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The practical implementation of the principle of optimisation of radiological protection (i.e., ALARA principle) was the subject of two workshops organised in Paris (France) in February 2017 and October 2018 at the initiative of SFRP within the framework of IRPA. The article summarizes the discussions and conclusions of these two workshops. The search for reasonableness was examined in three sectors: nuclear industry, medical practices and existing exposure situations. In all sectors, the optimisation remains a challenge and experience shows that this is implemented through a deliberative process to achieve a reasonable compromise with all informed parties. This issue was further investigated by three working groups − one for each sector – on the basis of cases studies. It emerges that, in complement to the use of classical tools such as cost-benefit analysis, the implementation of the optimisation principle implies a clear identification of the challenges to be met in order to achieve the best protection in the prevailing circumstances. These challenges may be specific to a type of exposure situation and in some cases to a given situation. The process should also well identify the relevant stakeholders and decision-makers to be involved and determine how they will be involved. A proactive process including development of awareness, empowerment and/or training may be needed. This reflexion deserves to be further developed. more...

International audience; When querying Knowledge Bases (KBs), users are faced with large sets of data, often without knowing their underlying structures. It follows that users may make mistakes when formulating their queries, therefore receiving an unhelpful response. In this paper, we address the plethoric answers problem, the situation where a query produces significantly more results than the user was expecting.We deal with this problem by identifying the parts of the failing query, called Minimal Failure Inducing Subqueries (MFIS), that cause plethoric answers. As long as the query contains an MFIS, it will fail to reach a sufficiently low amount of answers. Thanks to these MFIS, interactive and automatic approaches can be set up to help the user reformulate their query. The dual notion of MFIS, maXimal Succeeding Subqueries (XSS), is also useful. They are queries with the most parts of the original query that return non plethoric answers. Our goal is to compute MFIS and XSS efficiently, so that they may be used to solve the plethoric answers problem. We propose two algorithms that leverage query and data properties to compute MFIS and XSS. We show experimentally that our algorithms clearly outperform a baseline method on generated queries as well as real user-submitted~queries. more...

Evaluating the quality of resources and the reliability of entities in a system is one of the current needs of modern computer systems. This assessment is the result of two concepts that dominate our real life as well as computer systems, which are Trust and Reputation. To measure them, a variety of computational models have been developed to help users make decisions, and to improve interactions with the system and between users. Due to the wide variety of definitions for reputation and trust topics, this paper attempts to unify these definitions by proposing a unique formalization in terms of graphical and textual notations. It introduces also a deep analysis to understand the behavior and the intuition behind each computational model. more...

International audience

A large number of applications such as sensor networks, RFID-based monitoring systems, mobile object management and location-based services manage data pervaded with uncertainty. Usually, users wish/prefer high quality results (i.e. with highest certainty) when they pose queries with strict conditions over these data. However, as they may not be clear about the contents of the databases that contain such data, these queries may be failing i.e., they may return no result or results that do not satisfy the expected level of certainty. In this case, users may try to change manually the query conditions to obtain approximate answers. Due to the exponential combination number of query conditions, this procedure results in a time-consuming and frustrating task. In this paper, we address the failing queries problem by proposing an approach that identifies the query parts, called Minimal Failing Subqueries (MFSs), that are responsible for its failure. Thanks to these MFSs, interactive and automatic approaches can be set up to help the user reformulating her/his query. We also compute, in the same time, a set of Maximal Succeeding Subqueries (XSSs) that represents a list of non failing queries with a maximal number of predicates of the initial query. The results of these XSSs constitute good alternative answers that can be returned to the user instead of an empty result. To demonstrate the efficiency and the effectiveness of our proposal, a set of experiments have been conducted with synthetic and real datasets. A comparison with baseline and related work approaches shows the interest of our proposal. more...

Several large uncertain knowledge bases (KBs) are available on the Web where facts are associated with a certainty degree. When querying these uncertain KBs, users seek high-quality results, i.e., results that have a certainty degree greater than a given threshold $$\alpha $$ . However, as they usually have only a partial knowledge of the KB contents, their queries may be failing i.e., they return no result for the desired certainty level. To prevent this frustrating situation, instead of returning an empty set of answers, our approach explains the reasons of the failure with a set of $$\alpha $$ minimal failing subqueries ( $$\alpha $$ MFSs) and computes alternative relaxed queries, called $$\alpha $$ maXimal succeeding subqueries ( $$\alpha $$ XSSs), that are as close as possible to the initial failing query. Moreover, as the user may not always be able to provide an appropriate threshold $$\alpha $$ , we propose three algorithms to compute the $$\alpha $$ MFSs and $$\alpha $$ XSSs for other thresholds, which also constitutes a relevant feedback for the user. Multiple experiments with the WatDiv benchmark show the relevance of our algorithms compared to a baseline method. more...

