icegov2012 proceedings

approach [28] to expose indicators that play a significant role in
releasing data for public at the four organizations. Important
elements in this approach are desktop research, workshops,
questionnaires, and in-depth interviews with key persons at
different levels of the organizations. We have found that
important indicators for data release are the way data is stored in
an organization (distributed/decentralized versus centralized),
whether data is internally produced or externally gathered, the use
of data, and the availability of guidelines to determine whether
data is suitable for release. We discuss how these indicators may
contribute to shape an open data policy at a local level.
We note that while the combination of the indicators may be
considered as a predictor of data release by an organization, the
focus of the paper is rather to identify these indicators.
The remainder of this paper is organized as follows. In Section 2,
we embed our work in the field of open data in more detail. In
Section 3, we motivate the use of a participatory action research
approach for our purpose, while we implement this approach in
Section 4. In Section 5, we present our findings from the
participatory action research sessions. Section 6 is devoted to the
lessons that we have learned so far. Section 7 reports about our
future activities, while Section 8 concludes the paper.
2. RELATED WORK
Despite the pressures from higher levels of (federal) government
to realise data release on local level, there are barriers along
several dimensions to open data release. From a user perspective,
major barriers are the access to proper datasets and the adequate
use of datasets. The access to proper datasets is aggravated by the
fact that the datasets are fragmented and offered at several
websites, which are in some case hard to find [3, 17]. Moreover,
access to datasets are in some cases restricted to specific user
groups. Adequate use of datasets is hindered since metadata with
regard to datasets are poorly documented, and therefore the
semantics of the data may be ambiguous. Furthermore, how to
determine the quality of a dataset is an open question. In [29] an
overview of the barriers that users may encounter in using public
sector information is provided.
Along with barriers from a user perspective, data providers also
encounter barriers to data release. From this perspective, major
barriers are the lack of knowledge to deposit data, the economical
loss that data release may entail, and the lack of knowledge to
decide which datasets are eligible to release. In order to deposit a
dataset, often this dataset should be formatted and processed
according to the system requirements that accepts the dataset.
Especially dataset providers who are not familiar with the
technical aspects of data processing should deliver a lot of effort
to deposit a dataset.
The economic impact of data release becomes clear when taking
into account that some European public sector bodies used a cost
recovery model to fund data collection. For example, the Dutch
Business Register (KvK), knows a cost recovery ratio of 19,50%
[25]. By releasing data that is currently sold, certain agencies
loose a valuable source of income [27].
Organizations need practical frameworks that support them to
decide whether a dataset is eligible to release or not [30]. In these
frameworks, special attention should be given to privacy issues.
Nowadays, organizations are struggling with the questions
whether a dataset is or may become privacy sensitive [7]. For
6
example, according to [16, 18], combining datasets could lead to
undesirable results such as revealing the identity of persons.
Additionally, publishing data that was gathered and managed for a
one purpose might lead to different conclusions if implemented in
an unrelated context [16]. The potential violation of privacy, has
especially gained a lot of attention in the literature, see for
example [1, 5, 13, 16, 22, 23, 26].
In [5] a study is devoted on the impact that information
technology has on several privacy issues. While the field of
database security [1] mainly focuses to technical solutions that
enforce the “need to know principle” i.e., access control policies,
which may prevent the disclosure of privacy, more comprehensive
alternatives to prevent the disclosure of privacy are proposed in
[4, 16, 26]. In [26] a framework is proposed to protect the privacy
of citizens, while in [4] and [16] comprehensive architectures are
proposed to minimize the violation of privacy law and regulations.
In [13], the authors plea for a so-called ambient law that
articulates fundamental legal protections, including privacy,
within the socio-technical infrastructure. In [23] privacy concerns
about using cameras and solutions to these concerns are discussed
in the context of monitoring dementia patients, while [8, 22] do
the same in the context of public safety.
However, PSI, is not always personally bound. Moreover, the
barriers that may be encountered depends on the type of data at
hand to be released. Therefore, for different types of data,
different kind of barriers may be encountered. At a national level,
there are also barriers to data release above and beyond privacy. A
comparative study by [15] highlights these issues. Barriers to data
release on national level are cited as traditionally closed
government culture, but also limited data quality or uncertain
economic impact of data release.
These studies, while providing a view to data release on a national
level, lack the focus on issues as experienced on a local level by
public sector information professionals. There is a lack of
understanding on local government levels on the impact, barriers
and opportunities of open data release. Our study focus on the
understanding of the underlying processes entailed by open data at
a municipal level. The rationale to choose this level instead of a
national level is that data is mainly gathered at local levels, and
therefore their support are of crucial importance for the success of
open data. To prevent that the understanding of the underlying
processes will be dominated by privacy issues, we will place our
emphasis in this study on the release of data that not are
personally bound, and therefore the chance that data is privacy
sensitive is minimized. For example, we focus on the underlying
process that are entailed by the release of data that pertains to all
trees in Rotterdam, such as the number of trees in a street, the
kind of trees in the street, the year that a tree is planted and so on.
3. APPROACH
As mentioned above, there is a lack of understanding of how data
should be released, what the effects of release might be, and the
processes needed to facilitate data release. This applies not only to
national or federal governments, but also on a local level. Within
our education program experience has also shown that data
release is not self-evident.
In order to explore data release, the University of Applied
Sciences in Rotterdam initiated a research project with four
services that form part of the Municipality of Rotterdam. They are