The Mediated Integration Arcitecture for heterogeneous Data Integration

To interoperate data sources which differ structurally and semantically, particular problems occur, for example, problems of changing schemas in data sources will affect the integrated schema. In this paper, we propose the mediated integration architecture (MedInt), which employs mediation and wrapping techniques as the main components for the integration of heterogeneous systems. With MedInt, a mediator acts as an intermediate medium transforming queries to sub-queries, integrating result data and resolving conflicts. Wrappers then transform sub-queries to specific local queries so that each local system is able to understand the queries

A Mediator to Integrate Databases and Legacy Systems: The Mediated Data Integration (MeDInt) Mediator

To interoperate data sources which differ structurally and semantically, particular problems occur, for example, problems of changing schema in data sources will affect the integrated schema. In this paper, conflicts between heterogeneous systems are investigated and existing approaches to integration are reviewed. We propose a new mediated approach employing the Mediated Data Integration Mediator (MeDInt), and wrapping techniques as the main components for the integration of databases and legacy systems. The MeDInt mediator acts as an intermediate medium transforming queries to sub-queries, integrating result data and resolving conflicts. Wrappers then transform sub-queries to specific local queries so that each local system is able to understand the queries. This framework is currently being developed to make the integration process more widely accessible by using standard tools. A prototype is implemented to demonstrate the model

An Approach to Integrate Heterogeneous Data Sources

To gain a competitive advantage, it is extremely important for executives to be able to obtain one unique view of information, normally scattered across disparate data sources, in an accurate and timely manner. To interoperate data sources which differ structurally and semantically, particular problems occur, for example, problems of changing schema in data sources will affect the integrated schema. In this paper, conflicts between heterogeneous systems are investigated and existing approaches to integration are reviewed. This research introduces a new mediated approach employing the Mediated Data Integration Mediator (MeDInt), and wrapping techniques as the main components for the integration of databases and legacy systems. The MeDInt mediator acts as an intermediate medium transforming queries to subqueries, integrating result data and resolving conflicts. Wrappers then transform sub-queries to specific local queries so that each local system is able to understand the queries. This framework is currently being developed to make the integration process more widely accessible by using standard tools. A prototype is implemented to demonstrate the model

The data warehouse as a means to support knowledge management

: This paper tries to provide a new view on the currently vastly discussed and successfully employed concept of a Data Warehouse. This view presents it in the light of Knowledge Management, i.e. a Data Warehouse can serve as a storage medium for keeping the corporate memory, or at least concerning certain types of data. It helps gaining new knowledge by delivering well integrated data to analysis tools, e.g. On-Line Analytical Processing or Knowledge Discovery in Databases, and thus becomes an important part of Decision Support Systems or Executive Information Systems. In this way a Data Warehouse, storing only data, results in growth of knowledge and may lead to enhance the enterprise 's success. The paper does not claim, that a Data Warehouse is the only thing an enterprise needs to perform successful Knowledge Management. 1 Introduction During the last months several workshops, symposia etc. dealt with a new (or not so new) topic: "Knowledge Management" (KM). The term..

Development of grid frameworks for clinical trials and epidemiological studies

E-Health initiatives such as electronic clinical trials and epidemiological studies require access to and usage of a range of both clinical and other data sets. Such data sets are typically only available over many heterogeneous domains where a plethora of often legacy based or in-house/bespoke IT solutions exist. Considerable efforts and investments are being made across the UK to upgrade the IT infrastructures across the National Health Service (NHS) such as the National Program for IT in the NHS (NPFIT) [1]. However, it is the case that currently independent and largely non-interoperable IT solutions exist across hospitals, trusts, disease registries and GP practices – this includes security as well as more general compute and data infrastructures. Grid technology allows issues of distribution and heterogeneity to be overcome, however the clinical trials domain places special demands on security and data which hitherto the Grid community have not satisfactorily addressed. These challenges are often common across many studies and trials hence the development of a re-usable framework for creation and subsequent management of such infrastructures is highly desirable. In this paper we present the challenges in developing such a framework and outline initial scenarios and prototypes developed within the MRC funded Virtual Organisations for Trials and Epidemiological Studies (VOTES) project [2]