International audience; In many real applications, data are intrinsically uncertain due to measurement errors, interpretability issues, information incompleteness, etc. In those uncertain databases, users usually express quality requirements when the system evaluates their queries. However, as they may not be familiar with the contents of the queried database, their queries may be failing i.e., they may return no results or results that do not satisfy the expected degree of certainty. To provide users with relevant information in order to obtain alternative satisfactory results, we introduce a cooperative approach based on the dualization concept. This approach computes a set of meaningful subqueries (MFSs and XSSs) of the initial failing query, which is of paramount importance for query reformulation and relaxation purposes. The conducted experiments show that our proposition, a Mixed Dualization Matrix-Based approach (MDMB), outperforms existing algorithms, especially for large queries. more...

Requirements engineering plays a crucial role in the development process of an information system as it aims at providing a complete and accurate requirement specification. In the life cycle of a Data Repository (\({\mathcal {D}}{\mathcal {R}}\)) such as a database or a data warehouse, the requirements are mainly used to define the conceptual model once they have been identified from the informal specification. In this paper, we study the interest of requirements in the other phases of the \({\mathcal {D}}{\mathcal {R}}\) life cycle. As the data integration problem, handled in the Extract, Transform, Load (ETL) phase, comes from the heterogeneity of requirements, we introduce a requirement integration framework based on ontologies and a generic model to unify the used vocabularies and requirement languages. Then we propose an approach to check the consistency of the requirements, w.r.t. the integrity constraints defined on the logical schema using the formal B method. We also show that requirements help define appropriate access structures such as indexes and materialized views to optimize SQL queries of a \({\mathcal {D}}{\mathcal {R}}\). Our approach is based on transformation rules that identify important queries that will be executed on a \({\mathcal {D}}{\mathcal {R}}\) directly from the requirements. The experiments conducted on the Star Schema Benchmark (SSB) confirm the interest of this approach for the selection of different optimization structures. Finally, we present the OntoReqTool that implements the previous functionality on top of the OntoDB/OntoQL platform. more...

International audience; Ontologies have been increasingly used over the past few decades in a wide range of application domains spanning both academic and industrial communities. As ontologies are the cornerstone of the Semantic Web, the technologies developed in this context, including ontology languages, specialized databases and query languages, have become widely used. However, the expressiveness of the proposed ontology languages does not always cover the needs of specific domains. For instance, engineering is a domain for which the LIAS laboratory has proposed dedicated solutions with a worldwide recognition. The underlying assumptions made in the context of the Semantic Web, an open and distributed environment, do not apply to the controlled environments of our projects where the correctness and completeness of modeling can be guaranteed to a certain degree. As a consequence, we have developed over the last decades a specialized standard ontology language named PLIB associated with the OntoDB/OntoQL platform to manage ontological engineering data within a database. The goal of this paper is threefold: (1) to share our experience in manipulating ontologies in the engineering domain by describing their specificities and constraints; (2) to define a comprehensive classification of ontologies with respect to three main research communities: Artificial Intelligence, Databases and Natural Language Processing and (3) to present a persistent solution, called OntoDB, for managing extremely large semantic data sets associated with an ontological query language, called OntoQL. These objectives are illustrated by several examples that show the effectiveness and interest of our propositions in several industrial projects in different domains including vehicle manufacturing and CO2 storage. more...

In the last few years, research on database and information system technologies has been rapidly evolving thanks to the new paradigms of software and hardware adopted by modern scientific and more invasive applications. A huge and heterogeneous amount of data should be efficiently stored, managed, and analyzed exploiting proper technologies for such novel and more interesting data-driven applications. New and cutting-edge research challenges arise that have been attracting great attention from both academia and industry. The 21st European Conference on Advances in Databases and Information Systems (ADBIS 2017), held on September 24–27, 2017 in Nicosia, Cyprus includes four thematic workshops covering some emerging issues concerning such new trends in database and information system research. The aim of this paper is to present such events, their motivations and topics of interest, as well as briefly outline their programs including interesting keynotes, invited papers and a wide range of research, application, and industrial contributions selected for presentations. The selected papers have been included in this volume. more...

