Semantically Enriched Spreadsheet Tables in Science and Engineering

J.L. Top, M. Wigham, H. Rijgersberg

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


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.
Original languageEnglish
Title of host publicationThe Eighth International Conference on Advances in Semantic Processing, SEMAPRO 2014
EditorsA Cheptov, C Mavromoustakis
Place of PublicationRome
Publication statusPublished - 2014
EventSEMAPRO 2014 - Rome
Duration: 1 Jan 20141 Jan 2014


ConferenceSEMAPRO 2014


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