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In this paper we discuss the experience of the development of a real system for integrating data about turnover, price and selling volume of AOP UnoLombardia, the biggest association of fruit and vegetable growers in the Lombardia region (Italy), that includes primary Italian and European brands such as Bonduelle and Dimmidisi. The system represents an adaptation and transformation of traditional data warehouse repository oriented development to comply the requirements of a coopetitive environment, where multiple organizations are willing to cooperate over some topics but, at the same time, they compete in the market. Readers may found useful insights and lessons learned from the following contributions of the present work: (i) a methodology to design data warehouse applications in a coopetitive environment and (ii) an architecture based on the combination of virtual data integration and traditional ETL enforcing protection of sensible data. © 2013 Springer-Verlag.

In this paper we consider the case of the ICT adoption and use in an agriculture cluster in Lombardy, a northern region of Italy. At the state of the art, relationships among key factors of adoption and use of ICT in agriculture area received little attention by the academic literature. Thus, in this paper we aim to identify a research model in order to provide evidence of four different research questions concerning the determining factors for ICT adoption. The proposed case study reports and discusses the results obtained by analysing data from a survey of about 600 agricultural farms. Finally, Belief Bayesian Networks (BBNs) are used to analyse the complex influence relationships detected between research variables

An increasing amount of data is published and consumed on the Web according to the Linked Data paradigm. In consideration of both publishers and consumers, the temporal dimension of data is important. In this paper we investigate the characterisation and availability of temporal information in Linked Data at large scale. Based on an abstract definition of temporal information we conduct experiments to evaluate the availability of such information using the data from the 2011 Billion Triple Challenge (BTC) dataset. Focusing in particular on the representation of temporal meta-information, i.e., temporal information associated with RDF statements and graphs, we investigate the approaches proposed in the literature, performing both a quantitative and a qualitative analysis and proposing guidelines for data consumers and publishers. Our experiments show that the amount of temporal information available in the LOD cloud is still very small; several different models have been used on different datasets, with a prevalence of approaches based on the annotation of RDF documents. © 2012 Springer-Verlag Berlin Heidelberg.

An increasing amount of data are published and consumed on the Web according to the Linked Data paradigm. In such scenario, understanding if the data consumed are up-to-date is crucial. Outdated data are usually considered inappropriate for many crucial tasks, such as make the consumer confident that answers returned to a query are still valid at the time the query is formulated. In this paper we present a first dataset-independent framework for assessing currency of Linked Open Data (LOD) graphs. Starting from the analysis of the 8,713,282 triples containing temporal metadata in the billion triple challenge 2011, we investigate which vocabularies are used to represent versioning metadata, we defined Onto Currency, an ontology that integrates the most frequent properties used in this domain, and supports the collection of metadata from datasets that use different vocabularies. The proposed framework uses this ontology to assess the currency of an RDF graph/statement, by extrapolating it from the currency of the documents that describe the resources occurring in the graphs (statement). The approach has been implemented and evaluated in two different scenarios. © 2012 IEEE.

Many data sets contain temporal records over a long period of time; each record is associated with a time stamp and describes some aspects of a realworld entity at that particular time. From such data, users often wish to search for entities in a particular period and understand the history of one entity or all entities in the data set. A major challenge for enabling such search and exploration is to identify records that describe the same realworld entity over a long period of time; however, linking temporal records is hard given that the values that describe an entity can evolve over time (e.g., a person can move from one affiliation to another). We demonstrate the CHRONOS system which offers users the useful tool for finding real-world entities over time and understanding history of entities in the bibliography domain. The core of CHRONOS is a temporal record-linkage algorithm, which is tolerant to value evolution over time. Our algorithm can obtain an F-measure of over 0.9 in linking author records and fix errors made by DBLP. We show how CHRONOS allows users to explore the history of authors, and how it helps users understand our linkage results by comparing our results with those of existing systems, highlighting differences in the results, explaining our decisions to users, and answering "what-if" questions. © 2012 VLDB Endowment.

