Paper Info
Title
The Problem with XSD Binary Floating Point Datatypes in RDF
Abstract
The XSD binary floating point datatypes are regularly used for precise numeric values in RDF. However, the use of these datatypes for knowledge representation can systematically impair the quality of data and, compared to the XSD decimal datatype, increases the probability of data processing producing false results. We argue why in most cases the XSD decimal datatype is better suited to represent numeric values in RDF. A survey of the actual usage of datatypes on the relevant subset of the December 2020 Web Data Commons dataset, containing 19 453 060 341 literals from real web data, substantiates the practical relevancy of the described problem: 29%-68% of binary floating point values are distorted due to the datatype.
Year
DOI
Venue
2022
10.1007/978-3-031-06981-9_10
SEMANTIC WEB, ESWC 2022
Keywords
DocType
Volume
Data Quality, Datatypes, Floating Point Numbers, Knowledge Graphs, Numerical Stability, RDF, XSD
Conference
13261
ISSN
Citations 
PageRank 
0302-9743
0
0.34
References 
Authors
0
1
Name
Order
Citations
PageRank
Jan Martin Keil101.01