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hidden from their customers. Physical data locations,
the number of copies, backup strategies and so on
are normally not part of SLAs for clouds. In terms of
legal requirements, this can lead to conflicts of law,
because “data may move from one jurisdiction into
another in milliseconds” (Spies, 2011). In some
countries it is explicitly forbidden to export certain
kinds of data.
Table 1 summarizes the discussed issues with
data integration and compares them to on-premises
strategies, including private clouds.
4 DESIGN STUDY: CLOUD
INTEGRATING OPEN DATA
Based on the discussed literature and practical
experience, we argue that the migration of data
integration applications into (in particular: public)
clouds disintegrates existing information system
architectures. The redesign of a new system cannot
be without costs, and might even be impossible in a
given setting. The risks and costs must be balanced
against the potential advantages of a comprehensive
data virtualization as detailed above.
In order to judge and evaluate cloud data
integration solutions and offers, we will conduct a
design study (Hevner et al., 2004) that will try to
find answers to the following principal challenges:
How to design and build a generalized cloud
data virtualization application that can
integrate internal organization data and
external open data?
What are the necessary technical and
organizational prerequisites?
How to re-integrate and adapt existing data
integration architectures?
Can private cloud integration solutions serve as
a transitional solution for public cloud data
integration solutions later on?
Based on the methodological approach and these
questions, the main design artefact will be a software
prototype with the following preliminary global
specification:
migration of an existing database application
for soil data management into a private cloud
solution based on open source software
Integration of available open environmental
data into this cloud
Adaption and/or redevelopment of the existing
data access and management software tiers
The study will hopefully yield more insights into
the concrete questions of what kind of data can be
migrated, and how to efficiently handle on-premises
and cloud data integration. We hope to identify
further issues by the fact that the prototype responds
to an actual and relevant requirement in the
environmental department of the authors’ institute.
In the natural sciences, there is an increasing
demand for data integration solutions that permit to
conduct interdisciplinary research. The emerging
availability of open governmental data (Murray-
Rust, 2008) in this area can foster this. Furthermore,
mobility of researchers and long-term persistence
challenges for scientific data are additional reasons
for examining cloud solutions in this domain.
Given this, this prototype is an exemplary
application of data integration, and will permit to
scrutinize the application of cloud computing
principles in this domain.
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