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:

Anneke Zuiderwijk^a, Iryna Susha^ab, Yannis Charalabidis^c, Peter Parycek^d, Marijn Janssen^a

^a Delft University of Technology, The Netherlands, a.m.g.zuiderwijk-vaneijk@tudelft.nl,

  m.f.w.h.a.janssen@tudelft.nl

^b Örebro University, Sweden, iryna.susha@oru.se

^c University of the Aegean, Greece, yannisx@aegean.gr 

A. Factors critical for open data publication by administrations

Categories	Factors
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
	Generate 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	Determine which data and metadata will and will not be published
	Determine which standards and vocabularies will be used for data publication
	Determine which personnel has the key responsibilities for publishing open data
	Determine 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 anonymized)
	Develop information campaigns in which questions about open data publication are discussed
	Develop information campaigns in which success stories of internal and external open data use are discussed
5 Evaluation of the open data initiative	Develop 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 datasets
	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	Arrange 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
	Use 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
	Integrate 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 design)
9 Accessibility, interoperability and standards	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
	Provide various types of metadata, in line with metadata standards (e.g. CERIF, CKAN, DC, EGMS, DCAT)
	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. 

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

Categories	Factors
10 Legislation, regulation and licenses	Provide 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	Provide readily available examples of open data use (e.g. apps) to non-experts
	Develop stories of successful open data use
	Involve community key players to propagate success stories
12 Incentives for open data use	Provide incentive schemes to  engage citizens in open data usage
	Stimulate 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
	Support issue-oriented community building through participatory events
	Align events, competitions and hackathons with, for example, university curricula, awards, festivals and “direct marketing”
13 Training of and support for open data users	Ensure 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	Provide 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
	Provide mechanisms for governmental agencies to know how the publication of their data can be improved based on feedback that they received from open data users
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