Software Product Lines (SPL) based on reuse, claim to improve evolution, time to market and decrease software development costs. Concrete software products or systems, members of the SPL family, are derived by instantiating a generic Reference Architecture (RA) , holding common and variant components. The construction of RA is a complex and costly task, as well as its usage for product derivation, due to the huge number of variants, essentially caused by non functional requirements variability. In consequence, the selection of an RA instance or Feasible Solution (FS) , meeting RA constraints and customer requirements, is not straightforward. In this work RA is built by a bottom-up process from existing products; RA and its instances are represented by a non-directed connected graph. The HIS-RA Ontology also represents RA and captures Healthcare Integrated Information Systems (HIS) domain knowledge. Moreover, FS must be connected (the induced graph by FS in RA has no isolated components), consistent (it verifies consistency rules among FS components), and working (it meets domain functional (FR) and non functional (NFR) requirements). The main goal of this paper is to define a semiautomatic process (FFSP) , to derive consistency rules using the HIS-RA Ontology built-in reasoning capabilities, to construct consistent, connected and working FS. Software quality is considered by FFSP in the traceability between FR and NFR, and it is specified by ISO/IEC 25010, to guarantee RA evolution and the overall concrete product configuration quality. FFSP is validated on a HIS domain a case study. more...

Recent years have witnessed the development of large knowledge bases (KBs). Due to the lack of information about the content and schema semantics of KBs, users are often not able to correctly formulate KB queries that return the intended result. In this paper, we consider the problem of failing RDF queries, i.e., queries that return an empty set of answers. Query relaxation is one cooperative technique proposed to solve this problem. In the context of RDF data, several works proposed query relaxation operators and ranking models for relaxed queries. But none of them tried to find the causes of an RDF query failure given by Minimal Failing Subqueries (MFSs) as well as successful queries that have a maximal number of triple patterns named Ma$$\underline{x}$$x?imal Succeeding Subqueries (XSSs). Inspired by previous work in the context of relational databases and recommender systems, we propose two complementary approaches to fill this gap. The lattice-based approach (LBA) leverages the theoretical properties of MFSs and XSSs to efficiently explore the subquery lattice of the failing query. The matrix-based approach computes a matrix that records alternative answers to the failing query with the triple patterns they satisfy. The skyline of this matrix directly gives the XSSs of the failing query. This matrix can also be used as an index to improve the performance of LBA. The practical interest of these two approaches are shown via a set of experiments conducted on the LUBM benchmark and a comparative study with baseline and related work algorithms. more...

Recent advances in Web-information extraction have led to the creation of several large Knowledge Bases KBs. Querying these KBs often results in empty answers that do not serve the users' needs. Relaxation of the failing queries is one of the cooperative techniques used to retrieve alternative results. Most of the previous work on RDF query relaxation compute a set of relaxed queries and execute them in a similarity-based ranking order. Thus, these approaches relax an RDF query without knowing its failure causesFCs. In this paper, we study the idea of identifying these FCs to speed up the query relaxation process. We propose three relaxation strategies based on various information levels about the FCs of the user query and of its relaxed queries as well. A set of experiments conducted on the LUBM benchmark show the impact of our proposal in comparison with a state-of-the-art algorithm. more...

International audience; Ontologies are used in several application domains for representing knowledge. The defined approaches differ according to the type of addressed ontology (conceptual or linguistic) and to the used ontology model (e.g. OWL or PLIB). Several languages have been proposed to manipulate ontologies and their instances, especially in the Semantic Web domain. However these languages are often specific to a given ontology model, they focus on conceptual ontologies and they are not compatible with database exploitation languages. We address these three problems in this paper by proposing the OntoQL language. This language has three main original characteristics: (1) OntoQL is based on a core ontology model composed of the shared constructors of ontology models. This core ontology model can be extended by the language itself, (2) OntoQL queries can be expressed with different natural languages features using the linguistic layer of an ontology, and (3) OntoQL is fully compatible with SQL enabling a smooth integration between SQL queries of classical database applications and ontological queries. As a theoretical validation of this language, we present the algebra of operators that sets up its formal semantics. On the operational side, we describe the implementation of OntoQL on the OntoDB database and we illustrate the interest of this language by reporting several applications where this language has been extensively used and proved powerful. more...

