AGGREGATE QUERY PROCESSING FOR SEMANTIC WEB DATABASES: AN ALGEBRAIC APPROACH

As a growing number of applications represent data as semantic graphs like RDF (Resource Description Format) and the many entity-attribute-value formats, query languages for such data are being required to support operations beyond graph pattern matching and inference queries. Specifically the ability to express aggregate queries is an important feature which is either lacking or is implemented with little attention to the peculiarities of the data model. In this paper, we study the meaning and implementation of grouping and aggregate queries over RDF graphs. We first define grouping and aggregate operators algebraically and then show how the SPARQL query language can be extended to express grouping and aggregate queries.

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Towards Interactive Analytics over RDF Graphs

Algorithms ◽

10.3390/a14020034 ◽

2021 ◽

Vol 14 (2) ◽

pp. 34 ◽

Cited By ~ 1

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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gst-store: Querying Large Spatiotemporal RDF Graphs

Data and Information Management ◽

10.1515/dim-2017-0008 ◽

2017 ◽

Vol 1 (2) ◽

pp. 84-103 ◽

Cited By ~ 2

Author(s):

Dong Wang ◽

Lei Zou ◽

Dongyan Zhao

Keyword(s):

Query Language ◽

Data Management System ◽

Rdf Graph ◽

Spatiotemporal Information ◽

Simple Protocol ◽

Rdf Data ◽

Description Framework ◽

Query Algorithm ◽

Rdf Graphs ◽

Resource Description

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.

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VP-RDF: An RDF Based Framework to Introduce the Viewpoint in the Description of Resources

Applied Computer Systems ◽

10.2478/acss-2021-0006 ◽

2021 ◽

Vol 26 (1) ◽

pp. 44-53

Author(s):

Ouahiba Djama

Keyword(s):

Resource Description Framework ◽

Intelligent Systems ◽

Query Languages ◽

View Point ◽

Share Data ◽

Common Framework ◽

Description Framework ◽

Rdf Graphs ◽

Resource Description ◽

The Web

Abstract The description of resources and their relationships is an essential task on the web. Generally, the web users do not share the same interests and viewpoints. Each user wants that the web provides data and information according to their interests and specialty. The existing query languages, which allow querying data on the web, cannot take into consideration the viewpoint of the user. We propose introducing the viewpoint in the description of the resources. The Resource Description Framework (RDF) represents a common framework to share data and describe resources. In this study, we aim at introducing the notion of the viewpoint in the RDF. Therefore, we propose a View-Point Resource Description Framework (VP-RDF) as an extension of RDF by adding new elements. The existing query languages (e.g., SPARQL) can query the VP-RDF graphs and provide the user with data and information according to their interests and specialty. Therefore, VP-RDF can be useful in intelligent systems on the web.

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Algebraic Operations on Spatiotemporal Data Based on RDF

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9020080 ◽

2020 ◽

Vol 9 (2) ◽

pp. 80

Author(s):

Lin Zhu ◽

Nan Li ◽

Luyi Bai

Keyword(s):

Algebraic Approach ◽

Spatiotemporal Data ◽

Graph Algebras ◽

Graph Pattern ◽

Data Querying ◽

Filter Operation ◽

Algebraic Operations ◽

Description Framework ◽

Rdf Graphs ◽

Filter Rules

In the context of the Semantic Web, the Resource Description Framework (RDF), a language proposed by W3C, has been used for conceptual description, data modeling, and data querying. The algebraic approach has been proven to be an effective way to process queries, and algebraic operations in RDF have been investigated extensively. However, the study of spatiotemporal RDF algebra has just started and still needs further attention. This paper aims to explore an algebraic operational framework to represent the content of spatiotemporal data and support RDF graphs. To accomplish our study, we defined a spatiotemporal data model based on RDF. On this basis, the spatiotemporal semantics and the spatiotemporal algebraic operations were investigated. We defined five types of graph algebras, and, in particular, the filter operation can filter the spatiotemporal graphs using a graph pattern. Besides this, we put forward a spatiotemporal RDF syntax specification to help users browse, query, and reason with spatiotemporal RDF graphs. The syntax specification illustrates the filter rules, which contribute to capturing the spatiotemporal RDF semantics and provide a number of advanced functions for building data queries.

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An SQL-Based Query Language and Engine for Graph Pattern Matching

Graph Transformation - Lecture Notes in Computer Science ◽

10.1007/978-3-319-40530-8_10 ◽

2016 ◽

pp. 153-169 ◽

Cited By ~ 5

Author(s):

Christian Krause ◽

Daniel Johannsen ◽

Radwan Deeb ◽

Kai-Uwe Sattler ◽

David Knacker ◽

...

Keyword(s):

Pattern Matching ◽

Query Language ◽

Graph Pattern Matching ◽

Graph Pattern

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Multi-Fuzzy-Objective Graph Pattern Matching with Big Graph Data

Journal of Database Management ◽

10.4018/jdm.2019100102 ◽

2019 ◽

Vol 30 (4) ◽

pp. 24-40

Author(s):

Lei Li ◽

Fang Zhang ◽

Guanfeng Liu

Keyword(s):

Pattern Matching ◽

Particle Swarm Optimization Algorithm ◽

Nsga Ii ◽

Specific Domain ◽

Graph Pattern Matching ◽

Graph Data ◽

Graph Pattern ◽

Big Graph ◽

Complex Relationships ◽

Pattern Graph

Big graph data is different from traditional data and they usually contain complex relationships and multiple attributes. With the help of graph pattern matching, a pattern graph can be designed, satisfying special personal requirements and locate the subgraphs which match the required pattern. Then, how to locate a graph pattern with better attribute values in the big graph effectively and efficiently becomes a key problem to analyze and deal with big graph data, especially for a specific domain. This article introduces fuzziness into graph pattern matching. Then, a genetic algorithm, specifically an NSGA-II algorithm, and a particle swarm optimization algorithm are adopted for multi-fuzzy-objective optimization. Experimental results show that the proposed approaches outperform the existing approaches effectively.

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