loomp - mashup authoring and semantic annotation using linked data

Tracking #: 1472-2684

This paper is currently under review
Authors: 
Annika Hinze
Markus Luczak-Rosch
Ralf Heese
Hannes Muehleisen
Adrian Paschke

Responsible editor: 
Ruben Verborgh

Submission type: 
Full Paper
Abstract: 
Legacy full-text corpora and low precision of automatic annotation have long hindered widespread utilization of semantically-rich content. Best annotation quality on specialised collections can be achieved through manual annotation; most manual approaches assume that semantic annotations will be created by domain experts. However, the poor usability of many tools is a challenge to end-users who do not have extended knowledge of semantic techniques. For the semantic content authoring tool loomp, we followed a user-centred design approach to implement mashup and manual annotation of textual resources. Loomp was developed in close collaboration with knowledge workers and domain experts from public service institutions. This article provides technical details of Loomp's design, architecture and data model based on requirements derived from real-world journalism use cases.
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