The evolution of computer technology has strongly impacted the database design. No phase was spared: several conceptual formalisms e.g. ER, UML, ontological, various logical models e.g. relational, object, key-value, a wide panoply of physical optimization structures and deployment platforms have been proposed. As a result, the database design process has become more complex involving more tasks and even more actors as database architect or analyst. Getting inspired from software engineering in dealing with variable similar systems, we propose a methodological framework for a variability-aware design of databases, whereby this latter is henceforth devised as a Software Product Line. Doing so guarantees a high reuse, automation, and customizability in generating ready-to-be implemented databases. We also propose a solution to help users make a suitable choice among the wide panoply. Finally, a case study is presented. more...

This paper addresses the problem of failing $$\mathtt {RDF}$$ queries. Query relaxation is one of the cooperative techniques that allows providing users with alternative answers instead of an empty result. While previous works on query relaxation over $$\mathtt {RDF}$$ data have focused on defining new relaxation operators, we investigate in this paper techniques to find the parts of an $$\mathtt {RDF}$$ query that are responsible of its failure. Finding such subqueries, named Minimal Failing Subqueries$$\mathtt {MFSs}$$, is of great interest to efficiently perform the relaxation process. We propose two algorithmic approaches for computing $$\mathtt {MFSs}$$. The first approach $$\mathtt {LBA}$$ intelligently leverages the subquery lattice of the initial $$\mathtt {RDF}$$ query while the second approach $$\mathtt {MBA}$$ is based on a particular matrix that improves the performance of $$\mathtt {LBA}$$. Our approaches also compute a particular kind of relaxed RDF queries, called Maximal Succeeding Subqueries$$\mathtt {XSSs}$$. $$\mathtt {XSSs}$$ are subqueries with a maximal number of triple patterns of the initial query. To validate our approaches, a set of thorough experiments is conducted on the $$\mathtt {LUBM}$$ benchmark and a comparative study with other approaches is done. more...

Data warehouses (\(\mathcal{D}\mathcal{W}\)) are defined as data integration systems constructed from a set of heterogeneous sources and user’s requirements. Heterogeneity is due to syntactic and semantic conflicts occurring between used concepts. Existing \(\mathcal{D}\mathcal{W}\) design methods associate heterogeneity only to data sources. We claim in this paper that heterogeneity is also associated to users’ requirements. Actually, requirements are collected from heterogeneous target users, which can cause semantic conflicts between concepts expressed. Besides, requirements can be analyzed by heterogeneous designers having different design skills, which can cause formalism heterogeneity. Integration is the process that manages heterogeneity in \(\mathcal{D}\mathcal{W}\) design. Ontologies are recognized as the key solution for ensuring an automatic integration process. We propose to extend the use of ontologies to resolve conflicts between requirements. A pivot model is proposed for integrating requirements schemas expressed in different formalisms. A \(\mathcal{D}\mathcal{W}\) design method is proposed for providing the target \(\mathcal{D}\mathcal{W}\) schema (star or snowflake schema) that meets a uniformed and consistent set of requirements. more...

Requirements engineering aims at providing a requirement specification with some nice properties such as completeness or accuracy. In the lifecycle of a Data Repository (\(\mathcal{D}\mathcal{R}\)), user requirements are usually assumed to be homogenous and used mainly to define the conceptual model of a \(\mathcal{D}\mathcal{R}\). In this paper, we study the interest of the requirements in the other phases of the life cycle of a \(\mathcal{D}\mathcal{R}\). We propose a generic model based on ontologies to unify the used vocabularies and requirements languages. Then we extend this model using the formal method B to check the consistency of the requirements w.r.t. the integrity constraints defined on the logical schema. Finally we propose to select optimization structures of a \(\mathcal{D}\mathcal{R}\) using the user requirements instead of SQL queries. Several experiments on the Star Schema Benchmark (SSB) confirm the interest of our proposition. more...

With the extensive use of ontologies in various domains, Semantic Web Databases (\(\mathcal{SWDB}s\)) have appeared in the database landscape. Materialized views are one of the most popular optimization structures in advanced databases. Queries represent the most important input of the problem of selecting materialized views. In the context of \(\mathcal{SWDB}\), queries are expressed using the SPARQL language. A SPARQL query consists of a set of triple patterns executed on a set of triples representing the logical level of the \(\mathcal{SWDB}\). But a \(\mathcal{SWDB}\) may have several deployments according to the used storage layout (vertical, horizontal, binary). As a consequence the process of selecting materialized views has to consider this diversity. In this paper, we first present the difficulty of the process of materializing views in the context of \(\mathcal{SWDB}\) considering the diversity of storage layouts. Secondly, we define two approaches to select materialized views. The first approach hides the implementation aspects and views are selected at the ontological level using a rule-based approach. In the second approach, views are selected at the logical level and the view selection is guided by a cost model which considers the diverse storage layouts that can be used. Finally, intensive experiments are conducted by the means of the Lehigh University Benchmark and we empirically compare our finding with state-of-the-art algorithms. more...

