1,354,175 research outputs found

    Matching operators in data integration

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    This paper discusses the role of matching operators in Data Integration process. The paper proposes acategorization of matching operators, with the aim of distinguishing different relations to the possiblegoals of an integration process and their impact on the implementation of the mappings defining thisintegration. In order to lead the discussion some example

    An FCA-based mapping generator

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    We present an overview of ODDI an Ontology Driven Data Integration system based on Formal concept analysis and instance comparison. Data Integration systems are used to integrate heterogeneous data sources in a single view. Following the Global-as-View approach the data is retrieved through a common conceptualization, that in our system is modeled as an ontology. This paper focuses on the problem of matching and mapping of elements between the common ontology and the data sources. The problem of query translation is also mentioned for sake of completeness, but it will be treated in detail in a future paper. Recent works on Business Intelligence do highlight the need oftrustable and sound data access systems. We propose a system based on FCA to generate the mapping to the common representation and the relations between the heterogeneous data sources

    Potenzialità tecnologiche, chimiche e nutrizionali del frumento monococco

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    Per valutare le potenzialità tecnologiche, chimiche e nutrizionali del frumento monococco (Triticum monococcum) sono state analizzate farine integrali di tale specie e, come controllo, di Triticum turgidum e Triticum aestivum. I campioni di monococco hanno un alto contenuto in proteine (18,2±1,48 g/100 g) e ceneri (2,3±0,17 g/100 g). I carotenoidi, principalmente luteina, si attestano intorno a 8,4±1,23 mg/g, mentre i tocoli raggiungono i 78,1±9,19 mg/g s.s. Gli acidi grassi più abbondanti sono quelli linoleico (50,8% del totale), oleico (24,8%) e palmitico (16,6%). L’attività lipossigenasica è sempre minima. Sono stati determinati anche amido totale (65,5±2,56%), amilosio (25,7±1,23%) e fruttani (2 g/kg s.s.). Il volume di sedimentazione in SDS è basso (25,6±8,7 mL), ma esistono accessioni con valori superiori a 60 mL; la viscosità delle farine è simile a quella degli altri frumenti. Il monococco appare quindi particolarmente adatto alla produzione di alimenti ad elevato valore nutrizionale.The potential for human consumption of einkorn (Triticum monococcum) was studied through the analysis of chemical composition as well as technological and pasting properties of whole meal flour. Triticum turgidum and Triticum aestivum were the controls. Einkorn had high protein (18.2±1.48 g/100 g) and ash content (2.3±0.17 g/100 g). Carotenoids, mostly lutein, averaged 8.4±1.23 mg/g, while tocols averaged 78.1±9.19 mg/g. Linoleic (50.8%), oleic (24.8%), and palmitic (16.6%) were the most abundant fatty acids. Lipoxygenase activity was always minimal. Total starch (65.5±2.56%), amylose (25.7±1.23%), and fructans (2 g/kg) were also measured. SDS sedimentation volume was low (25.6±8.7 mL), but some accessions had values >60. Pasting parameters were similar to those of the other wheats. The results demonstrate that einkorn is a promising source for the production of high nutitional value products

    Semantics-aware matching strategy (SAMS) for the ontology mediated data integration (ODDI)

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    Data integration systems are used to integrate heterogeneous data sources in a single view. Recent work on business intelligence highlights the need of on-time, reliable and sound data access systems relying on methods based on semi-automatic procedures. A crucial factor for any semi-automatic algorithm is that of the matching strategy. Different categories of matching operators carry different semantics. For this reason, combining them into a single strategy is a non-trivial process that has to take into account a variety of options. This paper presents SAMS, a matching strategy based on a semantics-aware categorisation of matching operators that allows to group similar attributes on a semantically-rich form

    ODDI : a framework for semi-automatic data integration

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    Recent works on Business Intelligence do highlight the need of on-time, trustable and sound data access systems. Moreover the application of these systems in a flexible and dynamic environment requires for an approach based on automatic procedures that can provide reliable results. A crucial factor for any automatic data integration system is the matching process. Different categories of matching operators carry different semantics. For this reason combining them in a single algorithm is a non trivial process that have to take into account a variety of options. This paper proposes a solution based on a categorization of matching operators that allow to group similar attributes on a semantic rich form. This way we define all the information need in order to create a mapping. Then Mapping Generation is activated only on those set of elements that can be queried without violating any integrity constraints on data

    Using ontologies to map concept relations in a data integration system

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    In this paper we propose a Data Integration System based on an ontology as Global Representation. The paper briefly introduces the motivations and the benefits that the use of an ontology brings to a Data Integration System, which is also formally defined. The paper, in particular, focuses on the limitation of the proposed system to handle the different relations that can exist between concepts of an ontology. We divide the relations that can be defined in an ontology in two different sets: Mapped relations, which we consider atomic relations and Derived relations, which can be generated by combining mapped relations using SWRL rules. Some examples of the different kind of relations are reported to clarify the concepts and a new definition of Mapping in the Data Integration System is proposed, in order to define the atomic relations. The paper ends with considerations about the problems that still need to be considered

    Management of Virtual Organizations

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    In the Virtual Organization (VO) Management area the main challenge has been to develop policies and models for governance and lifecycle management of a business-to-business (B2B) collaboration. This work included research and development in the areas of federated identity management and semantics in addition to VO, business registries and B2B collaboration managements. The main results produced in the VO Management area include capabilities, patterns and software solutions to simplify governance and lifecycle management of B2B collaborations (VOs), and to manage applications distributed over several federated network hosts (e.g. Cloud Computing platforms)
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