Computing Changesets for RDF Views of Relational Data (original) (raw)

Framework for Live Synchronization of RDF Views of Relational Data

2017

This Demo presents a framework for the live synchronization of an RDF view defined on top of relational database. In the proposed framework, rules are responsible for computing and publishing the changeset required for the RDB-RDF view to stay synchronized with the relational database. The computed changesets are then used for the incremental maintenance of the RDB_RDF views as well as application views. The Demo is based on the LinkedBrainz Live tool, developed to validate the proposed framework.

Incremental Maintenance of RDF Views of Relational Data

Lecture Notes in Computer Science, 2013

A general and flexible way to publish relational data in RDF format is to create RDF views of the underlying relational data. In this paper, we demonstrate a framework, based on rules, for the incremental maintenance of RDF views defined on top of relational data. We also demonstrate a tool that automatically generates, based on the mapping between the relational schema and a target ontology, the RDF view exported from the relational data source and all rules required for the incremental maintenance of the RDF view.

A Framework for Incremental Maintenance of RDF Views of Relational Data

International Semantic Web Conference, 2014

Transient and persistent RDF views over relational databases in the context of digital repositories

2013

As far as digital repositories are concerned, numerous benefits emerge from the disposal of their contents as Linked Open Data (LOD). This leads more and more repositories towards this direction. However, several factors need to be taken into account in doing so, among which is whether the transition needs to be materialized in real-time or in asynchronous time intervals. In this paper we provide the problem framework in the context of digital repositories, we discuss the benefits and drawbacks of both approaches and draw our conclusions after evaluating a set of performance measurements. Overall, we argue that in contexts with infrequent data updates, as is the case with digital repositories, persistent RDF views are more efficient than real-time SPARQL-to-SQL rewriting systems in terms of query response times, especially when expensive SQL queries are involved.

Proactive Replication of Dynamic Linked Data for Scalable RDF Stream Processing

2016

In this paper, we propose a scalable method of proactively replicating a subset of remote datasets for RDF Stream Processing. Our solution achieves a fast query processing by maintaining the replicated data up-to-date before query evaluation. To construct the replication process effectively, we present an update estimation model to handle the changes in updates over time. With the update estimation model, we re-construct the replication process in response to the outdated data. Finally, we conduct exhaustive tests with a real-world dataset to verify our solution.

Incremental Maintenance of Materialized SPARQL-Based Linkset Views

Lecture Notes in Computer Science, 2016

In the Linked Data field, data publishers frequently materialize linksets between two different datasets using link discovery tools. To create a linkset, such tools typically execute linkage rules that retrieve data from the underlying datasets and apply matching predicates to create the links, in an often complex process. Also, such tools do not support linkset maintenance, when the datasets are updated. A simple, but costly strategy to maintain linksets up-todate would be to fully re-materialize them from time to time. This paper presents an alternative strategy, called incremental, for maintaining linksets, based on idea that one should re-compute only the links that involve the updated resources. The paper discusses in detail the incremental strategy, outlines an implementation and describes an experiment to compare the performance of the incremental strategy with the full re-materialization of linksets.

Consistent RDF Updates with Correct Dense Deltas

Lecture Notes in Computer Science, 2015

RDF is widely used in the Semantic Web for representing ontology data. Many real world RDF collections are large and contain complex graph relationships that represent knowledge in a particular domain. Such large RDF collections evolve in consequence of their representation of the changing world. Although this data may be distributed over the Internet, it needs to be managed and updated in the face of such evolutionary changes. In view of the size of typical collections, it is important to derive efficient ways of propagating updates to distributed data stores. The contribution of this paper is a detailed analysis of the performance of RDF change detection techniques. In addition the work describes a new approach to maintaining the consistency of RDF by using knowledge embedded in the structure to generate efficient update transactions. The evaluation of this approach indicates that it reduces the overall update size at the cost of increasing the processing time needed to generate the transactions.. . .

RDFSync: Efficient Remote Synchronization of RDF Models

2007

In this paper we describe RDFSync, a methodology for efficient synchronization and merging of RDF models. RDFSync is based on decomposing a model into Minimum Self-Contained graphs (MSGs). After illustrating theory and deriving properties of MSGs, we show how a RDF model can be represented by a list of hashes of such information fragments. The synchronization procedure here described is based on the evaluation and remote comparison of these ordered lists. Experimental results show that the algorithm provides very significant savings on network traffic compared to the fileoriented synchronization of serialized RDF graphs. Finally, we provide the design and report the implementation of a protocol for executing the RDFSync algorithm over HTTP.

RDFS update: from theory to practice

The Semanic Web: Research and Applications, 2011

There is a comprehensive body of theory studying updates and schema evolution of knowledge bases, ontologies, and in particular of RDFS. In this paper we turn these ideas into practice by presenting a feasible and practical procedure for updating RDFS. Along the lines of ontology evolution, we treat schema and instance updates separately, showing that RDFS instance updates are not only feasible, but also deterministic. For RDFS schema update, known to be intractable in the general abstract case, we show that it becomes feasible in real world datasets. We present for both, instance and schema update, simple and feasible algorithms.

UnifiedViews: An ETL tool for RDF data management

Semantic Web, 2018

We present UnifiedViews, an Extract-Transform-Load (ETL) framework that allows users to define, execute, monitor, debug, schedule, and share data processing tasks, which may employ custom plugins (data processing units) created by users. UnifiedViews natively supports processing of RDF data. In this paper, we: (1) introduce Unified-Views' basic concepts and features, (2) demonstrate the maturity of the tool by presenting exemplary projects where UnifiedViews is successfully deployed, and (3) outline research projects and future directions in which UnifiedViews is exploited. Based on our practical experience with the tool, we found that UnifiedViews simplifies the creation and maintenance of Linked Data publication processes.

Computing Changesets for RDF Views of Relational Data (original) (raw)

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