A taxonomy of critical success factors for Open Data

This is a simple two-tier taxonomy of factors that are critical for the success of open data initiatives at local, national and international level.  It has been developed through a series  of workshops analysing and classifying international open data best practices and initiatives. It can be used as a guidance support for public servants, the overall planning of open data initiatives or classification of best practice scenarios or examples.

This is based on work done by:

A. Factors critical for open data
publication by administrations



1 Legislation,
regulation and licenses

Having in
place a (national) legal framework for open data publication

Enforce publishing and curating of data on
administrations (maybe even through penalties)

Provide information
about data protection and privacy legislation and how open data can be
published in compliance with this legislation

Develop a (national) guide on legal
Intellectual Property Right (IPR) issues allowing organizations to pick the
correct licensing form

2 Strategy and
political support

Develop a
strategy for open data publication at an (inter)national level

Ensure that (top) management within
governmental agencies supports publishing data

support of policy-makers for data publication

Organize focus groups with heads of
departments and open data policy implementers to give both proponents and
opponents of open data an auditorium

Introduce incentives
schemes for public servants (e.g. explain why a data provider would release
data, explain what kind of value is created for the data provider)

Create consensus between open data publication
and the organizational framework for publishing data

3 Management support and publication
processes within governmental agencies

Define clear
process steps for publishing data

Determine which type of data is important to
address societal issues and focus on the publication of these data

Start with
the publication of data which is interesting for users so that the users see
the benefit of open data

Determine which data and metadata will and
will not be published

which standards and vocabularies will be used for data publication

Determine which personnel has the key
responsibilities for publishing open data

where datasets will be published

Release only data which is of high quality

4 Training of and support for civil servants

Create a
virtual competence center which assists in answering questions and helping
out with administrative data publication processes

Provide training on open data publication
within governmental agencies (e.g. training on how datasets can be

information campaigns in which questions about open data publication are

Develop information campaigns in which success
stories of internal and external open data use are discussed

5 Evaluation of the open data initiative

metrics and success indicators for data publication by government departments

Evaluate the realization of metrics and
success indicators as an integral part of the open data initiative

6 Sustainability of
the open data initiative

Identify the
need for data

Create a strategy for maintaining published

Ensure data
provision continuity, including timely and automatic updates of data

Be transparent towards open data users about
the conditions under which data publication takes place

7 Collaboration

meetings with open data users to find out what their needs are and how the
data from the governmental agency are used

Organize internal meetings to discuss the data
publication processes and to evaluate them

Organize inter-organizational
collaboration about and management of open data initiatives

Ensure agile and  open cooperation with various other
organizations (administration, universities, CSO, Open Knowledge Foundation)

Organize inter-organizational
collaboration (e.g. network meetings) to learn from the open data initiatives
of other governmental agencies

8 Open data platforms, tools and services

Integrate the open data platform into existing
Content Management Systems (CMS) to kick-start the progress

Have one
central portal which combines data from many different governmental
organizations (federal level)

Implement advanced data search functionalities

complementary toolsets for performing additional curation tasks (cleaning,
linking, visualizing, analyzing)

Use a “web 2.0” approach for open data,
allowing citizens to post, rate, work with datasets and web services

frameworks for assessing data quality and usability of data and platform,
providing continuous feedback to developers and administrations

Provide a forum to discuss what can be learned
from open data use

Develop a
clear User Interface (logical symbols, clear setup of the web page, simple

9 Accessibility, interoperability and

Use standards for data, metadata, licenses,
URIs and exchange protocols

Use cloud
infrastructures able to gather, manage and publish open data, interoperable
with other sources within the country or region

Integrate metadata schemas and federated
controlled vocabularies for properly categorizing information

various types of metadata, in line with metadata standards (e.g. CERIF, CKAN,

Provide Application Programming Interfaces
(API’s) for open data provision in the form of service feeds (from open data
to open services)

Enable multilinguality
of metadata and data, allowing for the reuse and integration of data from
different countries/languages


B. Factors critical for open data
use by citizens, entreprises and administrations



10 Legislation, regulation and licenses

information on the meanings and implications of licenses

Provide information about privacy legislation
and how open data can be used in compliance with this legislation

11 Success stories

readily available examples of open data use (e.g. apps) to non-experts

Develop stories of successful open data use

community key players to propagate success stories

12 Incentives for open data use

Provide incentive schemes to  engage citizens in open data usage

the development of specialized, open-data driven startup incubators

Stimulate the development of business models
to allow enterprises to develop add-on services on top of open data
platforms, at a cost

issue-oriented community building through participatory events

Align events, competitions and hackathons
with, for example, university curricula, awards, festivals and “direct

13 Training of and support for open data

agile, dynamic, and professional support services and training for potential
open data users 

Organize events and ensure community building
where the potential benefits of open data are communicated to users (e.g. by
building scenarios for usage)

14 Feedback and sustainability

mechanisms for governmental agencies to know how their data have been reused

Provide mechanisms for governmental agencies
to know what can be learned from the reuse of their data

mechanisms for governmental agencies to know how the publication of their
data can be improved based on feedback that they received from open data

15 Research and education

Develop university and continuous education
curricula on open data

Develop and
maintain research areas roadmaps on open data, in order to consolidate
research efforts and address open issues