A Query Approximating Approach Over RDF Graphs

Author(s):  
Ala Djeddai ◽  
Hassina Seridi-Bouchelaghem ◽  
Med Tarek Khadir

Regardless of the knowledge structure lack about Resource Description Framework (RDF) data, difficulties, principally, occur in specifying and answering queries. Approximate querying is the solution to find relevant information by getting a set of sub structures (e.g. sub graphs) matching the query. Approaches based on the structure and others based on semantic, marginalized the common meaning between concepts in its computing. In this paper in order to improve the approximation by introducing the meaning similarity between components in the query and RDF components is proposed, getting better need satisfaction. The meaning similarity measure can be calculated using WordNet and used in all steps of the query answering process. In addition, other important properties in the approximation level calculation between query paths and RDF paths are considered; besides indexing and optimizations strategies are performed. Answers are a set of sub graphs ranked in decreasing order on its matching degree. Experiments are conducted within real RDF dataset.

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Tanvi Chawla ◽  
Girdhari Singh ◽  
Emmanuel S. Pilli

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.


2015 ◽  
Vol 18 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Yevgeny Gryaznov ◽  
Pavel Rusakov

Abstract In this paper authors perform a research on possibilities of RDF (Resource Description Framework) syntaxes usage for information representation in Semantic Web. It is described why pure XML cannot be effectively used for this purpose, and how RDF framework solves this problem. Information is being represented in a form of a directed graph. RDF is only an abstract formal model for information representation and side tools are required in order to write down that information. Such tools are RDF syntaxes – concrete text or binary formats, which prescribe rules for RDF data serialization. Text-based RDF syntaxes can be developed on the existing format basis (XML, JSON) or can be an RDF-specific – designed from scratch to serve the only purpose – to serialize RDF graphs. Authors briefly describe some of the RDF syntaxes (both XML and non-XML) and compare them in order to identify strengths and weaknesses of each version. Serialization and deserialization speed tests using Jena library are made. The results from both analytical and experimental parts of this research are used to develop the recommendations for RDF syntaxes usage and to design a RDF/XML syntax subset, which is intended to simplify the development and raise compatibility of information serialized with this RDF syntax.


Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 34 ◽  
Author(s):  
Maria-Evangelia Papadaki ◽  
Nicolas Spyratos ◽  
Yannis Tzitzikas

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.


2017 ◽  
Vol 1 (2) ◽  
pp. 84-103 ◽  
Author(s):  
Dong Wang ◽  
Lei Zou ◽  
Dongyan Zhao

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 the SPARQL language with spatiotemporal assertions to query spatiotemporal information-integrated RDF data, and design a novel index and the corresponding query algorithm. The experimental results on a large, real RDF graph integrating spatial and temporal information (> 180 million triples) confirm the superiority of our approach. In contrast to its competitors, gst-store outperforms by more than 20%-30% in most cases.


2015 ◽  
Vol 12 (2) ◽  
pp. 104-118 ◽  
Author(s):  
Frank T. Bergmann ◽  
Nicolas Rodriguez ◽  
Nicolas Le Novère

Summary Several standard formats have been proposed that can be used to describe models, simulations, data or other essential information in a consistent fashion. These constitute various separate components required to reproduce a given published scientific result.The Open Modeling EXchange format (OMEX) supports the exchange of all the information necessary for a modeling and simulation experiment in biology. An OMEX file is a ZIP container that includes a manifest file, an optional metadata file, and the files describing the model. The manifest is an XML file listing all files included in the archive and their type. The metadata file provides additional information about the archive and its content. Although any format can be used, we recommend an XML serialization of the Resource Description Framework.Together with the other standard formats from the Computational Modeling in Biology Network (COMBINE), OMEX is the basis of the COMBINE Archive. The content of a COMBINE Archive consists of files encoded in COMBINE standards whenever possible, but may include additional files defined by an Internet Media Type. The COMBINE Archive facilitates the reproduction of modeling and simulation experiments in biology by embedding all the relevant information in one file. Having all the information stored and exchanged at once also helps in building activity logs and audit trails.


2017 ◽  
Vol 44 (2) ◽  
pp. 203-229 ◽  
Author(s):  
Javier D Fernández ◽  
Miguel A Martínez-Prieto ◽  
Pablo de la Fuente Redondo ◽  
Claudio Gutiérrez

The publication of semantic web data, commonly represented in Resource Description Framework (RDF), has experienced outstanding growth over the last few years. Data from all fields of knowledge are shared publicly and interconnected in active initiatives such as Linked Open Data. However, despite the increasing availability of applications managing large-scale RDF information such as RDF stores and reasoning tools, little attention has been given to the structural features emerging in real-world RDF data. Our work addresses this issue by proposing specific metrics to characterise RDF data. We specifically focus on revealing the redundancy of each data set, as well as common structural patterns. We evaluate the proposed metrics on several data sets, which cover a wide range of designs and models. Our findings provide a basis for more efficient RDF data structures, indexes and compressors.


