Improving knowledge about the risks of inappropriate uses of geospatial data by introducing a collaborative approach in the design of geospatial databases

La disponibilité accrue de l’information géospatiale est, de nos jours, une réalité que plusieurs organisations, et même le grand public, tentent de rentabiliser; la possibilité de réutilisation des jeux de données est désormais une alternative envisageable par les organisations compte tenu des économies de coûts qui en résulteraient. La qualité de données de ces jeux de données peut être variable et discutable selon le contexte d’utilisation. L’enjeu d’inadéquation à l’utilisation de ces données devient d’autant plus important lorsqu’il y a disparité entre les nombreuses expertises des utilisateurs finaux de la donnée géospatiale. La gestion des risques d’usages inappropriés de l’information géospatiale a fait l’objet de plusieurs recherches au cours des quinze dernières années. Dans ce contexte, plusieurs approches ont été proposées pour traiter ces risques : parmi ces approches, certaines sont préventives et d’autres sont plutôt palliatives et gèrent le risque après l'occurrence de ses conséquences; néanmoins, ces approches sont souvent basées sur des initiatives ad-hoc non systémiques. Ainsi, pendant le processus de conception de la base de données géospatiale, l’analyse de risque n’est pas toujours effectuée conformément aux principes d’ingénierie des exigences (Requirements Engineering) ni aux orientations et recommandations des normes et standards ISO. Dans cette thèse, nous émettons l'hypothèse qu’il est possible de définir une nouvelle approche préventive pour l’identification et l’analyse des risques liés à des usages inappropriés de la donnée géospatiale. Nous pensons que l’expertise et la connaissance détenues par les experts (i.e. experts en geoTI), ainsi que par les utilisateurs professionnels de la donnée géospatiale dans le cadre institutionnel de leurs fonctions (i.e. experts du domaine d'application), constituent un élément clé dans l’évaluation des risques liés aux usages inadéquats de ladite donnée, d’où l’importance d’enrichir cette connaissance. Ainsi, nous passons en revue le processus de conception des bases de données géospatiales et proposons une approche collaborative d’analyse des exigences axée sur l’utilisateur. Dans le cadre de cette approche, l’utilisateur expert et professionnel est impliqué dans un processus collaboratif favorisant l’identification a priori des cas d’usages inappropriés. Ensuite, en passant en revue la recherche en analyse de risques, nous proposons une intégration systémique du processus d’analyse de risque au processus de la conception de bases de données géospatiales et ce, via la technique Delphi. Finalement, toujours dans le cadre d’une approche collaborative, un référentiel ontologique de risque est proposé pour enrichir les connaissances sur les risques et pour diffuser cette connaissance aux concepteurs et utilisateurs finaux. L’approche est implantée sous une plateforme web pour mettre en œuvre les concepts et montrer sa faisabilité.Nowadays, the increased availability of geospatial information is a reality that many organizations, and even the general public, are trying to transform to a financial benefit. The reusability of datasets is now a viable alternative that may help organizations to achieve cost savings. The quality of these datasets may vary depending on the usage context. The issue of geospatial data misuse becomes even more important because of the disparity between the different expertises of the geospatial data end-users. Managing the risks of geospatial data misuse has been the subject of several studies over the past fifteen years. In this context, several approaches have been proposed to address these risks, namely preventive approaches and palliative approaches. However, these approaches are often based on ad-hoc initiatives. Thus, during the design process of the geospatial database, risk analysis is not always carried out in accordance neither with the principles/guidelines of requirements engineering nor with the recommendations of ISO standards. In this thesis, we suppose that it is possible to define a preventive approach for the identification and analysis of risks associated to inappropriate use of geospatial data. We believe that the expertise and knowledge held by experts and users of geospatial data are key elements for the assessment of risks of geospatial data misuse of this data. Hence, it becomes important to enrich that knowledge. Thus, we review the geospatial data design process and propose a collaborative and user-centric approach for requirements analysis. Under this approach, the user is involved in a collaborative process that helps provide an a priori identification of inappropriate use of the underlying data. Then, by reviewing research in the domain of risk analysis, we propose to systematically integrate risk analysis – using the Delphi technique – through the design of geospatial databases. Finally, still in the context of a collaborative approach, an ontological risk repository is proposed to enrich the knowledge about the risks of data misuse and to disseminate this knowledge to the design team, developers and end-users. The approach is then implemented using a web platform in order to demonstrate its feasibility and to get the concepts working within a concrete prototype

Towards development of fuzzy spatial datacubes : fundamental concepts with example for multidimensional coastal erosion risk assessment and representation

