International audience

Informal care is fundamental in the wellbeing and resilience of elderly and people with chronic conditions. However, solutions for the effective collaboration of healthcare professionals, patients and informal carers are not yet widely available. CareKeeper builds on a state-of-the-art personal health system, augmenting it with Artificial Intelligence and Big Data technologies, to boost informal care coordination. In this paper we report on the design of the platform with the aim of providing a light-weighted communication solution to support practical challenges about sharing the responsibility of caring, such as the frequency of visits, support to routinely activities and timely intervention in case of emergency and need.

The evaluation of SPARQL algebra queries on various kinds of annotated RDF graphs can be seen as a particular case of the evaluation of these queries on RDF graphs annotated with elements of so-called spm-semirings . Spm-semirings extend semirings, used for representing the provenance of positive relational algebra queries on annotated relational data, with a new operator to capture the semantics of the non-monotone SPARQL operators. Furthermore, spm-semiring-based annotations ensure that desired SPARQL query equivalences hold when querying annotated RDF. In this work, in addition to introducing spm-semirings, we study their properties and provide an alternative characterization of these structures in terms of semirings with an embedded boolean algebra (or seba-structure for short). This characterization allows us to construct spm-semirings and identify a universal object in the class of spm-semirings. Finally, we show that this universal object provides a provenance representation of poly-sized overhead and can be used to evaluate SPARQL queries on arbitrary spm-semiring-annotated RDF graphs.

We show that the evaluation of SPARQL algebra queries on various notions of annotated RDF graphs can be seen as particular cases of the evaluation of these queries on RDF graphs annotated with elements of so-called spm-semirings. Spm-semirings extend semirings, used for positive relational algebra queries on annotated relational data, with a new operator to capture the semantics of the non-monotone SPARQL operator OPTIONAL. Furthermore, spm-semiring-based annotations ensure that desired SPARQL query equivalences hold when querying annotated RDF. In addition to introducing spm-semirings, we study their properties and provide an alternative characterization of these structures in terms of semirings with an embedded boolean algebra (or seba-structure for short). This characterization allows to construct spm-semirings and to identify a universal object in the class of spm-semirings. Finally, we show that this universal object provides a concise provenance representation and can be used to evaluate SPARQL queries on arbitrary spm-semiring-annotated RDF graphs.

With the increasing use of Web 2.0 to create, disseminate, and consume large volumes of data, more and more information is published and becomes available for potential data consumers, that is, applications/services, individual users and communities, outside their production site. The most representative example of this trend is Linked Open Data (LOD), a set of interlinked data and knowledge bases. The main challenge in this context is data governance within loosely coordinated organizations that are publishing added-value interlinked data on the Web, bringing together issues related to data management and data quality, in order to support the full lifecycle of data production, consumption, and management. In this article, we are interested in curation issues for RDF(S) data, which is the default data model for LOD. In particular, we are addressing change management for RDF(S) data maintained by large communities (scientists, librarians, etc.) which act as curators to ensure high quality of data. Such curated Knowledge Bases (KBs) are constantly evolving for various reasons, such as the inclusion of new experimental evidence or observations, or the correction of erroneous conceptualizations. Managing such changes poses several research problems, including the problem of detecting the changes (delta) between versions of the same KB developed and maintained by different groups of curators, a crucial task for assisting them in understanding the involved changes. This becomes all the more important as curated KBs are interconnected (through copying or referencing) and thus changes need to be propagated from one KB to another either within or across communities. This article addresses this problem by proposing a change language which allows the formulation of concise and intuitive deltas. The language is expressive enough to describe unambiguously any possible change encountered in curated KBs expressed in RDF(S), and can be efficiently and deterministically detected in an automated way. Moreover, we devise a change detection algorithm which is sound and complete with respect to the aforementioned language, and study appropriate semantics for executing the deltas expressed in our language in order to move backwards and forwards in a multiversion repository, using only the corresponding deltas. Finally, we evaluate through experiments the effectiveness and efficiency of our algorithms using real ontologies from the cultural, bioinformatics, and entertainment domains.

Query optimization in RDF Stores is a challenging problem as SPARQL queries typically contain many more joins than equivalent relational plans, and hence lead to a large join order search space. In such cases, cost-based query optimization often is not possible. One practical reason for this is that statistics typically are missing in web scale setting such as the Linked Open Datasets (LOD). The more profound reason is that due to the absence of schematic structure in RDF, join-hit ratio estimation requires complicated forms of correlated join statistics; and currently there are no methods to identify the relevant correlations beforehand. For this reason, the use of good heuristics is essential in SPARQL query optimization, even in the case that are partially used with cost-based statistics (i.e., hybrid query optimization). In this paper we describe a set of useful heuristics for SPARQL query optimizers. We present these in the context of a new Heuristic SPARQL Planner (HSP) that is capable of exploiting the syntactic and the structural variations of the triple patterns in a SPARQL query in order to choose an execution plan without the need of any cost model. For this, we define the variable graph and we show a reduction of the SPARQL query optimization problem to the maximum weight independent set problem. We implemented our planner on top of the MonetDB open source column-store and evaluated its effectiveness against the state-of-the-art RDF-3X engine as well as comparing the plan quality with a relational (SQL) equivalent of the benchmarks.

