Distributed Semantic Wiki: Kolflow Project -Task 5- State of the art (D5.1)

This paper presents the state of the art on Distributed Semantic Wikis. This work is part of the Kolflow project, more precisely it is part of the task 5, {\bf D(5.1)}

Efficient Query Processing for SPARQL Federations with Replicated Fragments

Low reliability and availability of public SPARQL endpoints prevent real-world applications from exploiting all the potential of these querying infras-tructures. Fragmenting data on servers can improve data availability but degrades performance. Replicating fragments can offer new tradeoff between performance and availability. We propose FEDRA, a framework for querying Linked Data that takes advantage of client-side data replication, and performs a source selection algorithm that aims to reduce the number of selected public SPARQL endpoints, execution time, and intermediate results. FEDRA has been implemented on the state-of-the-art query engines ANAPSID and FedX, and empirically evaluated on a variety of real-world datasets

Causal Broadcast: How to Forget?

Causal broadcast constitutes a fundamental communication primitive of many distributed protocols and applications. However, state-of-the-art implementations fail to forget obsolete control information about already delivered messages. They do not scale in large and dynamic systems. In this paper, we propose a novel implementation of causal broadcast. We prove that all and only obsolete control information is safely removed, at cost of a few lightweight control messages. The local space complexity of this protocol does not monotonically increase and depends at each moment on the number of messages still in transit and the degree of the communication graph. Moreover, messages only carry a scalar clock. Our implementation constitutes a sustainable communication primitive for causal broadcast in large and dynamic systems

Optimistic Replication for Massive Collaborative Editing

In recent times, Wikipedia has opened the way to massive collaborative editing. More specifically, it has demonstrated what can be achieved with a massive collaborative effort. Massive collaborative editing implies scalability and pessimistic replication scales poorly in the wide area. Optimistic replication offers better performance but has severe drawbacks for maintaining consistency. In this paper, we propose a new optimistic replication algorithm for massive collaborative editing called WOOT. It is designed to scale as well as to ensure eventual consistency and intention preservation. It is important to point out that WOOT's efficiency does not depend on a number of sites and can be deployed on a very large, pure peer-to-peer network

Safe Generic Data Synchronizer

Rapport interne.Reconciliating divergent data is an important issue in concurrent engineering, mobile computing and software configuration management. Actually, a lot of synchronizers or merge tools perform reconciliations, however, which strategy they apply ? is it correct ? In this paper, we propose to use a transformational approach to build a safe generic data synchronizer

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

BlueFinder: Recommending Wikipedia Links Using DBpedia Properties

International audienceDBpedia knowledge base has been built from data extracted from Wikipedia. However, many existing relations among resources in DBpedia are missing links among articles from Wikipedia. In some cases, adding these links into Wikipedia will enrich Wikipedia content and therefore will enable bet- ter navigation. In previous work, we proposed PIA algorithm that predicts the best link to connect two articles in Wikipedia corresponding to those related by a semantic property in DB- pedia and respecting the Wikipedia convention. PIA calcu- lates this link as a path query. After introducing PIA results in Wikipedia, most of them were accepted by the Wikipedia community. However, some were rejected because PIA pre- dicts path queries that are too general. In this paper, we report the BlueFinder collaborative filtering algorithm that fixes PIA miscalculation. It is sensible to the specificity of the resource types. According to the conducted experimentation we found out that BlueFinder is a better solution than PIA because it solves more cases with a better recall

PFed: Recommending Plausible Federated SPARQL Queries

International audienceFederated SPARQL queries allow to query multiple inter-linked datasets hosted by remote SPARQL endpoints. However, finding federated queries over a growing number of datasets is challenging. In this paper, we propose PFed, an approach to recommend plausible fed-erated queries based on real query logs of different datasets. The problem is not to find similar federated queries, but plausible complementary queries over different datasets. Starting with a real SPARQL query from a given log, PFed stretches the query with real queries from different logs. To prune the research space, PFed proposes semantic summary to prune the query logs. Experimental results with real logs of DBpedia and SWDF demonstrate that PFed is able to prune drastically the logs and recommend plausible federated queries

Real time group editors without Operational transformation

A real time group editor allows multiple users to edit the same text at the same time from multiple sites across Internet. The real time group editors community has developed a framework called Operational Transformation (OT) for maintaining consistency of shared data. OT differs from other optimistic replication systems by not only ensuring content consistency but also intention consistency. In this paper, we describe the WOOT (WithOut Operational Transformation) framework that ensures intention consistency without following the OT approach. However, thanks to its new viewpoint, WOOT is drastically simpler, more efficient and does not require vector clocks or central sites. The WOOT framework is particularly adapted to very large peer-to-peer networks