The increasing diffusion of linked data as a standard way to share knowledge on the Web allows users and public and private organizations to fully exploit structured data from very large datasets that were not available in the past. Over the last few years, linked data developed into a large number of datasets with an open access from several domains leading to the linking open data (LOD) cloud. Similar to other types of information such as structured data, linked data suffers from quality problems such as inconsistency, inaccuracy , out-of-dateness, incompleteness, and inconsistency, which are frequent and imply serious limitations to the full exploitation of such data. Therefore, it is important to assess the quality of the datasets that are used in linked data applications before using them. The quality assessment allows users or applications to understand whether data is appropriate for their task at hand.
Data quality issues in linked open data
Rula, A;
2016-01-01
Abstract
The increasing diffusion of linked data as a standard way to share knowledge on the Web allows users and public and private organizations to fully exploit structured data from very large datasets that were not available in the past. Over the last few years, linked data developed into a large number of datasets with an open access from several domains leading to the linking open data (LOD) cloud. Similar to other types of information such as structured data, linked data suffers from quality problems such as inconsistency, inaccuracy , out-of-dateness, incompleteness, and inconsistency, which are frequent and imply serious limitations to the full exploitation of such data. Therefore, it is important to assess the quality of the datasets that are used in linked data applications before using them. The quality assessment allows users or applications to understand whether data is appropriate for their task at hand.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
