The Use of Open Data to Improve the Repeatability of Adaptivity and Personalisation Experiment

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2016Access:
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Harshvardhan J. Pandit, Ramisa Hamed, Seamus Lawless, David Lewis, The Use of Open Data to Improve the Repeatability of Adaptivity and Personalisation Experiment, 1st EvalUMAP workshop - Towards comparative evaluation in user modeling, adaptation and personalization, held in conjunction with the 24th Conference on User Modeling, Adaptation and Personalization, UMAP 2016, Halifax, canada, 16 July 2016, 2016Download Item:

Abstract:
Reproducibility of results is a key element for the verification
of scientific experiments and an important indicator of
the quality of a published experiment. It is vital therefore
to precisely and transparently share both the method and
the data associated with an experiment. Data associated
with an experiment is often linked within peer-reviewed scientific
publications, and is difficult to assess in a consistent
manner. In this paper we explore how emerging linked data
standards can be applied to the description and data of published
adaptivity and personalisation experiments in a manner
that can be linked from publications and easily located,
accessed and reused to repeat an experiment. The approach
also provides possibilities for published experiments to be
extended or modified to provide a firmer grounding for publishing
new results and conclusions
Sponsor
Grant Number
Science Foundation Ireland (SFI)
13/RC/2106
Author's Homepage:
http://people.tcd.ie/delewishttp://people.tcd.ie/pandith
Description:
PUBLISHEDHalifax, canada
Other Titles:
1st EvalUMAP workshop - Towards comparative evaluation in user modeling, adaptation and personalization, held in conjunction with the 24th Conference on User Modeling, Adaptation and Personalization, UMAP 2016Type of material:
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Linked Open Data, Language ResourcesSubject (TCD):
Digital Engagement , Linked Open DataLicences: