer stronger support for retrieval, and they can be adopted to almost any metadata format. Technically, those predicates may be serialized as RDF triples, but handling a huge amount of objects with numerous predicates puts an unpredictable load on the

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GEORGIEVA-TRIFONOVA, Tsvetanka, and Miroslav GALABOV. "Transforming 3D Models to Semantic Web Representation." Romanian Journal of Information Science and Technology 2023, no. 1 (2023): 33–48. http://dx.doi.org/10.59277/romjist.2023.1.03.

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"The purpose of the present paper is to research a rule-based approach for transforming X3D (eXtensible 3D) models to RDF (Resource Description Framework). The transformation is performed by using the RDF Mapping Language (RML). Its advantages are summarized, which are mainly due to the fact that the rules created build a knowledge base. By applying SPARQL (SPARQL Protocol and RDF Query Language) queries to it, the possibility of explore in order to validate and improve the defined RML rules themselves, is pointed out. An approach for reversing from the RDF triples to the original X3D in a uni

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Tomaszuk, Dominik, and David Hyland-Wood. "RDF 1.1: Knowledge Representation and Data Integration Language for the Web." Symmetry 12, no. 1 (2020): 84. http://dx.doi.org/10.3390/sym12010084.

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Resource Description Framework (RDF) can seen as a solution in today’s landscape of knowledge representation research. An RDF language has symmetrical features because subjects and objects in triples can be interchangeably used. Moreover, the regularity and symmetry of the RDF language allow knowledge representation that is easily processed by machines, and because its structure is similar to natural languages, it is reasonably readable for people. RDF provides some useful features for generalized knowledge representation. Its distributed nature, due to its identifier grounding in IRIs, natura

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Gao, Mingxia, Jianguo Lu, and Furong Chen. "Medical Knowledge Graph Completion Based on Word Embeddings." Information 13, no. 4 (2022): 205. http://dx.doi.org/10.3390/info13040205.

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The aim of Medical Knowledge Graph Completion is to automatically predict one of three parts (head entity, relationship, and tail entity) in RDF triples from medical data, mainly text data. Following their introduction, the use of pretrained language models, such as Word2vec, BERT, and XLNET, to complete Medical Knowledge Graphs has become a popular research topic. The existing work focuses mainly on relationship completion and has rarely solved entities and related triples. In this paper, a framework to predict RDF triples for Medical Knowledge Graphs based on word embeddings (named PTMKG-WE)

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Khodadadi, Nima, M. G. El El-Mahgoub, and Rokaia M. Zaki. "Mining Sematic Association Rules from RDF Data." Journal of Artificial Intelligence and Metaheuristics 4, no. 1 (2023): 43–51. http://dx.doi.org/10.54216/jaim.040105.

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Many fields rely heavily on the accurate and consistent portrayal of structured data. In order to effectively express and link information on the Semantic Web, RDF (Resource Description Framework) data is essential. Here, we present a process for extracting semantic association rules from RDF data. For our method, we employ the Apriori algorithm to mine the RDF triples for hidden connections between ideas and relationships. Using metrics such as confidence, support, and lift, we examine how well our model performs. We also give visual representations, like as scatter plots and clustered matric

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Rivero, Carlos R., Inma Hernández, David Ruiz, and Rafael Cochuelo. "Discovering and Analysing Ontological Models From Big RDF Data." Journal of Database Management 26, no. 2 (2015): 48–61. http://dx.doi.org/10.4018/jdm.2015040104.

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We are witnessing an increasing popularity of the Web of Data, which exposes a large variety of web sources that provide their data using RDF. Ontological models are used as the schema to organize this data. These models are usually shared by several communities and, to devise them, there is usually an agreement amongst those communities. As a result, it is common to have more than one ontological model to understand some RDF data; therefore, there might be a gap between the ontological models and the RDF data, which is not negligible in practice. In this article, the authors present a techniq

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Swar, Ahmed, Ghada Khoriba, and Mohamed Belal. "A unified ontology-based data integration approach for the internet of things." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 2097. http://dx.doi.org/10.11591/ijece.v12i2.pp2097-2107.

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<span lang="EN-US">Data integration enables combining data from various data sources in a standard format. Internet of things (IoT) applications use ontology approaches to provide a machine-understandable conceptualization of a domain. We propose a unified ontology schema approach to solve all IoT integration problems at once. The data unification layer maps data from different formats to data patterns based on the unified ontology model. This paper proposes a middleware consisting of an ontology-based approach that collects data from different devices. IoT middleware requires an additio

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Ahmed, Swar, Khoriba Ghada, and Belal Mohamed. "A unified ontology-based data integration approach for the internet of things." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 2097–107. https://doi.org/10.11591/ijece.v12i2.pp2097-2107.

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Data integration enables combining data from various data sources in a standard format. Internet of things (IoT) applications use ontology approaches to provide a machine-understandable conceptualization of a domain. We propose a unified ontology schema approach to solve all IoT integration problems at once. The data unification layer maps data from different formats to data patterns based on the unified ontology model. This paper proposes a middleware consisting of an ontology-based approach that collects data from different devices. IoT middleware requires an additional semantic layer for cl

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Konstantinou, Nikolaos, Dimitrios-Emmanuel Spanos, Dimitris Kouis, and Nikolas Mitrou. "An Approach for the Incremental Export of Relational Databases into RDF Graphs." International Journal on Artificial Intelligence Tools 24, no. 02 (2015): 1540013. http://dx.doi.org/10.1142/s0218213015400138.

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Several approaches have been proposed in the literature for offering RDF views over databases. In addition to these, a variety of tools exist that allow exporting database contents into RDF graphs. The approaches in the latter category have often been proved demonstrating better performance than the ones in the former. However, when database contents are exported into RDF, it is not always optimal or even necessary to export, or dump as this procedure is often called, the whole database contents every time. This paper investigates the problem of incremental generation and storage of the RDF gr

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Rakhmawati, Nur Aini, and Lutfi Nur Fadzilah. "Dataset Characteristics Identification for Federated SPARQL Query." Scientific Journal of Informatics 6, no. 1 (2019): 23–33. http://dx.doi.org/10.15294/sji.v6i1.17258.

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Nowadays, the amount of data published in the RDF format is increasing. Federated SPARQL query engines that can query from multiple distributed SPARQL endpoints have been developed recently. A federated query engine usually has different performance compared to the others. One of the factors that affect the performance of the query engine is the characteristic of the accessed RDF dataset, such as the number of triples, the number of classes, the number of properties, the number of subjects, the number of entities, the number of objects, and the spreading factor of a dataset. The aim of this wo

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Sutejo, Agus, Rahmat Gernowo, and Michael Andreas Purwoadi. "Ontology learning from object-relational mapping metadata and relational database." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (2024): 1116. http://dx.doi.org/10.11591/ijeecs.v33.i2.pp1116-1125.

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Ontologies play an important role in representing the semantics of data sources. Building an ontology as a representation of domain knowledge from available data sources is not a simple process, particularly when dealing with relational data, which remains prevalent in existing knowledge systems. In this study, we create an ontology from a relational database using object-relational mapping (ORM) metadata as additional rules for mapping. Our method comprises two main phases: ontology schema construction using ORM metadata and the generation of ontology instances from the relational database. D

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Sutejo, Agus, Rahmat Gernowo, and Michael Andreas Purwoadi. "Ontology learning from object-relational mapping metadata and relational database." Indonesian Journal of Electrical Engineering and Computer Science 33, no. 2 (2024): 1116–25. https://doi.org/10.11591/ijeecs.v33.i2.pp1116-1125.

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Ontologies play an important role in representing the semantics of data sources. Building an ontology as a representation of domain knowledge from available data sources is not a simple process, particularly when dealing with relational data, which remains prevalent in existing knowledge systems. In this study, we create an ontology from a relational database using object-relational mapping (ORM) metadata as additional rules for mapping. Our method comprises two main phases: ontology schema construction using ORM metadata and the generation of ontology instances from the relational database. D

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Khamis, Khamis Abdul Latif, Luo Zhong, and Hua Zhu Song. "Loading RDF/OWL File into Oracle NoSQL Database Using a Bulk Loading and Parallelization Techniques." Applied Mechanics and Materials 631-632 (September 2014): 1011–15. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.1011.

