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5.2 Future Work
Following on this work, the prototypical implemen-
tation will be enhanced, so that it not only supports
the requirements of the Coscine platform, but can be
used in general. With work looking into different
change indicators and implementing them, it will be
seen how well they perform and which produce the
best results in performance, accuracy and applicabil-
ity. Even new developed methods, which could focus
on machine learning and fueling a change indicator
based on a trained model, could be interesting in this
evaluation. Furthermore, the paper is focused on data
entities however an interesting area to look into is how
to reflect this research on collection of data entities
and collection of collections. Since a change indicator
is proposed, another area of future interest is to see if
the difference between data entities in two collections
could tell the similarity between them. Especially
by looking into the descriptive metadata as well, the
defining topics which are similar could be detected by
such a method and most importantly which topics are
not the same.
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