OLAP for Multidimensional Semantic Web Databases

Matei, Adriana; Chao, Kuo‐Ming; Godwin, Nick

doi:10.1007/978-3-662-46839-5_6

Cited by 17 publications

(8 citation statements)

References 8 publications

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“…However, the work [1,2] only describes general principles and research orientations. The authors of [28] propose IGOLAP vocabulary allowing representing multisource data according to a multidimensional structure. However, the compatibility of the work [28] is limited to LOD datasets.…”

Section: Related Workmentioning

confidence: 99%

“…The authors of [28] propose IGOLAP vocabulary allowing representing multisource data according to a multidimensional structure. However, the compatibility of the work [28] is limited to LOD datasets. To deal with warehoused data, the authors suggest (i) transforming them into LOD formats through a mapping language proposed in [25] and (ii) loading large amounts of transformed data into a IGOLAP dataset.…”

Section: Related Workmentioning

confidence: 99%

“…To deal with warehoused data, the authors suggest (i) transforming them into LOD formats through a mapping language proposed in [25] and (ii) loading large amounts of transformed data into a IGOLAP dataset. Consequently, the work [28] faces the same problems of the ETL-based work. Moreover, the feasibility of unifying multisource data in a IGO-LAP dataset is only discussed without being experimentally assessed.…”

Section: Related Workmentioning

confidence: 99%

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A Unified Approach to Multisource Data Analyses

Ravat

Song

2018

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Classically, Data Warehouses (DWs) supports business analyses on data coming from the inside of an organization. Nevertheless, Lined Open Data (LOD) might sensibly complete these business analyses by providing complementary perspectives during a decision-making process. In this paper, we propose a conceptual modeling solution, named Unified Cube, which blends together multidimensional data from DWs and LOD datasets without materializing them in a stationary repository. We complete the conceptual modeling with an implementation framework which manages the relations between a Unified Cube and multiple data sources at both schema and instance levels. We also propose an analysis processing process which queries different sources in a transparent way to decision-makers. The practical value of our proposal is illustrated through real-world data and benchmarks.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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A Unified Approach to Multisource Data Analyses

Ravat

Song

2018

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“…Les auteurs de (Abelló et al, 2013) discutent des défis et des perspectives de recherche pour fusionner les données à partir de sources multiples, mais des propositions concrètes manquent. Les travaux de (Matei et al, 2015)…”

Section: éTat De L'artunclassified

Vers un modèle unifié de données entreposées et de données ouvertes liées. Concepts et expérimentations

Ravat¹,

Song²,

Teste³

2017

isi

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De nos jours, la plupart des systèmes d'aide à la décision (SAD) reposent sur un entrepôt de données (ED) construit à partir de données de production internes à l'organisation. Cependant, les analyses décisionnelles peuvent être sensiblement améliorées par l'ajout d'informations supplémentaires provenant de l'extérieur d'une organisation, notamment des données ouvertes liées (DOL). L'intégration de ces données dans un SAD peut offrir de nouveaux points de vue aux décideurs. Dans cet article, nous décrivons un nouveau modèle multidimensionnel, appelé Cube Unifié, qui offre une représentation conceptuelle générique des données entreposées et des DOL. Un processus en deux étapes est proposé pour construire un Cube Unifié. Dans un premier temps, les schémas publiés avec des langages de modélisation spécifiques sont transformés en une représentation conceptuelle reposant sur un même langage. La seconde étape consiste à associer les schémas précédemment définis pour former un schéma unifié. Un langage algébrique est proposé afin de permettre aux concepteurs de construire un Cube Unifié selon leurs besoins. Pour valider nos propositions, nous montrons comment un Cube Unifié 1) est construit sur des jeux de données réelles et 2) permet aux décideurs d'effectuer des analyses décisionnelles avec de multiples sources. ABSTRACT. Nowadays, most Decision Support Systems (DSS) rely on a Data Warehouse (DW) built with internal data sources. However, business analyses can be significantly enhanced by including complementary information coming from the outside of an organization, especially Linked Open Data (LOD). Integrating these data in a DSS can offer multiple perspectives to decision-makers. This paper provides a new multidimensional model, named Unified Cube, which offers a generic representation of both warehoused data and LOD at the conceptual level. A two-stage process is proposed to build a Unified Cube according to decision-makers' needs. As a first step, schemas published with specific modeling languages are transformed into a common conceptual representation based on a generic modeling language. The second step is to associate together all schemas obtained after the first step to form a Unified Cube containing all useful information about an analysis subject. A high-level declarative language is provided to enable designers to build a Unified Cube according to their needs. To demonstrate the feasibility of the proposed concepts, we show how a Unified Cube 1) is built from reel-world datasets and 2) enables decision-makers to carry out business analyses with multiple data sources. MOTS-CLÉS : données ouvertes liées, entrepôt de données, analyse multidimensionnelle.