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Processing and loading large RDF/OWL data files often involves the transfer of large amounts of data from source operational systems to the target data store. It requires a proper loading techniques and more expressive methods to ensure the RDF/OWL data files are correctly loaded into the database, or the loading process will end up finishing all memory space which resulted in performance deterioration in the entire application. The Bulk loading is one of the predominant scientific techniques and with fastest loading method to load large amounts of data into the database; however, this study h

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Ringwald, Célian, Fabien Gandon, Catherine Faron, Franck Michel, and Hanna Abi Akl. "Well-Written Knowledge Graphs: Most Effective RDF Syntaxes for Triple Linearization in End-to-End Extraction of Relations from Texts (Student Abstract)." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 21 (2024): 23631–32. http://dx.doi.org/10.1609/aaai.v38i21.30502.

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Seq-to-seq generative models recently gained attention for solving the relation extraction task. By approaching this problem as an end-to-end task, they surpassed encoder-based-only models. Little research investigated the effects of the output syntaxes on the training process of these models. Moreover, a limited number of approaches were proposed for extracting ready-to-load knowledge graphs following the RDF standard. In this paper, we consider that a set of triples can be linearized in many different ways, and we evaluate the combined effect of the size of the language models and different

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Hartmann, Thomas, Benjamin Zapilko, Joachim Wackerow, and Kai Eckert. "Directing the Development of Constraint Languages by Checking Constraints on RDF Data." International Journal of Semantic Computing 10, no. 02 (2016): 193–217. http://dx.doi.org/10.1142/s1793351x16400079.

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For research institutes, data libraries, and data archives, validating RDF data according to predefined constraints is a much sought-after feature, particularly as this is taken for granted in the XML world. Based on our work in two international working groups on RDF validation and jointly identified requirements to formulate constraints and validate RDF data, we have published 81 types of constraints that are required by various stakeholders for data applications. In this paper, we evaluate the usability of identified constraint types for assessing RDF data quality by (1) collecting and clas

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Zec, Tatjana. "On the Roman domination problem of some Johnson graphs." Filomat 37, no. 7 (2023): 2067–75. http://dx.doi.org/10.2298/fil2307067z.

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A Roman domination function (RDF) on a graph G with a set of vertices V = V(G) is a function f : V ? {0, 1, 2} which satisfies the condition that each vertex v ? V such that f (v) = 0 is adjacent to at least one vertex u such that f (u) = 2. The minimum weight value of an RDF on graph G is called the Roman domination number (RDN) of G and it is denoted by ?R(G). An RDF for which ?R(G) is achieved is called a ?R(G)-function. This paper considers Roman domination problem for Johnson graphs Jn,2 and Jn,3. For Jn,2, n ? 4 it is proved that ?R(Jn,2) = n ? 1. New lower and upper bounds for Jn,3, n ?

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Szwabe, Andrzej, Pawel Misiorek, Michal Ciesielczyk, and Czeslaw Jedrzejek. "Collaborative Filtering Based on Bi-Relational Data Representation." Foundations of Computing and Decision Sciences 38, no. 1 (2013): 67–83. http://dx.doi.org/10.2478/v10209-011-0021-x.

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Abstract Widely-referenced approaches to collaborative filtering (CF) are based on the use of an input matrix that represents each user profile as a vector in a space of items and each item as a vector in a space of users. When the behavioral input data have the form of (userX, likes, itemY) and (userX, dislikes, itemY) triples one has to propose a representation of the user feedback data that is more suitable for the use of propositional data than the ordinary user-item ratings matrix. We propose to use an element-fact matrix, in which columns represent RDF-like behavioral data triples and ro

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Allocca, Carlo, and Alexandros Gougousis. "A Preliminary Investigation of Reversing RML: From an RDF dataset to its Column-Based data source." Biodiversity Data Journal 3 (July 29, 2015): e5464. https://doi.org/10.3897/BDJ.3.e5464.