Most of studies on relaxing Semantic Web Database (\(\mathcal{S}\mathcal{W}\mathcal{D}\mathcal{B}\)) queries focus on developing new relaxation techniques or on optimizing the top-k query processing. However, only few works have been conducted to provide a fine and declarative control of query relaxation using an \(\mathcal{S}\mathcal{W}\mathcal{D}\mathcal{B}\) query language. In this paper we first define a set of requirements for an \(\mathcal{S}\mathcal{W}\mathcal{D}\mathcal{B}\) cooperative query language(\(\mathcal{C}\mathcal{Q}\mathcal{L}\)). Then, based on these requirements, we propose an extension of query language with a new clause to use and combine the relaxation operators we introduce. A similarity function is associated with these operators to rank the alternative answers retrieved. more...

As any product design, data warehouse applications follow a well-known life-cycle. Historically, it included only the physical phase, and had been gradually extended to include the conceptual and the logical phases. The management of phases either internally or intranally is dominated by rule-based approaches. More recently, a cost-based approach has been proposed to substitute rule-based approaches in the physical design phase in order to optimize queries. Unlike the traditional rule-based approach, it explores a huge search space of solutions (e.g., query execution plans), and then based on a cost-model, it selects the most suitable one(s). On the other hand, the logical design phase is still managed by rule-based approaches applied on the conceptual schema. In this paper, we propose to propagate the cost-based vision on the logical phase. As a consequence, the selection of a logical design of a given data warehouse schema becomes an optimization problem with a huge space search generated thanks to correlations (e.g. hierarchies) between data warehouse concepts. By the means of a cost model estimating the overall query processing cost, the best logical schema is selected. Finally, a case study using the Star Schema Benchmark is presented to show the effectiveness of our proposal. more...

International audience; Model persistence has always been one of the major interests of the model-driven development community. In this context, Persistent Meta-Modeling Systems (PMMS) have been proposed as database environments dedicated to meta-modeling and model management. Yet, if existing PMMS store meta-models, models and instances, they provide mechanisms that are sometimes insufficient to accomplish some advanced model management tasks like model transformation or model analysis. In this paper we validate the work achieved in [5] by exploiting the support of user-defined operations in PMMS in order to perform model transformations and model analysis. more...

International audience; Recently, ontologies have been widely adopted by small, medium and large companies in various domains. These ontologies may contain redundant concepts (computed from primitive concepts). At the beginning of the development of ontologies, the relationship between them and the database was weakly coupled. With the explosion of semantic data, persistent solutions to ensure a high performance of applications were proposed. As a consequence, a new type of database, called semantic database (SDB) is born. Several types of SDB have been proposed and supported by different DBMS, where each one has its architecture and its storage layouts for ontologies and its instances. At this stage, relationship between databases and ontologies becomes strongly coupled. As a consequence, several research studies were proposed on the physical design phase of SDB. To guarantee the similar success that relational databases got, SDB has to be supported by complete design methodologies and tools including the different steps of the database life cycle. Such methodology should identify the redundancy embedded into ontology. In this paper, we propose a design methodology dedicated to SDB including the main phases of the lifecycle of the database development: conceptual, logical, deployment and physical. The conceptual design of SDB can be easily performed by exploiting the similarities between ontologies and conceptual models. The logical design phase is performed thanks to the incorporation of dependencies between concepts and properties in the ontologies. These dependencies are quite similar to the principle of functional dependencies defined in the traditional databases. Due to the diversity of the SDB architectures and the variety of the used storage layouts (horizontal, vertical, binary) to store and manage ontological data, we propose a SDB deployment à la carte. Finally, a prototype implementing our design approach on Oracle 11g is outlined. more...