Les systèmes actuels de base de données géodécisionnels (GeoBI) ne tiennent généralement pas compte de l'incertitude liée à l'imprécision et le flou des objets; ils supposent que les objets ont une sémantique, une géométrie et une temporalité bien définies et précises. Un exemple de cela est la représentation des zones à risque par des polygones avec des limites bien définies. Ces polygones sont créés en utilisant des agrégations d'un ensemble d'unités spatiales définies sur soit des intérêts des organismes responsables ou les divisions de recensement national. Malgré la variation spatio-temporelle des multiples critères impliqués dans l’analyse du risque, chaque polygone a une valeur unique de risque attribué de façon homogène sur l'étendue du territoire. En réalité, la valeur du risque change progressivement d'un polygone à l'autre. Le passage d'une zone à l'autre n'est donc pas bien représenté avec les modèles d’objets bien définis (crisp). Cette thèse propose des concepts fondamentaux pour le développement d'une approche combinant le paradigme GeoBI et le concept flou de considérer la présence de l’incertitude spatiale dans la représentation des zones à risque. En fin de compte, nous supposons cela devrait améliorer l’analyse du risque. Pour ce faire, un cadre conceptuel est développé pour créer un model conceptuel d’une base de donnée multidimensionnelle avec une application pour l’analyse du risque d’érosion côtier. Ensuite, une approche de la représentation des risques fondée sur la logique floue est développée pour traiter l'incertitude spatiale inhérente liée à l'imprécision et le flou des objets. Pour cela, les fonctions d'appartenance floues sont définies en basant sur l’indice de vulnérabilité qui est un composant important du risque. Au lieu de déterminer les limites bien définies entre les zones à risque, l'approche proposée permet une transition en douceur d'une zone à une autre. Les valeurs d'appartenance de plusieurs indicateurs sont ensuite agrégées basées sur la formule des risques et les règles SI-ALORS de la logique floue pour représenter les zones à risque. Ensuite, les éléments clés d'un cube de données spatiales floues sont formalisés en combinant la théorie des ensembles flous et le paradigme de GeoBI. En plus, certains opérateurs d'agrégation spatiale floue sont présentés. En résumé, la principale contribution de cette thèse se réfère de la combinaison de la théorie des ensembles flous et le paradigme de GeoBI. Cela permet l’extraction de connaissances plus compréhensibles et appropriées avec le raisonnement humain à partir de données spatiales et non-spatiales. Pour ce faire, un cadre conceptuel a été proposé sur la base de paradigme GéoBI afin de développer un cube de données spatiale floue dans le system de Spatial Online Analytical Processing (SOLAP) pour évaluer le risque de l'érosion côtière. Cela nécessite d'abord d'élaborer un cadre pour concevoir le modèle conceptuel basé sur les paramètres de risque, d'autre part, de mettre en œuvre l’objet spatial flou dans une base de données spatiales multidimensionnelle, puis l'agrégation des objets spatiaux flous pour envisager à la représentation multi-échelle des zones à risque. Pour valider l'approche proposée, elle est appliquée à la région Perce (Est du Québec, Canada) comme une étude de cas.Current Geospatial Business Intelligence (GeoBI) systems typically do not take into account the uncertainty related to vagueness and fuzziness of objects; they assume that the objects have well-defined and exact semantics, geometry, and temporality. Representation of fuzzy zones by polygons with well-defined boundaries is an example of such approximation. This thesis uses an application in Coastal Erosion Risk Analysis (CERA) to illustrate the problems. CERA polygons are created using aggregations of a set of spatial units defined by either the stakeholders’ interests or national census divisions. Despite spatiotemporal variation of the multiple criteria involved in estimating the extent of coastal erosion risk, each polygon typically has a unique value of risk attributed homogeneously across its spatial extent. In reality, risk value changes gradually within polygons and when going from one polygon to another. Therefore, the transition from one zone to another is not properly represented with crisp object models. The main objective of the present thesis is to develop a new approach combining GeoBI paradigm and fuzzy concept to consider the presence of the spatial uncertainty in the representation of risk zones. Ultimately, we assume this should improve coastal erosion risk assessment. To do so, a comprehensive GeoBI-based conceptual framework is developed with an application for Coastal Erosion Risk Assessment (CERA). Then, a fuzzy-based risk representation approach is developed to handle the inherent spatial uncertainty related to vagueness and fuzziness of objects. Fuzzy membership functions are defined by an expert-based vulnerability index. Instead of determining well-defined boundaries between risk zones, the proposed approach permits a smooth transition from one zone to another. The membership values of multiple indicators (e.g. slop and elevation of region under study, infrastructures, houses, hydrology network and so on) are then aggregated based on risk formula and Fuzzy IF-THEN rules to represent risk zones. Also, the key elements of a fuzzy spatial datacube are formally defined by combining fuzzy set theory and GeoBI paradigm. In this regard, some operators of fuzzy spatial aggregation are also formally defined. The main contribution of this study is combining fuzzy set theory and GeoBI. This makes spatial knowledge discovery more understandable with human reasoning and perception. Hence, an analytical conceptual framework was proposed based on GeoBI paradigm to develop a fuzzy spatial datacube within Spatial Online Analytical Processing (SOLAP) to assess coastal erosion risk. This necessitates developing a framework to design a conceptual model based on risk parameters, implementing fuzzy spatial objects in a spatial multi-dimensional database, and aggregating fuzzy spatial objects to deal with multi-scale representation of risk zones. To validate the proposed approach, it is applied to Perce region (Eastern Quebec, Canada) as a case study

