Introducing Dynamic Behavior in Amalgamated Knowledge Bases

The problem of integrating knowledge from multiple and heterogeneous sources is a fundamental issue in current information systems. In order to cope with this problem, the concept of mediator has been introduced as a software component providing intermediate services, linking data resources and application programs, and making transparent the heterogeneity of the underlying systems. In designing a mediator architecture, we believe that an important aspect is the definition of a formal framework by which one is able to model integration according to a declarative style. To this purpose, the use of a logical approach seems very promising. Another important aspect is the ability to model both static integration aspects, concerning query execution, and dynamic ones, concerning data updates and their propagation among the various data sources. Unfortunately, as far as we know, no formal proposals for logically modeling mediator architectures both from a static and dynamic point of view have already been developed. In this paper, we extend the framework for amalgamated knowledge bases, presented by Subrahmanian, to deal with dynamic aspects. The language we propose is based on the Active U-Datalog language, and extends it with annotated logic and amalgamation concepts. We model the sources of information and the mediator (also called supervisor) as Active U-Datalog deductive databases, thus modeling queries, transactions, and active rules, interpreted according to the PARK semantics. By using active rules, the system can efficiently perform update propagation among different databases. The result is a logical environment, integrating active and deductive rules, to perform queries and update propagation in an heterogeneous mediated framework.Comment: Other Keywords: Deductive databases; Heterogeneous databases; Active rules; Update

Context Aware Source Selection for Linked Data

The traditional Web is evolving into the Web of Data, which gathers huge collections of structured data over distributed, heterogeneous data sources. Live queries are needed to get current information out of this global data space. In live query processing, source selection allows the identification of the sources that most likely contain relevant content. Due to the semantic heterogeneity of the Web of Data, however, it is not always easy to assess relevancy. Context information might help in interpreting the user\u2019s information needs. In this paper, we discuss how context information can be exploited to improve source selection

Recurring retrieval needs in diverse and dynamic dataspaces: Issues and reference framework

Processing information requests over heterogeneous data spaces is very challenging because aimed at guaranteeing user satisfaction with respect to conflicting requirements on result quality and response time. In [3], it has been argued that, in dynamic contexts pre-venting substantial user involvement in interpreting requests, information on similar requests recurring overtime can be exploited during query processing. In this paper, referring to a graph-based modeling of dataspaces and requests, we propose a preliminary approach in this direction centered on the enabling concept of Profiled Graph Query Pattern (PGQP) as an aggregation of information on past evaluations of a set of previously executed queries. The information maintained in PGQP is not query results, as in materialized queries, but can include different kinds of data and metadata

Holistic Nursing of Forensic Patients: A Focus on Spiritual Care

Prisons are a unique context where nurses are required to have specific skills to ensure that prisoners receive the same type of holistic care as anyone else out of prison, including spiritual care. This discussion paper focuses on understanding how nurses deliver spiritual care in Italian prisons where there are often limited resources and where organizational priorities hinder the provision of holistic nursing. This paper draws from a previous qualitative research study that we had conducted. In this study, we observed that prison nurses reported that they experienced many difficulties related to the provision of holistic care to prisoners. This was particularly true for spiritual care in vulnerable forensic patients, such as older individuals, and physically and mentally frail prisoners. Prison officers did not allow nurses to just "listen and talk" to their patients in prison, because they considered it a waste of time. The conflict between prison organizational constraints and nursing goals, along with limited resources placed barriers to the development of therapeutic relationships between nurses and prisoners, whose holistic and spiritual care needs remained totally unattended. Therefore, prison organizational needs prevailed over prisoners' needs for spiritual care, which, while fundamental, are nevertheless often underestimated and left unattended. Educational interventions are needed to reaffirm nurses' role as providers of spiritual care

The role of geographic knowledge in sub-city level geolocation

Geolocation of microblog messages has been largely investigated in the literature. Many solutions have been proposed that achieve good results at the city level. Existing approaches are mainly data-driven (i.e., they rely on a training phase). However, the development of algorithms for geolocation at sub-city level is still an open problem. In this paper, we investigate the role that external geographic knowledge can play in geolocation approaches. We show how different geographical data sources can be combined with a semantic layer within a knowledge base to achieve reasonably accurate sub-city level geolocation