Common use of Research Framework Clause in Contracts

Research Framework. Decision support increasingly requires the ability to manage, combine and use information from heterogeneous sources.. Figure 3.1 depicts framework for decision support based on four pillars related to semantic interoperabil- ity, GIS interoperability, query processing and P2P architectures. In the following, the main characteristics and issues of the four pillars is presented. Figure 3.1: Four Pillars Research Famework 3.2.1 Semantic Interoperability, characteristics and is- sues Research on interoperability is shifting from communication level to high operational level where data semantics play an important role. Informa- tion heterogeneity can occur at the syntactic, structural and semantic level. Semantic interoperability is more acute in dynamic and autonomous envi- ronments, due to the lack of relationships among sources. Semantic inter- operability is essentially based on having a common understanding of the meaning of the information exchanged by di erent sources. It's a multi-level problem that can occur in data sources, fromats or models. The main characteristics of semantic interoperability pillar are: Semi-structure data models such as XML are used to model web oriented data and to facilitate interoperability. XML is widely ac- cepted as the de facto standard for data modeling and exchange in web environments. XML (eXtensible Markup Language) is a textual language that provides a structural description (and re- lated semantic) of information. It allows the de nition of schema in XML Schema or grammars to represent the conceptual char- acteristics of information systems. XML is a meta-language from which several variants have been derived for di erent domains in the last few years. Examples of languages derived from XML in- clude GML (Geography Markup Language), Global Positioning System Markup Language (GPSML). XML is foundation syntax for upper layer in semantic and ontology model, such as RDF, OWL. Ontologies are increasingly used in interoperable systems, to cap- ture the meanings and relationships of concepts used in various domains. ▇▇▇▇▇▇ [47] de nes an ontology as an explicit speci ca- tion of a conceptualization of the real world entities of an applica- tion domain. An ontology is a vocabulary composed of terms and relationships among them. Several studies have been devoted to ontology representation lan- guages: they range from informal natural languages to formal languages based on predicate logic or graph concepts. Among the formal languages, OWL which has recently gained in popularity, is a description language aimed at incorporating a theory based semantics and an ontological inference and reasoning mechanism into RDF . Some of issues involved in semantic heterogeneity are: 3.2.2 GIS Interoperability, characteristics and issues In addition to the problem involved in semantic interoperability of traditional data, GIS interoperability must take into account spatial and temporal char- acteristics. Geographic information systems are commonly used in many spatial and environmental applications. There are well known GIS software system, such as ESRI ArcInfo, Smallworld GIS, Intergraph GeoMedia, Map- Info Professional and Grass. Proposed by di erent vendor who have their own proprietary software designs, data models, and database storage struc- ture. This results in the availability of a large number of ad hoc independent spatial data repositories created for speci c purposes and described in var- ious formats. To exchange information and share computational geo-data resources among heterogeneous systems, conversion tools are usually devel- oped to transfer data from one format to other format. GIS composed of image and traditional database, it required geographic data exhibits com- plex structure, large size, and complex semantics. The motivation for the interoperability of geographical information systems is to provide users with the architectures and tools to: tutions and government agencies. However, spatial data sharing can be hindered by data volume and con icts arising from the diversity and complexity of spatial data structures. To achieve the goal of semantic interoperability of geographic systems, several issues must be tackled.: 3.2.3 P2P Architecture, characteristics and issues Peer to Peer (P2P) is becoming popular as overlay network on top of Internet. P2P allows sharing of large volume of data and other resources. Some popular implementations of P2P are Nepster for sharing mp3 music le, and eDonkey for sharing many type of le such as book, music, movie. Implementation of P2P for GIS le sharing has been introduced, the purpose is to overcome the large size of GIS data and network tra c by 'automatically' distributing the data/ le to some peers. P2P can provide infrastructure for dynamic environment in which au- tonomous and independent peers can joint or leave the network easily and frequently. However in a diverse and large community, it is hard to discover relevant data for decision making. P2P allow to develop community which share common interest, so that large community will be 'clustered' based on the same interest. Then searching relevant data can be easier. As shown in gure 3.1, P2P system are characterized by the following components: Generally P2P can be used to: number of sources with relevant data need to be searched for. Another characteristic of P2P is the autonomy of data sources. Every source has high autonomy to decide which data will be available for public, and which format or point of view will implement. P2P systems have mech- anism to handle autonomous environment, and semantic can tackle of diversity of information sources in P2P environment. There are interesting issues that must be addressed to achieve semantic interoperability of spatial information. 3.2.4 Query Processing, characteristics and issues A query is an access facility to database. Query in a heterogeneous database system can be expressed in the query language of the component databases or in a system-independent query language. Processing a query requires a mechanism for decomposing, and translating the query into subqueries for relevant sources. Query processing can involve query optimization stage that determines a query strategy and plan for accessing the component sources and combin- ing the query result. The optimization techniques also depend on the type of query interface supported by the system. Two queries are semantically equivalent if they return the same answer for any database state satisfying a given set of integrity constraints. A semantic transformation transforms a given query into a semantically equivalent one. Semantic query optimization is the process of determining the set of semantic transformation that results in a semantically equivalent query with a lower execution cost. Therefore the main components of query pillar are: Regarding the query pillar, in this thesis will focus on: Figure 3.2: Peer Agreement Famework