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Semantic Annotation of Mutable Data 

Robert A. Morris, Lei Dou, James Hanken, Maureen Kelly, David
B. Lowery, Bertram Ludäscher, James A. Macklin, Paul J. Morris

This is a preprint of a paper to appear in PLoS ONE. It appears in the
file SemAnnMutableDataProductionV2.16bisWithFigs.pdf. This directory also
has a zip file containing Supporting Information files
SupportingMaterials.zip that should normally accompany the preprint.
For convenience, the preprint and SupportingMaterials.zip are
themselves both available in a single zip file named
SemAntMutableDataPreprintBis.zip.  The pdf file is not formatted the way
the publication will be, so care should be taken about citation.

If this is your initial download, you may find it most convenient to
fetch  SemAntMutableDataPreprintBis.zip

Abstract

Electronic annotation of scientific data is very similar to
annotation of documents. Both types of annotation amplify the original
object, add related knowledge to it, and dispute or support assertions
in it. In each case, annotation is a framework for discourse about the
original object, and, in each case, an annotation needs to clearly
identify its scope and its own terminology. However, electronic
annotation of data differs from annotation of documents: the content
of the annotations, including expectations and supporting evidence, is
more often shared among members of networks. Any consequent actions
taken by the holders of the annotated data could be shared as
well. But even those current annotation systems that admit data as
their subject often make it difficult or impossible to annotate at
fine-enough granularity to use the results in this way for data
quality control. We address these kinds of issues by offering simple
extensions to an existing annotation ontology and describe how the
results support an interest-based distribution of annotations. We are
using the result to design and deploy a platform that supports
annotation services overlaid on networks of distributed data, with
particular application to data quality control. Our initial instance
supports a set of natural science collection metadata services. An
important application is the support for data quality control and
provision of missing data. A previous proof of concept demonstrated
such use based on data annotations modeled with XML-Schema.


Copyright 2012-2013 by the authors under a Creative Commons CC-BY
license. If you redistribute this preprint, we will appreciate it if
you also distribute the accompanying zip file. This preprint carries
the version SemAnnMutableDataPreprintV2.16bisWithFigs.