Monday, March 16, 2015

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
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Determine which data and metadata will and will not be published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. Factors critical for open data use by citizens, entreprises and administrations

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

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