TY - JOUR
T1 - Towards certified open data in digital service ecosystems
AU - Immonen, Anne
AU - Ovaska, Eila
AU - Paaso, Tuomas
N1 - Funding Information:
In our initial research on open data (Immonen et al. ; Immonen et al. ), the first draft of an open data ecosystem was defined from the business viewpoint. The work was performed in 2012–2014 on the national strategic research project, ODEP (Open Data End-user Programming), funded by the Finnish Funding Agency for Technology and Innovation (TEKES) and VTT Technical Research Centre of Finland. The purpose of the ODEP project with the research theme “Open data and analytics” was to create new technology and business potential utilizing open data. The subject was, at the time, relatively new and the utilization of open data in business by companies was at the outset. The requirements of such an ecosystem were collected with the help of interviews of industry representatives and the motives and challenges of acting in the open data ecosystem were identified. Altogether, 11 industry representatives participated in the interviews, including ecosystem actors such as data providers, application developers, infrastructure providers, and application users. Companies were selected from different application domains to be interviewed, and they differed in company size and service types. The interviewees, for example, product developer managers, customer and development managers, and finance and administration managers, were selected based on their knowledge of the business viewpoint of their company. The interviews provided valuable insight and requirements for the concept of an open data-based ecosystem and enabled a response to the actual needs of the data-based industry. Furthermore, the interviews enabled identifying the challenges and opportunities of open data, and applications and services of open data, and enabled evaluating the feasibility of the open data ecosystem (Immonen et al. ).
Publisher Copyright:
© 2017, The Author(s).
PY - 2018
Y1 - 2018
N2 - The opportunities of open data have been recently
recognized among companies in different domains. Digital
service providers have increasingly been interested in
the possibilities of innovating new ideas and services
around open data. Digital service ecosystems provide
several advantages for service developers, enabling the
service co-innovation and co-creation among ecosystem
members utilizing and sharing common assets and
knowledge. The utilization of open data in digital
services requires new innovation practices, service
development models, and a collaboration environment.
These can be provided by the ecosystem. However, since
open data can be almost anything and originate from
different kinds of data sources, the quality of data
becomes the key issue. The new challenge for service
providers is how to guarantee the quality of open data.
In the ecosystems, uncertain data quality poses major
challenges. The main contribution of this paper is the
concept of the Evolvable Open Data based digital service
Ecosystem (EODE), which defines the kinds of knowledge
and services that are required for validating open data
in digital service ecosystems. Thus, the EODE provides
business potential for open data and digital service
providers, as well as other actors around open data. The
ecosystem capability model, knowledge management models,
and the taxonomy of services to support the open data
quality certification are described. Data quality
certification confirms that the open data is trustworthy
and its quality is good enough to be accepted for the
usage of the ecosystem's services. The five-phase open
data quality certification process, according to which
open data is brought to the ecosystem and certified for
the usage of the digital service ecosystem members using
the knowledge models and support services of the
ecosystem, is also described. The initial experiences of
the still ongoing validation steps are summarized, and
the concept limitations and future development targets
are identified.
AB - The opportunities of open data have been recently
recognized among companies in different domains. Digital
service providers have increasingly been interested in
the possibilities of innovating new ideas and services
around open data. Digital service ecosystems provide
several advantages for service developers, enabling the
service co-innovation and co-creation among ecosystem
members utilizing and sharing common assets and
knowledge. The utilization of open data in digital
services requires new innovation practices, service
development models, and a collaboration environment.
These can be provided by the ecosystem. However, since
open data can be almost anything and originate from
different kinds of data sources, the quality of data
becomes the key issue. The new challenge for service
providers is how to guarantee the quality of open data.
In the ecosystems, uncertain data quality poses major
challenges. The main contribution of this paper is the
concept of the Evolvable Open Data based digital service
Ecosystem (EODE), which defines the kinds of knowledge
and services that are required for validating open data
in digital service ecosystems. Thus, the EODE provides
business potential for open data and digital service
providers, as well as other actors around open data. The
ecosystem capability model, knowledge management models,
and the taxonomy of services to support the open data
quality certification are described. Data quality
certification confirms that the open data is trustworthy
and its quality is good enough to be accepted for the
usage of the ecosystem's services. The five-phase open
data quality certification process, according to which
open data is brought to the ecosystem and certified for
the usage of the digital service ecosystem members using
the knowledge models and support services of the
ecosystem, is also described. The initial experiences of
the still ongoing validation steps are summarized, and
the concept limitations and future development targets
are identified.
KW - digital service ecosystem
KW - interoperability
KW - knowledge sharing
KW - quality of data
KW - quality policy
KW - semantics
UR - http://www.scopus.com/inward/record.url?scp=85021108130&partnerID=8YFLogxK
U2 - 10.1007/s11219-017-9378-2
DO - 10.1007/s11219-017-9378-2
M3 - Article
SN - 0963-9314
VL - 26
SP - 1257
EP - 1297
JO - Software Quality Journal
JF - Software Quality Journal
IS - 4
ER -