English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The dynamic nature of Web data gives rise to a multitude of problems relatedto the identification, computation and management of the evolving versions andthe related changes. In this paper, we consider the problem of changerecognition in RDF datasets, i.e., the problem of identifying, and whenpossible give semantics to, the changes that led from one version of an RDFdataset to another. Despite our RDF focus, our approach is sufficiently generalto engulf different data models that can be encoded in RDF, such as relationalor multi-dimensional. In fact, we propose a flexible, extendible anddata-model-independent methodology of defining changes that can capture thepeculiarities and needs of different data models and applications, while beingformally robust due to the satisfaction of the properties of completeness andunambiguity. Further, we propose an ontology of changes for storing thedetected changes that allows automated processing and analysis of changes,cross-snapshot queries (spanning across different versions), as well as queriesinvolving both changes and data. To detect changes and populate said ontology,we propose a customizable detection algorithm, which is applicable to differentdata models and applications requiring the detection of custom, user-definedchanges. Finally, we provide a proof-of-concept application and evaluation ofour framework for different data models.

A Flexible Framework for Defining, Representing and Detecting Changes on the Data Web