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“…In [4], the authors propose the QB4OLAP vocabulary which adds more multidimensional characteristics to QB, like multiple analytical granularities within multiple aggregation paths and the specification of the aggregation functions associated to a measure. [8] proposes IGOLAP vocabulary allowing representing the correlation relationships between two different dimensions. QB, QB4OLAP and IGOLAP are logical models expressed in RDF vocabularies.…”

mentioning

confidence: 99%

Unifying Warehoused Data with Linked Open Data: A Conceptual Modeling Solution

Ravat

Song

2016

Model and Data Engineering

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 17173The contribution was presented at MEDI 2016 :http://indalog.ual.es/MEDI2016/HOME.html IntroductionIn today's highly dynamic business context, decision-makers should access internal and external sources to obtain an overall perspective over an organization [2]. Data Warehouses (DWs) have been widely used as internal sources to support online, interactive analyses, while Linked Open Data (LOD) 1 have become one of the most important external information sources allowing enhancing business analyses on a web scale [12]. However, warehoused data and LOD follow different models in each domain, which makes it difficult to analyze both types of data in a unified way. Moreover, dispersion of related data in different schemas results in repetitive searches for relevant information in different sources, which reduces the efficiency of analysis.Motivating example. In a company selling home appliances, a decision-maker looks up in an internal R-OLAP DW to assess the performance of sales staff. The DW relates to an analysis subject (i.e. fact), named Sales Analysis, which contains a set of numeric indicators (i.e. measures), namely unit price and quantity. Each measure can be computed according to three analysis axes (i.e. dimensions): salesman, product and time (cf. figure 1(a)). The R-OLAP DW alone does not provide enough information to support effective and well-informed decisions. The decision-maker must 1 http://linkeddata.org search for additional information to obtain other complementary perspectives over the sales activities. Since the sales of some home appliances (e.g., heaters) are strongly influenced by the climate changes, the decision-maker browses in an online dataset denoted LOD1 revealing the monthly average temperature according to countries. The LOD are published in RDF Data Cube Vocabulary (QB) 2 format, which is the current W3C standard to publish multidimensional statistical data. Moreover, since retail sales may compete with the company's promotions in the same catchment area, the decision-maker consults another online dataset denoted LOD2 about the outlet prices offered by rival retailers. The LOD2 dataset is published in QB4OLAP, it involves the retail price for a class (i.e., type) of merchandise offered by a retailers' shop. Extracts of the LOD datasets in tabular form are available in figure 1(b) and (c). Without a comprehensive representation of related data, analyses involving several sources are carried out in a sequential way. Decision-makers must explore all data sources one after another before obtaining an overall vision on an analysis subject. Carrying out such analyses is inefficient and difficult, because all schemas do not include the same information at the same analytical granularities: (a) the same analysis axes present in different sources may in...

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OLAP for Multidimensional Semantic Web Databases

Cited by 17 publications

References 8 publications

A Unified Approach to Multisource Data Analyses

A Unified Approach to Multisource Data Analyses

Vers un modèle unifié de données entreposées et de données ouvertes liées. Concepts et expérimentations

Unifying Warehoused Data with Linked Open Data: A Conceptual Modeling Solution

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