Tracking Federated Queries in the Linked Data

Federated query engines allow data consumers to execute queries over the federation of Linked Data (LD). However, as federated queries are decomposed into potentially thousands of subqueries distributed among SPARQL endpoints, data providers do not know federated queries, they only know subqueries they process. Consequently, unlike warehousing approaches, LD data providers have no access to secondary data. In this paper, we propose FETA (FEderated query TrAcking), a query tracking algorithm that infers Basic Graph Patterns (BGPs) processed by a federation from a shared log maintained by data providers. Concurrent execution of thousand subqueries generated by multiple federated query engines makes the query tracking process challenging and uncertain. Experiments with Anapsid show that FETA is able to extract BGPs which, even in a worst case scenario, contain BGPs of original queries

Personal Linked Data: A Solution to Manage User's Privacy on the Web

National audienceWhile using modern applications, personal digital data is spread over hundreds of servers all around the world and users have very poor control over these data. To tackle this issue, based on the semantic Web, we are developing a framework, named Privacy-Lookout, to allow people to be on the lookout for transgressions of their personal data privacy. Concretely, we propose to construct a personal linked data view of individuals to organize and semantically enrich the meta information of their personal data existing in the Web. The mean idea is to allow users to know if the information the Web posses about them respects their privacy principles. This paper introduces the first ideas of such approach

FETA: Federated QuEry TrAcking for Linked Data

International audienceFollowing the principles of Linked Data (LD), data providers are producing thousands of interlinked datasets in multiple domains including life science, government, social networking, media and publications. Federated query engines allow data consumers to query several datasets through a federation of SPARQL endpoints. However, data providers just receive subqueries resulting from the decomposition of the original federated query. Consequently, they do not know how their data are crossed with other datasets of the federation. In this paper, we propose FETA, a Federated quEry TrAcking system for LD. We consider that data providers collaborate by sharing their query logs. Then, from a fed-erated log, FETA infers Basic Graph Patterns (BGPs) containing joined triple patterns, executed among endpoints. We experimented FETA with logs produced by FedBench queries executed with Anapsid and FedX federated query engines. Experiments show that FETA is able to infer BGPs of joined triple patterns with a good precision and recall

A License-Based Search Engine

International audienceThe reuse of licensed resources to produce new ones is very common and encouraged on the Web. But producing resources whose licenses are compliant with all reused resource licenses is not easy. It is necessary to know (1) the set of licenses with which the license of the produced resource is compliant and (2) what are the available resources whose licenses are part of this set. With CaLi, we provide an answer to the first concern. CaLi is a lattice-based model that partially orders licenses in terms of compatibility and compliance. In this demonstration, we illustrate the usability of CaLi through a prototype for the second concern. That is, based on a CaLi ordering of licenses we implement a license-based search engine which can answer questions such as "find licensed resources that can be reused under a given license" or "find licensed resources that can reuse a resource that has a particular license"

Working Modes with a Declarative Modeler

International audienceThis paper presents the point of view of a designer about declarative modelers. We propose a model of this point of view. Our approach is based on the work we have done to develop some of our declarative modelers. It takes into account the main functions used by a designer in these modelers. We explain also the scene-building process and we present working processes that can be used with those modelers

Collaborative Knowledge Acquisition under Control of a Non-Regression Test System

14 pagesInternational audienceThis paper introduces BeGoood, a generic system for man- aging non-regression tests on knowledge-bases. BeGoood is a system al- lowing to define test plans in order to monitor the evolution of knowledge- bases. Any system answering queries by providing results in the form of set of strings can be tested with BeGoood. BeGoood has been devel- oped following a REST architecture and is independent of any applica- tion domain. This paper describes the architecture of the system and gives a use case to illustrate how BeGoood is able to manage a collab- orative knowledge evolution in the framework of a case-based reasoning system

Extracting Basic Graph Patterns from Triple Pattern Fragment Logs

The Triple Pattern Fragment (TPF) approach is de-facto a new way to publish Linked Data at low cost and with high server availability. However, data providers hosting TPF servers are not able to analyze the SPARQL queries they execute because they only receive and evaluate queries with one triple pattern. In this paper, we propose LIFT: an algorithm to extract Basic Graph Patterns (BGPs) of executed queries from TPF server logs. Experiments show that LIFT extracts BGPs with good precision and good recall generating limited noise

Policies Composition Based on Data Usage Context

International audienceIn federated query processing, different datasets can be queried simultaneously. Each dataset has different privacy policies attached, but,which privacy policy will govern the usage of the query result? In this work we propose a mechanism, based on semantic web technologies, tocompose privacy policies. The originality of our approach is that our composition rules are based on the data usage context and deduced implicitterms