This presentation looks at the Benefits, adoption barriers and myths of open data and open government. The slides are prepared based on the work of (Janssen. M, et al. 2012)

1. Benefits, Adoption Barriers and
Myths of Open Data and Open
Government
Presenter: Fatemeh Ahmadi Zeleti
E-Gov Unit
Based on: M. Janssen, Y. Charalabidis & A. Zuiderwijk (2012). Benefits,
Adoption Barriers and Myths of Open Data and Open Government.
Information Systems Management (ISM), vol. 29, no.4, pp. 258-268
May 11, 2016

2. Overview
Data is defined as non-privacy restricted and non-
confidential data which is produced by public money and
is made available without any restrictions on its usage and
distribution
Public bodies are the largest data creators and collectors
Opening of data reinforce existing structures instead of
changing them
Opening data leads to two assumptions about government
Readiness of public agencies for an opening process
Government is to give up control
May 11, 2016

3. Problem and the Paper
Research on open data is limited
No paper (by 2012) focus on analyzing the benefits and
barriers of open data
This paper analyzes the benefits and barriers of open data by
synthesizing people’s experiences with open data
May 11, 2016

4. The paper
 Open data benefits
 Adoption barriers of open data
 Myths of open data

5. Approach
Analyzing the literature
Literature was used as a background for organizing a group session
Session with 9 participants was held in June 2011
Findings from the session were refined based on the interviews with 14
key persons
The interviews were aimed at better understanding the nature of the
benefits and barriers and were used to determine the myths of open
data.
May 11, 2016

6. Potential Benefits
The benefits are clustered into 3 groups:
1) Political and social (public value: transparency and
accountability)*
2) Economic
3) Operational and technical
* Political and social benefits are viewed as the most important category and are the overarching arguments for stimulating open data
May 11, 2016

7. Potential Benefits – Category 1
Political and social
More transparency
Democratic accountability
More participation and self-empowerment of citizens (users)
Creation of trust in government
Public engagement
Scrutinization of data
Equal access to data
New governmental services for citizens
Improvement of citizen services
Improvement of citizen satisfaction
Improvement of policy-making processes
More visibility for the data provider
Stimulation of knowledge developments
Creation of new insights in the public sector
New (innovative) social services
May 11, 2016

8. Economic
Economic growth and stimulation of competitiveness
Stimulation of innovation
Contribution toward the improvement of processes, products and/or
services
Development of new products and services
Use of the wisdom of the crowds: tapping into the intelligence of the
collective
Creation of a new sector adding value to the economy
Availability of information for investors and companies
Potential Benefits- Category 2
May 11, 2016

9. Operational and technical
The ability to reuse data / not having to collect the same data again and
counteracting unnecessary duplication and associated costs (also by
other public institutions)
Optimization of administrative processes
Improvement of public policies
Access to external problem solving capacity
Fair decision-making by enabling comparison
Easier access to data and discovery of data
Creation of new data based on combining data
External quality checks of data (validation)
Sustainability of data (no data loss)
The ability to merge, integrate and mesh public and private data
Potential Benefits- Category 3
May 11, 2016

10. Some Insights from the Interviewees
“effective use of public sector data is vital to the growth of our
knowledge economy”
“if data is used for policy-making a high level of confidence in the
data and in the veracity of the interpretation is given. Therefore
policymakers should be prepared to share their data”
Most of the interviewees expect that open data can strengthen
accountability, build trust and improve citizen satisfaction
One of the main benefits of opening a system is the ability to tap
into the collective intelligence of the public. The key idea is that
under the right circumstances, groups can generate better
alternatives and make better decisions than even the smartest
people can do on their own
May 11, 2016

11. Barriers
Barriers are identified and categorized into the ff 6 levels:
1) Institutional level -> Data provider’s perspective
2) Task complexity of handling the data -> User’s
perspective
3) Use of open data and participation in the open data
process -> User’s perspective
4) Legislation -> Relevant for both providers and users
5) Information quality -> Relevant for both providers and
users
6) Technical -> Relevant for both providers and users
May 11, 2016