The spectacular use of ontologies generates a big amount of semantic instances. To facilitate their management, a new type of databases, called semantic databases ($\mathcal{S}\mathcal{D}\mathcal{B}$) is launched. Large panoply of these $\mathcal{S}\mathcal{D}\mathcal{B}$ exists. Three main characteristics may be used to differentiate them: (i) the storage layouts for storing instances and the ontology, (ii) ontology modeling languages, and (iii) the architecture of the target database management system (DBMS) supporting them. During the deployment phase, the database administrator (DBA) is faced to a choice problem (which $\mathcal{S}\mathcal{D}\mathcal{B}$ she/he needs to choose). In this paper, we first present in details the causes of this diversity. Based on this analysis, a generic formalization of $\mathcal{S}\mathcal{D}\mathcal{B}$ is given. To facilitate the task of the DBA, mathematical cost models are presented to evaluate the performance of each type of $\mathcal{S}\mathcal{D}\mathcal{B}$. Finally, two types of intensive experiments are conducted by considering six $\mathcal{S}\mathcal{D}\mathcal{B}$, both issued from industry and academic communities; one based on our mathematical cost models and another based on the studied semantic DBMS cost models. more...

Nowadays, all ingredients are available for developing domain ontologies. This is due to the presence of various types of methodologies for creating domain ontologies [3]. The adoption of ontologies by real life applications generates mountains of ontological data that need techniques and tools to facilitate their storage, management and querying. more...

In this paper, we address the problem of cooperative query answering on Semantic Web Databases (\(\mathcal{SWDB}s\)) in order to overcome the problem of empty or unsatisfactory answers. While most existing approaches propose an automatic relaxation process based on RDF-S entailment, our proposition consists in endowing \(\mathcal{S}\mathcal{W}\mathcal{D}\mathcal{B}\) query languages with relaxation and approximation operators. The main interest of this approach is that the relaxation process can be finely controlled by the user or implicitly by the system. Experiments on real data are conducted to evaluate (1) the scalability of the proposed operators and (2) the interest of the similarity measure defined to rank the alternative answers. more...

With the increasing needs for the world wide enterprises to integrate, share and visualize data from various heterogeneous, autonomous and distributed sources data and Web data covering a given domain, the development of integration and reconciliation solutions becomes a challenging issue. The existing studies on data integration and reconciliation of results have been developed in an isolated way and did not consider the strong integration between these two processes. On one hand, ontologies were largely used for building automatic integration systems due to their ability to reduce schematic and semantic heterogeneities that may exist among sources. On the other hand, reconciliation of results is performed either by considering that all sources use the same identifier for an instance or by means of statistical methods that identify affinities between concepts. These reconciliation solutions are not usually suitable for real-world sensitive-applications where exact results are required and where each source may use a different identifier for the same concept. In this paper, we propose a methodology that simultaneously integrate source data and reconciliate their instances based on ontologies enriched with functional dependencies (FD) in a mediation architecture. The presence of FD gives more autonomy to sources when choosing their primary keys and facilitates the result reconciliation. This methodology is experimented using the Lehigh University Benchmark (LUBM) dataset to show its scalability and the quality of the reconciliation result phase. more...

International audience; Providing automatic integration solutions is the key to the success of applications managing massive amounts of data. Two main problems stand out in the major studies: (i) the management of the source heterogeneity; (ii) the reconciliation of query results. To tackle the first problem, formal ontologies are used to explicit the semantic of data. The reconciliation problem consists in deciding whether different identifiers refer to the same instance. Two main trends emerge in the reconciliation process: (i) the assumption that different source entities representing the same concept have the same key – a strong hypothesis that violates the autonomy of sources; (ii) The use of statistical methods that identify affinities between concepts – not suitable for sensitive applications. In this paper, we propose a methodology integrating sources referencing shared domain ontology enriched with functional dependencies (FD). The presence of FD gives more autonomy to sources when choosing their primary keys and allows deriving a reconciliation key for a given query. The methodology is then validated using LUBM. more...

With the globalisation, the development of advanced applications and complex systems requires the implication of a large number of designers that may come from different fields, departments, research laboratories, etc. Usually, they are free to use their favourite vocabularies and formalisms to express the requirements related to their assigned parts of a given project. Various formalisms exist to express user requirements: informal (interviews), semi-formal (UML use case, goal oriented, etc.) and formal (B-Method, etc.). The concepts and properties used by these formalisms may belong to different alphabets. This situation makes the interoperability between user requirement formalism models difficult. In this paper, we propose a conceptual ontology-driven approach to facilitate this interoperability and to reduce the heterogeneities between formalisms. We first present the concepts related to conceptual ontologies and their connection with the user requirement formalisms. Secondly, a pivot model allowing the integration of different semi-formal models is described, through a case study. Finally, an implementation based on model driven approach (MDA) is given. more...

