Masterarbeit
Application-driven support for different customer journeys in FAIR research data
publishing
Research Area
Intelligent Information Management
Students
Ryan Harris
Advisers
Description
Publishing research datasets in centralized DataHubs so that
other
researchers can find it is a crucial aspect of proper scientific
work
beside other steps in the research data management lifecycle.
Sophisticated web-based data management applications already exist
that
allow a user to openly publish a dataset in different shapes,
formats and
sizes. Examples are CKAN/DKAN, DSpace or the Dataverse.
However, the publishing
process for research datasets (in comparison
to OpenData in general) is special
in several ways. Metadata has to be
provided that describes the characteristics
of the research artifact,
which can often only be done by the researcher
himself/herself. The
description has to be structured and unambiguous, so that
it can also
be understood by researchers from other disciplines. Further
legal
aspects have to be taken into consideration such as limited access
or
embargo dates. Interfaces to other applications might be relevant that
require stable resource identifiers. And the user group of researchers
might have different levels of experience, time and expectation when
publishing a new research dataset.
The aim of this project is
to address this issue with a
customer-journey centered approach in an
appropriate, existing DataHub
application. After providing a motivating
scenario, different research
data publishing behaviors have to be identified
and be described in
customer journeys. Based on that, requirements have to be
described
when publishing a research dataset so that researchers also from
other
disciplines can find and reuse it. A state-of-the-art overview has
to
compare existing DataHub applications and their support for these
research data publishing activities. A concept has to be developed,
how a
research data management platform can be established and
extended so that the
identified customer journeys and
interdisciplinary research dataset exchange
idea are supported. An
implementation and evaluation has to show the
feasability and
acceptance.
