PatchR: A Framework for Linked Data Change Requests

Magnus Knuth

doi:10.4018/IJSWIS.2015010102

PatchR: A Framework for Linked Data Change Requests

2015-01-01

0

PRE

AI

DOI：10.4018/IJSWIS.2015010102

原文链接

原文求助

摘要

En 中文

Incorrect or outdated data is a common problem when working with Linked Data in real world applications. Linked Data is distributed over the web and under control of various dataset publishers. It is difficult for data publishers to ensure the quality and timeliness of the data all by themselves, though they might receive individual complaints by data users, who identified incorrect or missing data. Indeed, the authors see Linked Data consumers equally responsible for the quality of the datasets they use. PatchR provides a vocabulary to report incorrect data and to propose changes to correct them. Based on the PatchR ontology a framework is suggested that allows users to efficiently report and data publishers to handle change requests for their datasets.

Keyword:

Change Management

Crowd-Sourcing

Data Curation

Linked Data

RDF

PatchR: A Framework for Linked Data Change Requests

摘要

AI总结

期刊

机构

引用论文