Many data sets contain temporal records which span a long period of time; each record is associated with a time stamp and describes some aspects of a real-world entity at a particular time (e. g., author information in DBLP). In such cases, we often wish to identify records that describe the same entity over time and so be able to perform interesting longitudinal data analysis. However, existing record linkage techniques ignore temporal information and fall short for temporal data. This article studies linking temporal records. First, we apply time decay to capture the effect of elapsed time on entity value evolution. Second, instead of comparing each pair of records locally, we propose clustering methods that consider the time order of the records and make global decisions. Experimental results show that our algorithms significantly outperform traditional linkage methods on various temporal data sets. © 2012 Higher Education Press and Springer-Verlag Berlin Heidelberg.

Genetics and Molecular Biology are keys for the understanding the mechanisms of many of the human diseases that have strong harmful effects. The empirical mission of Genetics is to translate these mechanisms into Clinical benefits, thus bridging in-silico findings to patient bed side: approaching this goal means achieving what is commonly referred as clinical genomics or personalized medicine. In this process, technologies are assuming an increasing role. With the introduction of new experimental platforms (microarrays, sequencing, etc), today's analyses are much more detailed and can cover a wide spectrum of applications, from gene expression to Copy Number Variants detection. The advantages of technological improvements are usually followed by data management drawbacks due to the explosion of data throughput that reflects on a real need for new systems of data rationalization and management, data access, query and extraction. Our genetic laboratories partners encountered all those issues: what they need is a tool that allows data-integration and supports biological data analysis exploiting computational infrastructures on distributed environment. From such needs, we defined two main goals: (1) Computer Science goal: to design and implement a framework that integrates and manages data and genetic analyses; (2) Genetics and Molecular Biology goal (application domains): to solve biological problems through the framework and develop new methods. Given these requirements and related specifications, we designed an extensible framework based on three inter-connected layers: (1) Experimental data layer, that provides data integration of data from high-throughput platforms (also called horizontal data integration); (2) Knowledge data layer, that provides data integration of knowledge data (also called vertical integration); (3) Computational layer, that provides access to distributed environments for data analysis, in our cases GRID and Cluster technologies. Above the thre

Service contracts represent the agreement between the service provider and potential service consumers to use a specific service under given conditions; for each service multiple service contracts are available. In this paper we investigate a new approach to support the service contract selection by exploiting preferences both explicitly defined by a user and implicitly inferred from his/her context. The core of our approach is the use of multi-constraint queries expressed on punctual values and on textual descriptions. Both semantic-based and information retrieval (IR) techniques are applied. Experimental evaluations show the effectiveness of the proposed approach

The paper discusses two concepts that have been associated with various approaches to data and information, namely capacity and value, focusing on data base architectures, and on two types of technologies diffusely used in integration projects, namely data integration, in the area of Enterprise Information Integration, and publish & subscribe, in the area of Enterprise Application Integration. Furthermore, the paper proposes and discusses a unifying model for information capacity and value, that considers also quality constraints and run time costs of the data base architecture.

The eighth international workshop on Quality in Database was held in Singapore, on September 13th, 2010 and co-located with the 36th Conference on Very Large DataBase (VLDB). The main objective of the workshop was to address the challenge to detect data anomalies and assess, monitor, improve, and maintain the quality of information. The keynote speech, titled 'SOLOMON: Seeking the Truth Via Copying Detection' was delivered by Xin Luna Dong, AT&T. The author presented the SOLOMON tool that supports the discovery of copying relationships between structured data source to improve data integration features. The goal of 'Deriving Effectiveness Measures for Data Quality Rules' by Lei Jiang, Alex Borgida, Daniele Barone, John Mylopoulos is the evaluation of data quality rules. Peter Yeh, and Colin Puri show in 'Discovering Conditional Functional Dependencies to Detect Data Inconsistencies' an approach that exploits conditional functional dependencies for detecting inconsistencies in data and hence improves data quality.

Many data sets contain temporal records over a long period of time; each record is associated with a time stamp and describes some aspects of a realworld entity at that particular time (e.g., author information in DBLP). In such cases, we often wish to identify records that describe the same entity over time and so be able to enable interesting longitudinal data analysis. However, existing record linkage techniques ignore the temporal information and can fall short for temporal data. This paper studies linking temporal records. First, we apply time decay to capture the effect of elapsed time on entity value evolution. Second, instead of comparing each pair of records locally, we propose clustering methods that consider time order of the records and make global decisions. Experimental results show that our algorithms significantly outperform traditional linkage methods on various temporal data sets.