12. Barriers Category 1
Institutional Level Barriers
Emphasis of barriers and neglect of opportunities
Unclear trade-off between public values (transparency vs. privacy
values)
Risk-averse culture (no entrepreneurship culture)
No uniform policy for publicizing data
Making public only non-value-adding data
No resources with which to publicize data (especially small agencies)
Revenue system is based on creating income from data
Fostering local organizations’ interests at the expense of citizen
interests
No process for dealing with user input (no adequate feedback system)
Debatable quality of user input
May 11, 2016

13. Barriers Category 2
Task Complexity
Lack of ability to discover the appropriate data
No access to the original data (only processed data)
No explanation of the meaning of data
No information about the quality of the open data (see category “Information
Quality”)
Duplication of data, data available in various forms or before/after processing
resulting in discussions about what the source is
Difficulty in searching and browsing due to no index or other means to ensure
easy search for finding the right data
Even if data can be found, users might not be aware of its potential uses
Data formats and data sets are too complex to handle and use easily
No tooling support or help desk
Focus is on making use of single data sets, whereas the real value might come
from combining various data sets
Contradicting outcomes based on the use of the same data (right? wrong?)
Invalid conclusions May 11, 2016

14. Barriers Category 3
Use and participation
No incentives for the users
Public organizations do not react to user input
Frustration at there being too many data initiatives
No time to delve into the details or no time at all
Having to pay a fee for the data
Registration required before being able to download the data
Unexpected escalated costs
No time to make use of the open data
Lack of knowledge to make use of or to make sense of data
Lack of the necessary capability to use the information
No statistical knowledge or understanding of the potential and limitations
of statistics
Thread of lawsuits or other violations
May 11, 2016

15. Barriers Category 4
Legislation
Privacy violation
Security
No (generally accepted/understood) license for using data
Limited conditions for using data
Dispute and litigations (the process of taking legal action)
Prior written permission required to gain access to and reproduce data
Reuse of contracts/agreements
May 11, 2016

16. Barriers Category 5
Information Quality
Lack of information (e.g. Time period in which the data was collected)
Lack of accuracy of the information
Incomplete information, only part of the total picture shown or only a
certain range
Obsolete and non-valid data
Unclear value: information may appear to be irrelevant when viewed in
isolation, but when linked and analyzed, it can result in new insights
Too much information to process and not sure what to look at
(Essential) Information is missing
Similar data stored in different systems yields different results
May 11, 2016

17. Barriers Category 6
Technical
Data must be in a well-defined format that is easily accessible: while the
format of data is arbitrary, the format of data definitions needs to be
rigorously defined
No understanding of standards (country open data standards (e.g.
handbook) is not well documented)
No central portal or internationally/nationally accepted architecture
No support for making data available
Lack of understanding of metadata standards
No standard software for processing open data/ different approach exist
Legacy systems that complicate the publicizing of data
May 11, 2016

18. Some Insights from the Interviewees
“only data that is relatively safe is publicized and dropped in
the large pile … some of them even hope that the data will
not be discovered in this pile … there are no mechanisms
for gaining any feedback about its use”
“The reinforcement of the existing structure was
strengthened due to the current budget cuts.
Reinforcement also originate from the lack of systematic
analysis about which type of data should be allowed to be
publicized and what users expect from open data. This
provides arguments for not publishing data.”
“Use is limited to the happy few, those who are educated and
have time to explore new business opportunities”
May 11, 2016

19. What is Myth and Why to Formulate it
What:
A myth is a traditional or legendary story without a determinable basis of
fact or evidence. The essence of a myth is that its existence is fictional
or unproven.
Why:
Oftentimes a conceptually simplistic look at open data is taken (by different
stakeholders)
May 11, 2016

