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making quick progress to disseminate best practices in terms of standards and tech-
nologies for increasingly opening PSI. From a technical perspective, it is a matter
of time before open government data initiatives will reach the level of maturity of
library and research data initiatives.
Ultimately, the main issues are not technical (persistent identifiers, quality, con-
trolled vocabularies, registries, etc.) but institutional/organizational. How can we
develop a network of interrelated, recognized public sector data repositories (or data
archives, or data infrastructures, regardless the label used) that take on the respon-
sibility of long-term management of PSI across Europe?
Public institutions are characterized by not being able to get full return on
investment from their valuable internal data sets for boosting innovation, due to
several factors such as the lack of human and economic resources as well as the
lack of proper stimuli and future vision. Fortunately, acts like the PSI Directive
(EU, 2003, 2013) and some ongoing initiatives are trying to raise awareness of the
economic value of opening data because data are the new raw material for the cur-
rent knowledge-based economy. Government data can be “opened” in the sense of
publishing freely available data to the entire society but can also be “opened” with
no restrictions to create social utility, new services, and added value to stimulating
stakeholder ecosystems and economic growth based primarily on open data. These
two meanings of “open” encompass the idea of Open Innovation formulated origi-
nally by Chesbrough (2006) in the economic and business sectors, in that business
boundaries become permeable to external actors' influence, promoting then a new
wealth of innovate ideas and synergies, thus creating a data-driven economy.
An open data ecosystem could bridge different open access solutions (platforms,
approaches, etc.) in an interoperable way because a one-fits-all solution seems unre-
alistic due to the extraordinarily great diversity of fields, disciplines, and areas of
knowledge. It should build on central lessons that can be learned from past and
ongoing activities in the PSI sector and research communities and the derived
recommendations.
13.5 Practical implications
From the examples in the previous sections, and crossing many of the guidelines
and recommendations of individual projects and initiatives, we can extract several
practical implications when establishing an open data ecosystem—each beginning
with a lesson learned, followed by supporting examples, and ending with a derived
need for action (highlighted in italic):
1. The distinction between PSI and research data is not definite; for example,
statistical data from public authorities might be used for scientific analysis, and
data that are acquired as part of a public-funded research project might be
considered PSI. Accordingly, the coupling of PSI and research data implies
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