From a user perspective, data and services provide a complementary view of an information source: data provide detailed information about specific needs, while services execute processes involving data and returning an informative result as well. For this reason, users need to perform aggregated searches to identify not only relevant data, but also services able to operate on them. At the current state of the art such aggregated search can be only manually performed by expert users, who first identify relevant data, and then identify existing relevant services. In this paper we propose a semantic approach to perform aggregated search of data and services. In particular, we define a technique that, on the basis of an ontological representation of both data and services related to a domain, supports the translation of a data query into a service discovery process. In order to evaluate our approach, we developed a prototype that combines a data integration system with a novel information retrieval-based Web Service discovery engine (XIRE). The results produced by a wide set of experiments show the effectiveness of our approach with respect to IR approaches, especially when Web Service descriptions are expressed by means of a heterogeneous terminology. © 2010 Elsevier B.V. All rights reserved.

The vast amount of data available on the Internet introduces new challenging data quality problems, such as accessibility and usability. Low information quality is common in various Web applications, including Web 2.0 tools. Consequently, information quality on the Internet is one of the most crucial requirements for an effective use of data from the Web and pervasive deployment of Web-based applications.

In medium-big enterprise it is quite typical that the database architecture is defined through a sequence of projects and realizations that result a number of different and sometime overlapping data sources. This trend is worsened by merger and acquisition activities that add in existing data archi-tecture new data sources from external organizations. Data fragmentation reduces significantly the possibility to exploit organizational information assets and it needs the building of a data integration architecture. This architecture allows the organization to access to data stored by heterogeneous data sources and to manage updates through a unified view of this data. In this paper we present an original framework able to support the evolution of data architecture by identi-fying the optimal solution that maximize the quality of the overall architecture within a given cost threshold. In partic-ular, we focus on Publish and Subscribe as solution for data architecture. Copyright 2010 ACM.

While several techniques have been introduced for specifying and acquiring context and quality information associated with Web services, they consider such information representing the whole Web services. However, accessing to context and quality of data resources provided by Web services is crucial. This is particularly relevant for data-intensive Web services of which the context and quality of data resources will strongly impact on the service development and composition. In this paper we contribute an analysis of relationships among context, quality, and relevance, as well as their impact on the design and composition of Web services, in particular at the data resource level. Then, we propose several techniques to incorporate context and quality descriptions into REST APIs and RESTful services publishing. By implementing these features, RESTful Web services could allow the consumer to specify and query context and quality information associated with services and data resources, thus fostering the provision of high relevant data resources. © 2010 Springer-Verlag.

The increasing availability of massive information on the Web causes the need for information aggregation by filtering and ranking according to user's goals. In the last years both industrial and academic researchers have investigated the way in which quality of services can be described, matched, composed and monitored for service selection and composition. However, very few of them have considered the problem of evaluating and certifying the quality of the provided service information to reduce irrelevant information for service consumers, which is crucial to improve the efficiency and correctness of service composition and execution. This paper discusses several problems due to the lack of appropriate way to manage quality and context in service composition and execution, and proposes a research roadmap for reducing irrelevant service information based on context and quality aspects. We present a novel solution for dealing with irrelevant information about Web services by developing information quality metrics and by discussing experimental evaluations

In large organizations the database architecture is typically built through a series of projects and realizations that result in a number of heterogeneous and overlapping data sources. This trend is worsened by merger and acquisition activities that add new data sources from external organizations to the existing data architecture. Data fragmentation significantly reduces the possibility for an organization to exploit its information assets. A technology that partially alleviates these problems is data integration middleware that allows users to read-only access data stored in heterogeneous data sources through the presentation of a unified view of these data. In this paper we introduce a new concept to measure the improvement in information capacity enabled by data integration solutions, and propose an original framework which can support the evolution of the organization data architecture by identifying the optimal solution that maximizes such improvement within a given cost threshold.