The Resource Description Framework (RDF) has become the defacto standard for representing information in the Semantic Web. Given the increasing amount of sensitive RDF data available on the Web, it becomes increasingly critical to guarantee secure access to this content. In this paper we advocate the use of an abstract access control model to ensure the selective exposure of RDF information. The model is defined by a set of abstract operators and tokens. Tokens are used to label RDF triples with access information. Abstract operators model RDF Schema inference rules and propagation of labels along the RDF Schema(RDFS) class and property hierarchies. In this way, the access label of a triple is a complex expression that involves the labels of the triples and the operators applied to obtain said label. Different applications can then adopt different concrete access policies that encode an assignment of the abstract tokens and operators to concrete (specific) values. Following this approach, changes in the interpretation of abstract tokens and operators can be easily implemented resulting in a very flexible mechanism that allows one to easily experiment with different concrete access policies (defined per context or user). To demonstrate the feasibility of the approach, we implemented our ideas on top of the MonetDB and PostgreSQL open source database systems. We conducted an initial set of experiments which showed that the overhead for using abstract expressions is roughly linear to the number of triples considered; performance is also affected by the characteristics of the dataset, such as the size and depth of class and property hierarchies as well as the considered concrete policy.

XML access control policies involving updates may contain security flaws, here called inconsistencies, in which a forbidden operation may be simulated by performing a sequence of allowed operations. ACCOn implements i) consistency checking algorithms that examine whether a write-access control policy defined over a DTD is inconsistent and ii) repair algorithms that propose repairs to an inconsistent policy to obtain a consistent one.

XML search is increasing in popularity as more and larger XML repositories are becoming available. The accuracy of XML search varies across different systems and a lot of effort is put into designing scoring functions tailored to specific users and datasets. We argue that there is no one scoring function that fits all and advocate incorporating user profiles into XML search to personalize query answers by accounting for user profiles. First, we propose a framework for defining user profiles and for enforcing them during query processing. Second, we adapt the well-known top-k pruning to account for user profiles. Finally, we present effectiveness and efficiency experiments which show that query personalization in XML search dramatically improves the accuracy of query results while incurring negligible processing overhead. This work is in the context of the Pimento project which aims at improving the relevance of searching structured and unstructured content.

Several languages have been proposed over the past years which support the specification of access control on XML data. Most of these languages consider read-access restrictions only and do not deal with access rights for updates(such as add, delete, or modify operations). Fine-grain XML update operations are subject to current research. This paper proposes XACU, a language for specifying access control on XML data in the presence of update operations. The update operations used in XACU are based on the W3CX Query Update Facility working draft. A formal access control model is defined which allows to study properties of XACU access policies. One essential property is consistency the policy should not allow the execution of a sequence of updates which has the same total effect as an update forbidden by the policy. Since XACU is a rich language with inherent ambiguities, checking consistency of a set of XACU rules is difficult, and undecidable in general.

The web services paradigm holds the promise of tremendous flexibility in how services are combined to meet the needs of individual end-users. The “convergence” of networks (wireline telephony, wireless, data) further enhances the web services paradigm, by enabling the incorporation of real time contextual information (e.g., presence and location) along with opportunities for web services to impact the physical world more immediately (e.g., a vending machine delivering a soda based on a purchase via a cell phone). But it will not be possible for most end-users to enjoy the rich and intricate possibilities, unless a broad variety of personalization technologies are available and respect the end user’s legitimate need for privacy. This seminar begins with examples illustrating why personalization will be so important for the emerging web and converged services. The main body of the seminar focuses on 3 inter-related technologies. First is profile data management, the ability for services to share and access end-user profile data (including address, credit card, “simple” preferences, current location, current presence, ...) as appropriate for the services to be provided. Second is preference and policy management, the ability to store and execute on intricate, interrelated preferences that end-users may have (e.g., “during working hours, calls from strangers should be routed to voice-mail”; “I usually work from 9 to 6, but on Thursdays it is from 8 to 4”; ...). And third is personalized and privacy-conscious data sharing of profile data and preferences, the notion that an end-user should have complete control over what profile and preference data is shared with whom and under what circumstances and how it is interpreted. In addition to describing emerging approaches for providing these capabilities, the seminar will describe how to add value to applications by using personalization, from both the end-user and the application provider perspectives.

Access control for XML documents is a non-trivial topic, as can be witnessed from the number of approaches presented in the literature. Trying to compare these, we discovered the need for a simple, clearand unambiguous language to state the declarative semantics of an access control policy. All current approaches state the semantics in natural language, which has none of the above properties. This makes it hard to assess whether the proposed algorithms are correct (i.e., really implement the described semantics). It is also hard to assess the proposed policy on its merits, and to compare it to others (for file systems for instance). This paper shows how XPath can be used to specify the semantics of an access control policy for XML documents. Using XPath has great advantages: it is standard technology, widely used and it has clear and easy syntax and semantics. We use the developed framework to give a formal specification of the five most prominent approaches of access controlfor XML documents from the literature.

No abstract available.