2017 ◽  
Vol 2 (2) ◽  
pp. 41-55 ◽  
Author(s):  
Chunqiu Li ◽  
Shigeo Sugimoto

Abstract Purpose The purpose of this paper is to discuss provenance description of metadata terms and metadata vocabularies as a set of metadata terms. Provenance is crucial information to keep track of changes of metadata terms and metadata vocabularies for their consistent maintenance. Design/methodology/approach The W3C PROV standard for general provenance description and Resource Description Framework (RDF) are adopted as the base models to formally define provenance description for metadata vocabularies. Findings This paper defines a few primitive change types of metadata terms, and a provenance description model of the metadata terms based on the primitive change types. We also provide examples of provenance description in RDF graphs to show the proposed model. Research limitations The model proposed in this paper is defined based on a few primitive relationships (e.g. addition, deletion, and replacement) between pre-version and post-version of a metadata term. The model is simplified and the practical changes of metadata terms can be more complicated than the primitive relationships discussed in the model. Practical implications Formal provenance description of metadata vocabularies can improve maintainability of metadata vocabularies over time. Conventional maintenance of metadata terms is the maintenance of documents of terms. The proposed model enables effective and automated tracking of change history of metadata vocabularies using simple formal description scheme defined based on widely-used standards. Originality/value Changes in metadata vocabularies may cause inconsistencies in the longterm use of metadata. This paper proposes a simple and formal scheme of provenance description of metadata vocabularies. The proposed model works as the basis of automated maintenance of metadata terms and their vocabularies and is applicable to various types of changes.


Author(s):  
Zongmin Ma ◽  
Li Yan

The resource description framework (RDF) is a model for representing information resources on the web. With the widespread acceptance of RDF as the de-facto standard recommended by W3C (World Wide Web Consortium) for the representation and exchange of information on the web, a huge amount of RDF data is being proliferated and becoming available. So, RDF data management is of increasing importance and has attracted attention in the database community as well as the Semantic Web community. Currently, much work has been devoted to propose different solutions to store large-scale RDF data efficiently. In order to manage massive RDF data, NoSQL (not only SQL) databases have been used for scalable RDF data store. This chapter focuses on using various NoSQL databases to store massive RDF data. An up-to-date overview of the current state of the art in RDF data storage in NoSQL databases is provided. The chapter aims at suggestions for future research.


Author(s):  
Zongmin Ma ◽  
Li Yan

The Resource Description Framework (RDF) is a model for representing information resources on the Web. With the widespread acceptance of RDF as the de-facto standard recommended by W3C (World Wide Web Consortium) for the representation and exchange of information on the Web, a huge amount of RDF data is being proliferated and becoming available. So RDF data management is of increasing importance, and has attracted attentions in the database community as well as the Semantic Web community. Currently much work has been devoted to propose different solutions to store large-scale RDF data efficiently. In order to manage massive RDF data, NoSQL (“not only SQL”) databases have been used for scalable RDF data store. This chapter focuses on using various NoSQL databases to store massive RDF data. An up-to-date overview of the current state of the art in RDF data storage in NoSQL databases is provided. The chapter aims at suggestions for future research.


Author(s):  
Hatem Soliman ◽  
Izhar Ahmed Khan ◽  
Yasir Hussain

The resource description framework (RDF) was adopted by the World Wide Web (W3C) as an essential semantic web standard and the RDF scheme. It accords the hard semantics in the description and wields the crisp metadata. However, it usually produces vague or ambiguous information. Consequently, fuzzy RDF helps deal with such special data by transforming the crisp values into a fuzzy set. A method for analyzing fuzzy RDF data is proposed in this paper. To this end, first, we decompose the RDF into fuzzy RDF variables. Second, we are designing a model for global sensitivity analysis based on the decomposition of fuzzy RDF. It figures out the ambiguities of fuzzy RDF data. The proposed global sensitivity analysis model provides the importance of fuzzy RDF data by considering the response function’s structure and reselects it to a certain degree. A practical tool for sensitivity analysis of fuzzy RDF data has also been implemented based on the proposed model.


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