2,958 research outputs found
Interest-based RDF Update Propagation
Many LOD datasets, such as DBpedia and LinkedGeoData, are voluminous and
process large amounts of requests from diverse applications. Many data products
and services rely on full or partial local LOD replications to ensure faster
querying and processing. While such replicas enhance the flexibility of
information sharing and integration infrastructures, they also introduce data
duplication with all the associated undesirable consequences. Given the
evolving nature of the original and authoritative datasets, to ensure
consistent and up-to-date replicas frequent replacements are required at a
great cost. In this paper, we introduce an approach for interest-based RDF
update propagation, which propagates only interesting parts of updates from the
source to the target dataset. Effectively, this enables remote applications to
`subscribe' to relevant datasets and consistently reflect the necessary changes
locally without the need to frequently replace the entire dataset (or a
relevant subset). Our approach is based on a formal definition for
graph-pattern-based interest expressions that is used to filter interesting
parts of updates from the source. We implement the approach in the iRap
framework and perform a comprehensive evaluation based on DBpedia Live updates,
to confirm the validity and value of our approach.Comment: 16 pages, Keywords: Change Propagation, Dataset Dynamics, Linked
Data, Replicatio
Use-cases on evolution
This report presents a set of use cases for evolution and reactivity for data in the Web and
Semantic Web. This set is organized around three different case study scenarios, each of them
is related to one of the three different areas of application within Rewerse. Namely, the scenarios
are: “The Rewerse Information System and Portal”, closely related to the work of A3
– Personalised Information Systems; “Organizing Travels”, that may be related to the work
of A1 – Events, Time, and Locations; “Updates and evolution in bioinformatics data sources”
related to the work of A2 – Towards a Bioinformatics Web
Co-evolution of RDF Datasets
Linking Data initiatives have fostered the publication of large number of RDF
datasets in the Linked Open Data (LOD) cloud, as well as the development of
query processing infrastructures to access these data in a federated fashion.
However, different experimental studies have shown that availability of LOD
datasets cannot be always ensured, being RDF data replication required for
envisioning reliable federated query frameworks. Albeit enhancing data
availability, RDF data replication requires synchronization and conflict
resolution when replicas and source datasets are allowed to change data over
time, i.e., co-evolution management needs to be provided to ensure consistency.
In this paper, we tackle the problem of RDF data co-evolution and devise an
approach for conflict resolution during co-evolution of RDF datasets. Our
proposed approach is property-oriented and allows for exploiting semantics
about RDF properties during co-evolution management. The quality of our
approach is empirically evaluated in different scenarios on the DBpedia-live
dataset. Experimental results suggest that proposed proposed techniques have a
positive impact on the quality of data in source datasets and replicas.Comment: 18 pages, 4 figures, Accepted in ICWE, 201
Reason Maintenance - State of the Art
This paper describes state of the art in reason maintenance with a focus on its future usage in the KiWi project. To give a bigger picture of the field, it also mentions closely related issues such as non-monotonic logic and paraconsistency. The paper is organized as follows: first, two motivating scenarios referring to semantic wikis are presented which are then used to introduce the different reason maintenance techniques
Tabulator Redux: writing Into the Semantic Web
A first category of Semantic Web browsers were designed to present a given dataset (an RDF graph) for perusal, in various forms. These include mSpace, Exhibit, and to a certain extent Haystack. A second category tackled mechanisms and display issues around linked data gathered on the fly. These include Tabulator, Oink, Disco, Open Link Software's Data Browser, and Object Browser. The challenge of once that data is gathered, how might it be edited, extended and annotated has so far been left largely unaddressed. This is not surprising: there are a number of steep challenges for determining how to support editing information in the open web of linked data. These include the representation of both the web of documents and the web of things, and the relationships between them; ensuring the user is aware of and has control over the social context such as licensing and privacy of data being entered, and, on a web in which anyone can say anything about anything, helping the user intuitively select the things which they actually wish to see in a given situation. There is also the view update problem: the difficulty of reflecting user edits back through functions used to map web data to a screen presentation. In the latest version of the Tabulator project, described in this paper we have focused on providing the write side of the readable/writable web. Our approach has been to allow modification and addition of information naturally within the browsing interface, and to relay changes to the server triple by triple for least possible brittleness (there is no explicit 'save' operation). Challenges which remain include the propagation of changes by collaborators back to the interface to create a shared editing system. To support writing across (semantic) Web resources, our work has contributed several technologies, including a HTTP/SPARQL/Update-based protocol between an editor (or other system) and incrementally editable resources stored in an open source, world-writable 'data wiki'. This begins enabling the writable Semantic Web
Personalized content retrieval in context using ontological knowledge
Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. However, not all user preferences are relevant in all situations. It is well known that human preferences are complex, multiple, heterogeneous, changing, even contradictory, and should be understood in context with the user goals and tasks at hand. In this paper, we propose a method to build a dynamic representation of the semantic context of ongoing retrieval tasks, which is used to activate different subsets of user interests at runtime, in a way that out-of-context preferences are discarded. Our approach is based on an ontology-driven representation of the domain of discourse, providing enriched descriptions of the semantics involved in retrieval actions and preferences, and enabling the definition of effective means to relate preferences and context
Accurate and efficient splitting methods for dissipative particle dynamics
We study numerical methods for dissipative particle dynamics (DPD), which is
a system of stochastic differential equations and a popular stochastic
momentum-conserving thermostat for simulating complex hydrodynamic behavior at
mesoscales. We propose a new splitting method that is able to substantially
improve the accuracy and efficiency of DPD simulations in a wide range of the
friction coefficients, particularly in the extremely large friction limit that
corresponds to a fluid-like Schmidt number, a key issue in DPD. Various
numerical experiments on both equilibrium and transport properties are
performed to demonstrate the superiority of the newly proposed method over
popular alternative schemes in the literature
- …