In this paper we propose a meta-model for non- functional property descriptions targeted to support the se- lection of Web Services. The approach is based on the ex- plicit distinction between NFP offered by providers and re- quested by users, on the concept of policy that aggregates NFP descriptions into single entities with an applicability condition, and finally on a set of constraint operators, which is particularly relevant for NFP requests. The semantic meta-model embracing the above perspective is defined by a BNF syntax whose semantics is formalized by an ontology. The ontology has been formalized in OWL-DL and WSML to provide for logical syntaxes. The logic upon which the meta-model supports NFP-based selection is discussed in the paper.

Web service evaluation is a phase of the Web service selection,in which discovered Web services are evaluated with,respect to user request, which means that the non functional,properties (NFPs) offered by Web services are compared,with the non functional properties requested by users. The,fact that users and providers can express their NFPs in very,flexible ways makes the management of NFPs a very complex,task. In this paper we propose a computing-oriented,description of NFPs and a novel approach to NFP-based,service evaluation based on Hierarchical Constraint Logic,Programming. This proposal extends our previous work on,Policy Centered Meta-model (PCM) [2]. © 2009 IEEE.

Web service evaluation is a phase in Web service selection where discovered Web services are evaluated with respect to user requests, which means that the non functional properties (NFPs) offered by Web services are compared with the non functional properties requested by users. NFPs cover Quality of Service (QoS) aspects, but also other business-related properties, such as pricing, and properties not directly related to the service functionalities. The fact that users and providers can express their NFPs in very flexible ways makes the management of NFP a very complex task. The Policy Centered Meta-model (PCM) is a semantic-oriented model for sophisticated NFP descriptions that can be exploited to support Web service evaluation. In this paper, we propose a novel approach based on Hierarchical Constraint Logic Programming to handle PCM-based NFP descriptions along the Web service evaluation phase. © 2009 IEEE.

The increasing availability of data and eServices on the Web allows users to search for relevant information and to perform operations through eServices. Current technologies do not support users in the execution of such activities as a unique task; thus users have first to find interesting information, and then, as a separate activity, to find and use eServices. In this paper we present a framework able to query an integrated view of heterogeneous data and to search for eServices related to retrieved data. A unified view of data and semantically described eServices is the way in which it is possible to unify data and service perspectives. © 2009 Springer-Verlag Berlin Heidelberg.

The literature provides a wide range of techniques to assess and improve the quality of data. Due to the diversity and complexity of these techniques, research has recently focused on defining methodologies that help the selection, customization, and application of data qualityassessment and improvement techniques. The goal of this article is to provide a systematic and comparative description of suchmethodologies. Methodologies are compared along several dimensions, including the methodological phases and steps, the strategies and techniques, the data quality dimensions, the types of data, and, finally, the types of information systems addressed by each methodology. The article concludes with a summary description of each methodology.

The wide diffusion of ICTs has unchained subsequent waves of expectations about how the new ways of communicating and ex- changing information and knowledge would affect inter-firm relation- ships, hopefully improving their performance. However, facts often down- sized expectations. Even the so called Web revolution did not solve above mentioned issues. In fact the adoption of Internet-based tools by many SMEs have still limited to the Internet access, e-mail and static company Web sites only. Today the new frontier is the adoption of peer-to-peer approach and semantic-based technologies such as semantic Web ser- vices and ontologies. However, a crucial node for the future development of peer-to-peer semantic networks is understanding if, and eventually how, software architectures based on those concepts can create economic value for all network members. This paper presents relevant issues in the provisioning of electronic services in peer-to-peer environments and proposes preliminary solutions under developing in the context of the NeP4B (Network Peers for Business) project

The Semantic Web Service Challenge is one of the major ini- tiative dedicated to work on Semantic Web Service (SWS) discovery and selection. It represents an e®ective manner for evaluating the functional- ity of SWS technologies. In this paper, we provide a new SWS-Challenge scenario proposal with new interesting problems to be solved on the basis of an analysis of a real world shipment scenario in the logistic operators domain. In the discussion a number of aspects concerning the discovery and selection processes are emphasized. In particular, we focus on the problem of considering the heterogeneity between the provider and the requester perspectives, and on the di®erences between functional and non functional speci-cations both on the requester and provider side. Key words: Semantic Web Services Discovery, Semantic Web Services Selection, Non-functional properties, Semantic Matching, SWS-Challenge.

