In this paper we present LimesWebUI, our web interface of Limes. Limes, the Link Discovery Framework for Metric Spaces, is a framework for discovering links between entities contained in Linked Data sources. LimesWebUI assists the end user during the link discovery process. By representing the link specifications (LS) as interlocking blocks, our interface eases the manual creation of links for users who already know which LS they would like to execute. However, most users do not know which LS suits their linking task best and therefore need help throughout this process. Hence, our interface provides wizards which allow the easy configuration of many link discovery machine learning algorithms, that does not require the user to enter a manual LS. We evaluate the usability of the interface by using the standard system usability scale questionnaire. Our overall usability score of 76.5 suggests that the online interface is consistent, easy to use, and the various functions of the system are well integrated.
[1]
Axel-Cyrille Ngonga Ngomo,et al.
EAGLE: Efficient Active Learning of Link Specifications Using Genetic Programming
,
2012,
ESWC.
[2]
Jeff Sauro,et al.
The Factor Structure of the System Usability Scale
,
2009,
HCI.
[3]
Axel-Cyrille Ngonga Ngomo,et al.
On Link Discovery using a Hybrid Approach
,
2012,
Journal on Data Semantics.
[4]
Markus Nentwig,et al.
A survey of current Link Discovery frameworks
,
2016,
Semantic Web.
[5]
Jens Lehmann,et al.
Wombat - A Generalization Approach for Automatic Link Discovery
,
2017,
ESWC.