Tabular data are common in science and engineering. Datasets found in practice are often not very well specified, and are therefore hard to understand and use. Semantic standards are available to express the meaning and context of the data. However, present standards have their limitations in expressing heterogeneous datasets with several types of measurements. Such datasets are abundant in science and engineering. We propose the RDF Record Table vocabulary for semantically modelling tabular data. It complements the existing RDF Data Cube standard. RDF Record Table has a nested structure of records that contain self-describing observations. A first implementation of the model shows that it facilitates finding and integrating data from multiple spreadsheets. This support helps scientists to get the most out of available quantitative data with a minimum of effort.
|Title of host publication||The Eighth International Conference on Advances in Semantic Processing, SEMAPRO 2014|
|Editors||A Cheptov, C Mavromoustakis|
|Place of Publication||Rome|
|Publication status||Published - 2014|
|Event||SEMAPRO 2014 - Rome|
Duration: 1 Jan 2014 → 1 Jan 2014
|Period||1/01/14 → 1/01/14|