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A large percentage of scientific data with tabular structure are published on the Web of Data as interlinked RDF datasets. When we come to the issue of long-term preservation of such RDF-based digital objects, it is important to provide full support for reusing them in the future. In particular, it should include means for both players who have no familiarity with RDF data model and, at the same time, who by working only with the native format of the data still provide sufficient information. To achieve this, we need mechanisms to bring the data back to their original format and structure. In

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Martini, Ricardo G., Cristiana Araújo, and Pedro Rangel Henriques. "Uma Ontologia CIDOC-CRM para o Museu Virtual da Emigração." Revista ComInG - Communications and Innovations Gazette 1, no. 1 (2016): 79. http://dx.doi.org/10.5902/2448190421139.

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In this article we describe the use of the international standard for museum ontologies, CIDOC-CRM, to build a concrete ontology for ME, a virtual museum for the Emigration phenomena. Although the digital document repository is a conventional relational database, more abstract data models should be used to enable conceptual navigation over the information to help end-users (the museum visitors) to extract knowledge from the navigation (the visit). Thus, we will emphasize the design of a Reduced CRM-compatible form to describe the objects of our assets (people that emigrate in some moment to so

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Kević, Karlo, and Ana Kuveždić Divjak. "Open Technologies Supporting Linked Open Data Publishing: Croatian Population Census Case Study." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W13-2025 (July 11, 2025): 157–64. https://doi.org/10.5194/isprs-archives-xlviii-4-w13-2025-157-2025.

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Abstract. Population census data in Croatia is provided in spreadsheet and without explicit geometric representation of its spatial units which makes it not directly usable in spatial analyses and data-based decision-making. This poses challenges for data interoperability and limits practical usefulness of census data. To overcome these limitations, this paper aims to propose ontology mapping schema to structure population contingents by age and sex in RDF and publish it as Linked Open Data using open-source data wrangling tool, OpenRefine. In line with Linked Data best practices, population d

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Araújo, Cristiana Esteves, Ricardo Giuliani Martini, Pedro Rangel Henriques, and José João Almeida. "Building the Museum of the Person from RDF Triples and SPARQL." Revista ComInG - Communications and Innovations Gazette 1, no. 2 (2016): 1. http://dx.doi.org/10.5902/2448190422984.

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Zhao, Chongchong, Chao Dong, and Xiaoming Zhang. "EM3B2 – a semantic integration engine for materials science." Program 50, no. 1 (2016): 58–82. http://dx.doi.org/10.1108/prog-01-2015-0004.

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Purpose – The integration and retrieval of the vast data have attracted sufficient attention, thus the W3C workgroup releases R2RML to standardize the transformation from relational data to semantic-aware data. However, it only provides a data transform mechanism to resource description framework (RDF). The generation of mapping alignments still needs manual work or other algorithms. Therefore, the purpose of this paper is to propose a domain-oriented automatic mapping method and an application of the R2RML standard. Design/methodology/approach – In this paper, materials science is focussed to

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BARBIERI, DAVIDE FRANCESCO, DANIELE BRAGA, STEFANO CERI, EMANUELE DELLA VALLE, and MICHAEL GROSSNIKLAUS. "C-SPARQL: A CONTINUOUS QUERY LANGUAGE FOR RDF DATA STREAMS." International Journal of Semantic Computing 04, no. 01 (2010): 3–25. http://dx.doi.org/10.1142/s1793351x10000936.

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This article defines C-SPARQL, an extension of SPARQL whose distinguishing feature is the support of continuous queries, i.e. queries registered over RDF data streams and then continuously executed. Queries consider windows, i.e. the most recent triples of such streams, observed while data is continuously flowing. Supporting streams in RDF format guarantees interoperability and opens up important applications, in which reasoners can deal with evolving knowledge over time. C-SPARQL is presented by means of a full specification of the syntax, a formal semantics, and a comprehensive set of exampl

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Strong, Mieke, and Piers Higgs. "Mapping between Darwin Core and the Australian Biodiversity Information Standard: A linked data example." Biodiversity Information Science and Standards 7 (September 15, 2023): e112722. https://doi.org/10.3897/biss.7.112722.