Recently, Ontology-Based DataBases (OBDB) have been developed as a solution to store and manipulate, efficiently and in a scalable way, ontologies together with data they describe. Currently, existing OBDBs propose weak solutions to calculate derived (non-canonical) concepts. Indeed, these solutions are internal to the OBDB and specific to the ontology model (formalism) supported. As a consequence, non-canonical concepts can not be in all cases properly defined with the different available mechanisms since existing solutions are not constantly suitable. In this paper, we propose a generic solution which is an extension of OBDBs with the capability to introduce dynamically operators to calculate non-canonical concepts. These operators can be implemented in different ways (e.g. with external programs or with web services). Then, we show the interest of this extension by improving a proposed methodology to design databases storing ontologies. Finally, a prototype implementing our design approach is outlined. more...

Due to the explosion of ontologies on the web (Semantic Web, E-commerce, and so on) organizations are faced with the problem of managing mountains of ontological data. Several academic and industrial databases have been extended to cope with these data, which are called Ontology-Based Databases (\(\mathcal{O}\mathcal{B}\mathcal{D}\mathcal{B}\)). Such databases store both ontologies and data on the same repository. Unlike traditional databases, where their logical models are stored following the relational model and most of properties identified in the conceptual phase are valuated, OBDBs are based on ontologies which describe in a general way a given domain; some concepts and properties may not be used and valuated and they may use different storage models for ontologies and their instances. Therefore, benchmarking \(\mathcal{O}\mathcal{B}\mathcal{D}\mathcal{B}\) represents a crucial challenge. Unfortunately, existing \(\mathcal{O}\mathcal{B}\mathcal{D}\mathcal{B}\) benchmarks manipulate ontologies and their instances with characteristics far away from real life applications in terms of used concepts, attributes or instances. As a consequence, it is difficult to identify an appropriate physical storage model for the target \(\mathcal{O}\mathcal{B}\mathcal{D}\mathcal{B}\), which enables efficient query processing. In this paper, we propose a novel benchmarking system called OntoDBench to evaluate the performance and scalability of available storage models for ontological data. Our benchmark system allows : (1) evaluating relevant characteristics of real data sets, (2) storing the dataset following the existing storage models, (3) expressing workload queries based on these models and (4) evaluating query performance. Our proposed ontology-centric benchmark is validated using the data sets and workload from the Lehigh University Benchmark (LUBM). more...

With the increasing amount of Web Services available on the Web, Web Services discovery issues are becoming increasingly important. Since current Web Services standard technologies (e.g. UDDI) only provide syntactic descriptions of Web Services (mainly their signatures), semantic discovery approaches based on ontologies (e.g. OWL-S) have been developed. These approaches lead to more precise descriptions of Web Services functionalities, but they provide few mechanisms to capture non functional aspects of Web Services collectively referred as Quality of Services (QoS). To fill this gap, some works have proposed Web Services discovery approaches based on QoS ontologies. However these approaches do not take into account existing standards about software quality and the relationships that can be established between them. Yet, these standards could be used as a shared understanding between services providers and customers and thus, they would ease the Web Services discovery process. In this article we first propose an extension of OWL-S to describe QoS according to one or many quality standards. Then, we develop an approach based on this extension of OWL-S to improve the Web Services discovery process. This approach is based on an extension of SPARQL that simplifies expression of Web Services discovery queries. Relationships between standards are used to return Web Services even if they are described with quality properties defined in an other standard that the one used to express queries. Finally, non functional requirements can be expressed as user preferences. Thus, they can be used to rank Web Services fulfilling functional requirements during the Web Service discovery process. more...

Current databases and their associated languages allow a user to exploit data according to their logical model. Usually, there is a gap between this logical model and the actual concepts represented. As a consequence, exploiting, exchanging and integrating data stored in databases are difficult. To overcome these problems, several approaches have proposed to extend current databases with ontologies. We called Ontology-Based Databases (OBDB) such databases. However, current database languages such as SQL have not been designed to exploit ontologies. Thus, a new generation of languages we called ontology query languages has emerged. The goal of this chapter is to provide an up to date survey on ontology query languages. We survey languages coming from the Semantic Web community as well as those coming from the database community. more...