20. The paradox
Myths play an important role in policy-making – The one
sided advantage
“Our politicians are not aware of what is necessary. First they
push to publicize data, next, they complain about the
transparency and ask us to react to the questions asked …
transparency seems to be desirable only for others rather
than for their own activities”
May 11, 2016

21. The Five Myths of Open Data
Based on the interviewees the authors identify five myths
which proved not to be supported by evidence but were
often found at the heart of policy-making
1) The publicizing of data will automatically yield benefits
2) All information should be unrestrictedly publicized
3) It is a matter of simply publishing public data
4) Every constituent can make use of open data
5) Open data will result in open government
May 11, 2016

22. Myth 1
The publicizing of data will automatically yield benefits
 Open data on its own has little value; the value is created by its
use. Therefore, supporting use should not be viewed as
secondary to publicizing data
 The publicizing of data needs to be accompanied by an
infrastructure which is able to handle the data in an easy-to-use
way to lower the user threshold
 It cannot be expected that the public has the same amount of
knowledge and capabilities as researchers do. Lowering the
knowledge level required for use is key to large-scale
dissemination
 The creation of a huge pool of information might result in
difficulty in finding the right information. The more data there is,
the more difficult it is to analyze and draw meaningful
conclusions
May 11, 2016

23. Myth 2
All information should be unrestrictedly publicized
 Data that can be traced back to the individual may not be
publicized due to privacy legislation
 Limited resources for publishing, especially if the publishing of
open data does not bring benefits, can be another reason for not
opening data to the public
 The complexity of data structures and difficulty to understand
the data might make it less attractive to publicize it
 Law might prevent the publication of certain data
 Data sets receive income for some public organizations and they
can ask for fee (Fee-base business model)
 The arbitrary opening of some data might result into a biased
picture of the situation
May 11, 2016

24. Myth 3
It is a matter of simply publishing public data
 This myth challenges that data can be made available without additional
activities
 Not true myth -> Meta-data (publisher, authors, timeliness) is necessary
to overcome barriers like searching, interpretation and so on
 Governments that publish data sets face substantial criticism such as
poor usability, lack of data feedback and improvement mechanisms, and
inadequate meta-data
 => Standardization of methods and the development of robust meta-data
can increase data access
 **Data users want answers to their questions, services and other added
value that can be created from open data. Processing open data is
simply the hoop they have to jump through to gain answers to their
questions**
May 11, 2016

25. Myth 4
Every constituent can make use of open data
 This myth assumes that open data users have the resources,
expertise and capabilities to make use of the data
 Working with data requires capabilities (statistical techniques,
understanding underlying data and data relationships)
 Only people with required capabilities is able to make sense out
of data
 Data visualization and guide on how to use data can help non-
experienced users
 Automating the annotation and classification of data can help in
simplifying searches , analyze relationship and etc.
May 11, 2016

26. Myth 5
Open data will result in open government
 Myth suggest that disclosure of public data results in an
accountable and transparent government BUT this might have an
opposite effect AS
 Experience and tacit knowledge might be lacking among those
who should be able to make sense of the open data
 In addition, more information to public can result in less
understanding, more confusion and less trust
 Therefore, it is easier to not publish data than to introduce
mechanisms to seek feedback and questions from the public
May 11, 2016

27. Conclusion
 There are benefits and barriers in opening data and using data
 More research into the specific benefits, barriers and value of open data is necessary.
The long list of benefits presented in this paper can be used in determining the
benefits on a case by case basis
 Data are said to be publicized in name but they are still private in practice
 Data providers must provide easy-to- understand data rather than publicizing data
 Arguments in favor of open data are based on a rather simplistic and idealized view
 Being able to use data and find patterns and trends remains a significant challenge
therefore there is a need for having good structures and support for handling data
 The myths are:
 Convincing data providers to open their data for public to use
 While the user view is largely ignored and that use of data is not easy
May 11, 2016

28. Q&A