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The Australian Biodiversity Information Standard (ABIS) is a data standard that has been developed to represent and exchange biodiversity data expressed using the Resource Description Framework (RDF). ABIS has the TERN ontology at its core, which is a conceptual information model that represents plot-based ecological surveys. The RDF-linked data structure is self-describing, composed of "triples". This format is quite different from tabular data. During the Australian federal government Biodiversity Data Repository pilot project, occurrence data in tabular Darwin Core format was converted into

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Sharma, Kumar, Ujjal Marjit, and Utpal Biswas. "Efficiently Processing and Storing Library Linked Data using Apache Spark and Parquet." Information Technology and Libraries 37, no. 3 (2018): 29–49. http://dx.doi.org/10.6017/ital.v37i3.10177.

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Resource Description Framework (RDF) is a commonly used data model in the Semantic Web environment. Libraries and various other communities have been using the RDF data model to store valuable data after it is extracted from traditional storage systems. However, because of the large volume of the data, processing and storing it is becoming a nightmare for traditional data-management tools. This challenge demands a scalable and distributed system that can manage data in parallel. In this article, a distributed solution is proposed for efficiently processing and storing the large volume of libra

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Li, Pu, Yuncheng Jiang, Ju Wang, and Zhilei Yin. "Semantic Extension of Query for the Linked Data." International Journal on Semantic Web and Information Systems 13, no. 4 (2017): 109–33. http://dx.doi.org/10.4018/ijswis.2017100106.

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With the advent of Big Data Era, users prefer to get knowledge rather than pages from Web. Linked Data, a new form of knowledge representation and publishing described by RDF, can provide a more precise and comprehensible semantic structure to satisfy the aforementioned requirement. Further, the SPARQL query language for RDF is the foundation of many current researches about Linked Data querying. However, these SPARQL-based methods cannot fully express the semantics of the query, so they cannot unleash the potential of Linked Data. To fill this gap, this paper designs a new querying method whi

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Jabbar, Sohail, Farhan Ullah, Shehzad Khalid, Murad Khan, and Kijun Han. "Semantic Interoperability in Heterogeneous IoT Infrastructure for Healthcare." Wireless Communications and Mobile Computing 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/9731806.

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Interoperability remains a significant burden to the developers of Internet of Things’ Systems. This is due to the fact that the IoT devices are highly heterogeneous in terms of underlying communication protocols, data formats, and technologies. Secondly due to lack of worldwide acceptable standards, interoperability tools remain limited. In this paper, we proposed an IoT based Semantic Interoperability Model (IoT-SIM) to provide Semantic Interoperability among heterogeneous IoT devices in healthcare domain. Physicians communicate their patients with heterogeneous IoT devices to monitor their

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Um, Jung-Ho, Seungwoo Lee, Tae-Hong Kim, Chang-Hoo Jeong, Sa-Kwang Song, and Hanmin Jung. "Distributed RDF store for efficient searching billions of triples based on Hadoop." Journal of Supercomputing 72, no. 5 (2016): 1825–40. http://dx.doi.org/10.1007/s11227-016-1670-6.

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Goasdoué, François, Konstantinos Karanasos, Yannis Katsis, Julien Leblay, Ioana Manolescu, and Stamatis Zampetakis. "Growing triples on trees: an XML-RDF hybrid model for annotated documents." VLDB Journal 22, no. 5 (2013): 589–613. http://dx.doi.org/10.1007/s00778-013-0321-2.

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El Guemhioui, Karim, and Steven A. Demurjian. "Semantic Reconciliation of Electronic Health Records Using Semantic Web Technologies." International Journal of Information Technology and Web Engineering 12, no. 2 (2017): 26–48. http://dx.doi.org/10.4018/ijitwe.2017040102.