Nowadays, metamodeling techniques and ontologies play a central role in many computer science problems such as data exchange, integration of heterogeneous data and models or software reuse. Yet, if many metamodeling repositories and ontology repositories have been proposed, few attempts have been made to combine their advantages into a single repository with a dedicated language. In this paper, we present the capabilities of the OntoQL language for managing the various levels of information stored in a metamodeling systems where (1) both data, models and metamodels are available and (2) semantic descriptions are provided using ontologies. Some of the main characteristics of OntoQL are: management of the metamodel level using the same operators as the ones applied to data and to model levels, semantic queries through ontologies and SQL compatibility. We report several applications where this language has been extensively and successfully used. more...

Engineering models are computer-based models that enclose technical data issued from engineering domains. Those models usually implicit many of the details required to understand and interpret the data. In this context, integrating the results of models and querying the heterogeneous information is a challenge. more...

Most database applications are designed according the ANSI/SPARC architecture. When it is used a large amount of semantics of data may be lost during the transformation from the conceptual model to a logical model. As a consequence exchanging/integrating various databases or generating user interfaces for data access become difficult. Ontologies seem an interesting solution to solve these problems, since they allow making explicit the semantics of data. In this paper, we propose an ontology-based approach for designing database applications, and then, for representing explicitly the semantics of data within the database. It consists in extending the ANSI/SPARC architecture with the ontological level. Note that this extension may also be added to existing applications designed according to the ANSI/SPARC architecture, since it preserves an upward compatibility. more...

Engineering development activities rely on computer-based models, which enclose technical data issued from different sources. In this heterogeneous context, retrieving, re-using and merging information is a challenge. We propose to annotate engineering models with concepts of domain ontologies, which provide data with explicit semantics. The semantic annotation makes it possible to formulate queries using the semantic concepts that are significant to the domain of the engineers. This work is inspired from a petroleum engineering case study and we validate our approach by presenting an implementation of this case study. more...

1th International Conference on Enterprise Information Systems; Milan; Italy; 6 May 2009 through 10 May 2009, Ontologies have been defined to make explicit the semantics of data. With the emergence of the SemanticWeb, the amount of ontological data (or instances) available has increased. To manage such data, Ontology Based DataBases (OBDBs), that store ontologies and their instance data in the same repository have been proposed. These databases are associated with exploitation languages supporting description, querying, etc. on both ontologies and data. However, usually queries return a big amount of data that may be sorted in order to find the relevant ones. Moreover, in the current, few approaches considering user preferences when querying have been developed. Yet this problem is fundamental for many applications especially in the e-commerce domain. In this paper, we first propose an extension of an existing OBDB, called OntoDB through extension of their ontology model in order to support semantic description of preferences. Secondly, an extension of an ontology based query language, called OntoQL defined on OntoDB for querying ontological data with preferences is presented. Finally, an implementation of the proposed extensions are described. more...

International audience; Nowadays, ontologies are used in a lot of diverse research fields. They provide with the capability to describe a huge set of information contents. Therefore, several approaches for storing ontologies and their instances in databases have been proposed. We call Ontology Based Database (OBDB) a database providing such a capability. Several OBDB have been developed using different ontology models and different representation schemas to store the data. This paper proposes a data model and an algebra of operators for OBDB which can be used whatever are the used ontology model and representation schema. By extending the work done for object oriented databases (OODB), we highlight the differences between OODB and OBDB both in terms of data model and query languages. more...

If the word ontology is more and more used in a number of domain, the capabilities and benefits of ontology for Information Systems management are still unclear. Therefore, the usage of ontology-based Information Systems in industry and services is not widespread. This paper analyses the concept of a domain ontology from a database perspective. As a result, firstly, we provide three criteria that distinguish domain ontology from other existing domain modeling approach which lead us to propose a new definition of domain ontologies. Secondly, based on the various approaches of ontology modeling followed by different communities, we propose a taxonomy of domain ontology. We show how they may be organized into a layered model, called the onion model, allowing to design and to use the capabilities of each category of ontology in an integrated environment. Finally, this paper presents several information systems based on ontology technologies and describe the kinds of services that should be provided to allow a powerful usage of ontology in data management. more...

International audience; Nowadays, ontologies are used in several research domains by offering the means to describe and represent concepts of information sources. Therefore, several approaches and systems storing ontologies and their instances in the same repository (database) have been proposed. As a consequence, defining a query language to support ontology-based database (OBDB) becomes a challenge for the database community. In this paper, we present OntoQL, an ontology query language for OBDBs. Firstly, we present formally the OBDB data model supported by this language. Secondly, an overview of the algebra defining the semantics of operators used in OntoQL is described. Several query examples showing the interest of this language compared to traditional database query languages are given along this paper. Finally, we present a prototype of the implementation of OntoQL. more...