Why, Where and How to use Semantic Annotation for Systems Interoperability

ISSN 2247-6040International audienceSemantic annotation is one of the useful solutions to enrich target's (systems, models, meta-models, etc.) information. There are some papers which use semantic enrichment for different purposes (integration, composition, sharing and reuse, etc.) in several domains, but none of them provides a complete process of how to use semantic annotations. This paper identifies three main components of semantic annotation, gives a formal definition of semantic annotation method and presents a survey of current semantic annotation methods which include: languages and tools that can be used to develop ontology, the design of semantic annotation structure models and the corresponding applications. The survey presented in this paper will be the basis of our future research on models, semantics and architecture for systems interoperability

Interacting with Statistical Linked Data via OLAP Operations

Abstract. Online Analytical Processing (OLAP) promises an interface to analyse Linked Data containing statistics going beyond other interaction paradigms such as follow-your-nose browsers, faceted-search interfaces and query builders. Transforming statistical Linked Data into a star schema to populate a relational database and applying a common OLAP engine do not allow to optimise OLAP queries on RDF or to directly propagate changes of Linked Data sources to clients. Therefore, as a new way to interact with statistics published as Linked Data, we investigate the problem of executing OLAP queries via SPARQL on an RDF store. For that, we first define projection, slice, dice and roll-up operations on single data cubes published as Linked Data reusing the RDF Data Cube vocabulary and show how a nested set of operations lead to an OLAP query. Second, we show how to transform an OLAP query to a SPARQL query which generates all required tuples from the data cube. In a small experiment, we show the applicability of our OLAPto-SPARQL mapping in answering a business question in the financial domain

Explicitating semantics in Enterprise Information Systems Models

140 pages Report for the Post-Doctorate diploma of the Université Henri Poincaré Supervisors: Hervé Panetto and Alexis AubryInteroperability can be defined as the ability of two or more systems to share, to understand and to consume information (IEEE, 1990). The work (Chen et al., 2006) in the INTEROP NoE project has identified three different levels of barriers for interoperability: technical, conceptual and organisational. Our research focuses on the conceptual level of interoperability, namely the ability to understand the exchanged information. Information may be defined as data linked to knowledge about this data. This research memory will show the results obtained during the Post Doc study referring to the published works. It deals with a first phase from our general research work that focuses on the study of the semantic loss that appears in the exchange of information about business concepts. In order to quantify the semantic gap between interoperating ISs, their semantics needs to be enacted and structured by enriching, normalising and analysing their conceptual models. We propose a conceptualisation approach for explicitation of the finest-grained semantics, embedded into conceptual models in order to facilitate the semantic matching between two different information systems that have to interoperate. The structure of the document represents the different steps and the research domain on which the study focused

Using Semantic Web technologies in the development of data warehouses: A systematic mapping

The exploration and use of Semantic Web technologies have attracted considerable attention from researchers examining data warehouse (DW) development. However, the impact of this research and the maturity level of its results are still unclear. The objective of this study is to examine recently published research articles that take into account the use of Semantic Web technologies in the DW arena with the intention of summarizing their results, classifying their contributions to the field according to publication type, evaluating the maturity level of the results, and identifying future research challenges. Three main conclusions were derived from this study: (a) there is a major technological gap that inhibits the wide adoption of Semantic Web technologies in the business domain;(b) there is limited evidence that the results of the analyzed studies are applicable and transferable to industrial use; and (c) interest in researching the relationship between DWs and Semantic Web has decreased because new paradigms, such as linked open data, have attracted the interest of researchers.This study was supported by the Universidad de La Frontera, Chile, PROY. DI15-0020. Universidad de la Frontera, Chile, Grant Numbers: DI15-0020 and DI17-0043

Geospatial Information Research: State of the Art, Case Studies and Future Perspectives

Geospatial information science (GI science) is concerned with the development and application of geodetic and information science methods for modeling, acquiring, sharing, managing, exploring, analyzing, synthesizing, visualizing, and evaluating data on spatio-temporal phenomena related to the Earth. As an interdisciplinary scientific discipline, it focuses on developing and adapting information technologies to understand processes on the Earth and human-place interactions, to detect and predict trends and patterns in the observed data, and to support decision making. The authors – members of DGK, the Geoinformatics division, as part of the Committee on Geodesy of the Bavarian Academy of Sciences and Humanities, representing geodetic research and university teaching in Germany – have prepared this paper as a means to point out future research questions and directions in geospatial information science. For the different facets of geospatial information science, the state of art is presented and underlined with mostly own case studies. The paper thus illustrates which contributions the German GI community makes and which research perspectives arise in geospatial information science. The paper further demonstrates that GI science, with its expertise in data acquisition and interpretation, information modeling and management, integration, decision support, visualization, and dissemination, can help solve many of the grand challenges facing society today and in the future

Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project

Database Management; Artificial Intelligence (incl. Robotics); Information Systems and Communication Servic

Beiträge zu Business Intelligence und IT-Compliance

[no abstract