The increasing availability of Web Services asked for investigating ways to automate the discovery process. Discovery processes enhanced with semantics can be recognize to be general, but often they lack the flexibility needed in specific domains. In this paper, we propose the flexible architecture of the discovery engine Glue 2, which comes with a powerful set of discovery components (for functional matching, non-functional matching, data fetching, etc.) that can be executed in different order as required by specific execution workflows. © 2008 IEEE.

The proceedings contain 8 papers. The topics discussed include: analysis of non-functional service properties for transactional workflow management; flexible service offering with semantic policies; an SLA re-negotiation protocol; a taxonomy-driven approach for performance measurement and modelling in service oriented architectures; a service ranker based on logic rules evaluation and constraint programming; on reconciliation of contractual concerns of web services; non-functional property based service selection: a survey and classification of approaches; and context-aware service selection using graph matching.

Data quality (DQ) is emerging as a new relevant area for the improvement of the effectiveness of organizations. Despites the consequences of poor quality of data are often experienced in everyday life of enterprises, very few organizations adopt specific methodologies for assessing and monitoring quality of their data. In this paper we present the first results of an Italian project whose goal is to produce an enhanced version of well known approaches to Basel II operational risk evaluation, with a significant relevance to information and data quality, and its effects on operational risk. In particular in this paper we focus on the definition of an assessment methodology and a supporting tool for DQ.

BPEL only supports a strictly centralized and coordinated execution of Web service compositions, but this solution is clearly not the best option in many concrete cases. The conceptually monolithic BPEL process should be executed in a distributed setting, where each peer is only responsible for a fraction of the whole process and for the coordination with the other fragments. These considerations lead us to propose a formal approach to support the distributed execution of BPEL processes. The partitioning is customizable and easily intertwines with the adoption of special-purpose middleware infrastructures. In particular, the paper shows how we pair the distributed execution with a tuple-based infrastructure, to support distributed execution in mobile contexts, and with a publish and subscribe middleware, to support dynamically changing scenarios. Copyright © (2007) by Knowledge Systems Institute (KSI).

Multichannel Adaptive Information Systems (ISs) are becoming the new paradigm for building complex interorganization ISs based on the use of different devices, Web services, and XML specifications. Modeling Multichannel Adaptive ISs requires complex interactions between the users and the system front-end due to the different capabilities of existing devices. Unfortunately, the expressive power and effectiveness of visual languages have not been fully exploited in this new area. In this paper we address two related issues. First we propose a visual language that allows for adapting the presentation layer to different physical devices; then we describe a technique to evaluate possible tradeoffs between usability and other qualities of service in Web services design. (c) 2007 Elsevier Ltd. All rights reserved.

Multichannel Adaptive Web Information Systems (WISs) are emerging as a new class of information systems, characterized by their powerful use of mobility and context-awareness. Different methodologies have been proposed so far for the analysis and design of Multichannel Adaptive WISs, specifically focused on the front-end layer or the back-end layer, but no methodology has aimed to cover all the lifecycle and to design all the components that characterize Multichannel Adaptive WIS. This paper fills such a gap, by presenting UM-MAIS (Unified Methodology for Multichannel Adaptive Information Systems), a new methodology that capitalizes on well-established existing methods. It supports the analysis and design of the various components of Multichannel Adaptive WISs (including the user's experience) in a comprehensive and unified manner with special emphasis on context modeling, personalization, and adaptation.

Web services are increasingly used as an effective means to create and streamline processes and collaborations among governments, businesses, and citizens. As the number of available Web services is steadily increasing, there is a growing interest in providing methodologies that address the design of Web services according to specific qualities of service (QoS) rather than functional descriptions only. In this paper, we present WSMoD (Web Services MOdeling Design), a methodology that explicitly addresses this issue. Furthermore, we exploit general knowledge available on services, expressed by ontologies describing services, their qualities, and the context of use, to help the designer in expressing service requirements. Ontologies are used to acquire knowledge among the entities involved in service design and to check the consistency of the Web service. The discussion of a QoS-based Web service design within a real case study bears evidence of the potentials of WSMoD.