ReCert 2015 - 1st International Workshop on Linked Data Repair and Certification (ReCert 2015)
Topics/Call fo Papers
In recent years, we have witnessed a big growth of the Web of Data due to the enthusiasm shown by research scholars, public sector institutions and some private companies. Nevertheless, no rigorous processes for creating or mapping data have been systematically followed in most cases, leading to uneven quality among the different datasets available. Though low quality datasets might be adequate in some cases, these gaps in quality in different datasets sometimes hinder the effective exploitation, especially in industrial and production settings.
In this context, there are ongoing efforts in the Linked Data community to define the different quality dimensions and metrics to develop quality assessment frameworks. These initiatives have mostly focused on spotting errors as part of independent research efforts, sometimes lacking a global vision. Further, up to date, no significant attention has been paid to the automatic or semi-automatic repair of Linked Data, i.e., the use of unattended algorithms or supervised procedures for the correction of errors in linked data. Repaired data is susceptible of receiving a certification stamp, which together with reputation metrics of the sources can lead to having trusted linked data sources.
The goal of the Workshop on Linked Data Repair and Certification is to raise the awareness of dataset repair and certification techniques for Linked Data and to promote approaches to assess, monitor, maintain, improve, and certify Linked Data quality.
In this context, there are ongoing efforts in the Linked Data community to define the different quality dimensions and metrics to develop quality assessment frameworks. These initiatives have mostly focused on spotting errors as part of independent research efforts, sometimes lacking a global vision. Further, up to date, no significant attention has been paid to the automatic or semi-automatic repair of Linked Data, i.e., the use of unattended algorithms or supervised procedures for the correction of errors in linked data. Repaired data is susceptible of receiving a certification stamp, which together with reputation metrics of the sources can lead to having trusted linked data sources.
The goal of the Workshop on Linked Data Repair and Certification is to raise the awareness of dataset repair and certification techniques for Linked Data and to promote approaches to assess, monitor, maintain, improve, and certify Linked Data quality.
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Last modified: 2015-07-10 23:04:41