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In this paper, the authors present an approach to reconcile the semantics of distinct medical terms found in personal health records (PHRs - that store data controlled by patients) and electronic medical records (EMRs - that store data controlled by providers) that are utilized to describe the same concept in different systems. The authors present a solution for semantic reconciliation based on RDF and related semantic web technologies. As part of the solution, the authors utilize a centralized repository of ontologies to: uniformly interrogate the medical coding systems in which those terms a

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Le-Tuan, Anh, Conor Hayes, Manfred Hauswirth, and Danh Le-Phuoc. "Pushing the Scalability of RDF Engines on IoT Edge Devices." Sensors 20, no. 10 (2020): 2788. http://dx.doi.org/10.3390/s20102788.

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Semantic interoperability for the Internet of Things (IoT) is enabled by standards and technologies from the Semantic Web. As recent research suggests a move towards decentralised IoT architectures, we have investigated the scalability and robustness of RDF (Resource Description Framework)engines that can be embedded throughout the architecture, in particular at edge nodes. RDF processing at the edge facilitates the deployment of semantic integration gateways closer to low-level devices. Our focus is on how to enable scalable and robust RDF engines that can operate on lightweight devices. In t

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Komamizu, Takahiro, Toshiyuki Amagasa, and Hiroyuki Kitagawa. "H-SPOOL." International Journal of Web Information Systems 12, no. 3 (2016): 359–78. http://dx.doi.org/10.1108/ijwis-03-2016-0014.

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Purpose Linked data (LD) has promoted publishing information, and links published information. There are increasing number of LD datasets containing numerical data such as statistics. For this reason, analyzing numerical facts on LD has attracted attentions from diverse domains. This paper aims to support analytical processing for LD data. Design/methodology/approach This paper proposes a framework called H-SPOOL which provides series of SPARQL (SPARQL Protocol and RDF Query Language) queries extracting objects and attributes from LD data sets, converts them into star/snowflake schemas and mat

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Tao, Chen, Rongrong Shan, Hui Li, Dongsheng Wang, and Wei Liu. "An Agglomerative-adapted Partition Approach for Large-scale Graphs." International Journal of Librarianship 4, no. 1 (2019): 3. http://dx.doi.org/10.23974/ijol.2019.vol4.1.106.

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In recent years, an increasing number of knowledge bases have been built using linked data, thus datasets have grown substantially. It is neither reasonable to store a large amount of triple data in a single graph, nor appropriate to store RDF in named graphs by class URIs, because many joins can cause performance problems between graphs. This paper presents an agglomerative-adapted approach for large-scale graphs, which is also a bottom-up merging process. The proposed algorithm can partition triples data in three levels: blank nodes, associated nodes, and inference nodes. Regarding blank nod

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Ahn, Jinhyun, Jae-Hong Eom, Sejin Nam, Nansu Zong, Dong-Hyuk Im, and Hong-Gee Kim. "xStore : Federated temporal query processing for large scale RDF triples on a cloud environment." Neurocomputing 256 (September 2017): 5–12. http://dx.doi.org/10.1016/j.neucom.2016.03.116.

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Höffner, Konrad, and Tim Baccaert. "hdt-rs: A Rust library for the Header Dictionary Triples binary RDF compression format." Journal of Open Source Software 8, no. 84 (2023): 5114. http://dx.doi.org/10.21105/joss.05114.

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Vogt, Lars, and Roman Baum. "Using Named Graphs and Knowledge Graph Template Patterns for Efficiently Organizing FAIR Anatomy Data and Metadata." Biodiversity Information Science and Standards 3 (June 19, 2019): e37205. https://doi.org/10.3897/biss.3.37205.

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Currently, morphological data and metadata are still mostly published as unstructured free texts, which lack semantic transparency, cannot be parsed by computers, and do not comply with the FAIR (<u>F</u>indable, <u>A</u>ccessible, <u>I</u>nteroperable, <u>R</u>eusable; Wilkinson et al. (2016) data principles, thus hampering their reuse by non-experts and their integration across many fields in the life sciences. With an ever-increasing amount of available ontologies and the development of adequate semantic technology, however, a solution to this problem becomes available. Instead of free text

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