Geospatial data harmonization from regional level to european level: a usa case in forest fire data

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Geospatial data harmonization is becoming more and more important to increase interoperability of heterogeneous data derived from various sources in spatial data infrastructures. To address this harmonization issue we present the current status of data availability among different communities, languages, and administrative scales from regional to national and European levels. With a use case in forest data models in Europe, interoperability of burned area data derived from Europe and Valencia Community in Spain were tested and analyzed on the syntactic, schematic and semantic level. We suggest approaches for achieving a higher chance of data interoperability to guide forest domain experts in forest fire analysis. For testing syntactic interoperability, a common platform in the context of formats and web services was examined. We found that establishing OGC standard web services in a combination with GIS software applications that support various formats and web services can increase the chance of achieving syntactic interoperability between multiple geospatial data derived from different sources. For testing schematic and semantic interoperability, the ontology-based schema mapping approach was taken to transform a regional data model to a European data model on the conceptual level. The Feature Manipulation Engine enabled various types of data transformation from source to target attributes to achieve schematic interoperability. Ontological modelling in Protégé helped identify a common concept between the source and target data models, especially in cases where matching attributes were not found at the schematic level. Establishment of the domain ontology was explored to reach common ground between application ontologies and achieve a higher level of semantic interoperability

Towards interoperability in heterogeneous database systems

Distributed heterogeneous databases consist of systems which differ physically and logically, containing different data models and data manipulation languages. Although these databases are independently created and administered they must cooperate and interoperate. Users need to access and manipulate data from several databases and applications may require data from a wide variety of independent databases. Therefore, a new system architecture is required to manipulate and manage distinct and multiple databases, in a transparent way, while preserving their autonomy. This report contains an extensive survey on heterogeneous databases, analysing and comparing the different aspects, concepts and approaches related to the topic. It introduces an architecture to support interoperability among heterogeneous database systems. The architecture avoids the use of a centralised structure to assist in the different phases of the interoperability process. It aims to support scalability, and to assure privacy and nfidentiality of the data. The proposed architecture allows the databases to decide when to participate in the system, what type of data to share and with which other databases, thereby preserving their autonomy. The report also describes an approach to information discovery in the proposed architecture, without using any centralised structure as repositories and dictionaries, and broadcasting to all databases. It attempts to reduce the number of databases searched and to preserve the privacy of the shared data. The main idea is to visit a database that either containsthe requested data or knows about another database that possible contains this data

Big-Data-Driven Materials Science and its FAIR Data Infrastructure

This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

An Ontology Based Approach To The Integration Of Heterogeneous Information Systems Supporting Integrated Provincial Administration In Khon Kaen, Thailand

Information systems are a necessity to the administration of organizations. In a recent reform to the Thai administration, the governor of each province is entrusted with the full responsibility for the strategic planning and execution of the Integrated Provincial Administration (IPA). This presents a big challenge and many difficult problems for a potentially fast growing, both economically and demographically, province, such as Khon Kaen. To provide the administrator of the province with reliable and up to date information, the Provincial Operation Centre (POC) has been set up and assigned the task of collecting all required information from disparate information systems, many of which are legacy systems. This information lacks interoperability and integration of data due to many different structures and semantic heterogeneity encountered in many information systems. This research is a part of a collaborative data sources community development project. It attempts to aid high-level decision makers by using ontology to resolve heterogeneities among many disparate data sources. After relevant data sources are identified, they are analysed to reveal important and corresponding concepts, attributes and relations. They are then used in the creation of ontologies to resolve schematic and semantic conflicts in the data sources. The integration of many heterogeneous information systems will provide a unified view of information facilitating the provincial administrator in his decision making