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Best Practices/Open Data Publication Plan

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Name of the Share-PSI workshop: Samos Workshop

Title of the Best Practice: Open Data Publication Plan

File:BP Open Data Publication Plan.docx

Outline of the best practice

Budgetary and other constraints prevent public sector bodies from publishing all the suitable datasets as Open Data at once. Datasets that are fit for publication as Open Data need to be identified as well as the requirements of both the internal and external stakeholders. Open Data publication plan should be developed taking into account needs of the relevant stakeholders as well as the potential benefits, risks and costs of publication of the datasets.

Management summary

Challenge

Public sector bodies hold a large number of various datasets. However they also operate under budgetary and various other constraints that prevent them from making every potential dataset available for re-use at once. Beside this the complete list of datasets is not always available which complicates identification and selection of datasets to be published as Open Data.

Solution

In order to overcome the above mentioned challenges an analysis of the available datasets should be performed, needs and requirements of both the internal and external stakeholders should be understood and the Open Data publication plan should be developed.

The analysis should be aimed at:

  • Identification of the available datasets.
  • Assessment of the potential barriers to publication of the identified datasets, e.g. confidentiality of the data or the privacy protection.
    • If any of the datasets cannot be published as Open Data, justification needs to be provided that explains why it cannot be made available for re-use. Releasing anonymized data or aggregate statistics derived from some primary data should be taken into account.
  • Colleting the basic metadata such as the title, description, responsible person/department and current formats. Scope of the collected metadat might be adjusted according to the needs of the organization.
  • Assessment of the potential benefits and risks of publishing the identified datasets as Open Data.
  • Assessment of costs and effort associated with publication of the identified datasets as Open Data.

Publication of Open Data should be in line with the strategic aims of the organization, with the relevant policies such as the national Open Data strategy and it should meet the demand of the potential users of the data. Therefore the requirements both internal and external stakeholders should be identified and analyzed.

Based on the results of the previous steps the Open Data publication plan should be developed. It should contain all the necessary tasks to implement the Open Data initiative. With regard to the datasets planned to be published as Open Data a release roadmap should be developed. Release of the datasets should be prioritized taking into consideration the requirements of the stakeholders as well as the results of the analysis of the datasets, i.e. the identified benefits and risks and the cost/effort estimates.

Progress should tracked against the Open Data publication plan. This plan should be also regularly reviewed and updated.

Best Practice Identification

Why is this a Best Practice? What's the impact of the Best Practice?

Open Data publication plan has been successfully used to manage the Open Data initiative of the Czech Telecommunication Office [3]. Development of the Open Data publication plan is a recommended practice in [5]. Carrying out a data audit to discover the potential datasets for release as Open Data and the subsequent priority publication of the high-value datasets is a proposed best practice in [4]. In the UK the government departments publish their Open Data strategies [6]. For example Open Data strategy of the Department of Health contains a list of datasets released or planned to be released [1].

Link to the PSI Directive

(Please use one or more of the categories listed on the last page of this document, as many as relevant)

Dataset criteria and priorities and value and scope w.r.t. datasets

Selection of information/data to be published according to various criteria

Why is there a need for this Best Practice?

Janssen et al. [2] name many barriers to publication of Open Data and limited resources that can be allocated to its publication is one of them. This best practice aims at balancing the requirements and needs of the relevant stakeholders with the available resources by planning of the data release and other necessary steps that takes into account the demand for data, the potential benefits and risks associated with the publication of the identified datasets as well as the estimated costs of the publication.

What do you need for this Best Practice?

This best practice requires:

  • Obtaining a top management support.
  • Appointing a person responsible for development of the Open Data publication plan.
  • Securing cooperation of the departments involved in the Open Data initiative.
  • Setting up a review process for the Open Data publication plan.

Applicability by other member states?

In general this best practice should be applicable across the EU member states because it does not build upon any particular legal framework. However the legal framework, national or other strategies as well as for example the data management practices applied in the particular member state and its public sector bodies might affect what datasets should be included in the Open Data publication plan and how this plan is going to be implemented and assessed.

Contact info - record of the person to be contacted for additional information or advice.

Jan Kučera (University of Economics, Prague, Czech Republic). Email: jan.kucera@vse.cz.

References

  1. DEPARTMENT OF HEALTH, 2012. The Power of Information. Putting all of us in control of the health and care information we need. In: data.gov.uk [online]. 21 may 2012 [Accessed 2015-05-02]. Available from: http://data.gov.uk/library/dh-open-data-strategy.
  2. JANSSEN, Marijn, CHARALABIDIS, Yannis and ZUIDERWIJK, Anneke, 2012. Benefits, Adoption Barriers and Myths of Open Data and Open Government. Information Systems Management. 2012, vol. 29, no. 4, pp. 258-268. ISSN 1058-0530.
  3. KUČERA, Jan and CHLAPEK, Dušan. Comparison of Approaches to Publication of Open Government Data in Two Czech Public Sector Bodies. eJournal of eDemocracy and Open Government (JeDEM) [online], 2014, vol. 6, no. 1, pp. 106–111. ISSN 2075-9517. URL: http://www.jedem.org/article/view/316.
  4. LEE, Deirdre, CYGANIAK, Richard and DECKER, Stefan, 2014. Open Data Ireland: Best Practice Handbook. In: per.gov.ie [online]. May 2014 [Accessed 2014-11-20]. Available from: http://www.per.gov.ie/open-data/.
  5. NEČASKÝ, Martin, CHLAPEK, Dušan, KLÍMEK, Jakub, KUČERA, Jan, MAURINO, Andrea, RULA, Anisa, KONEČNÝ, Miroslav and VANOVÁ, Lenka, 2014. Deliverable D5.1: Methodology for publishing datasets as open data. In: COMSODE [online]. 31. 7. 2014 [Accessed 2014-09-10]. Available from: http://www.comsode.eu/wp-content/uploads/D5.1-Methodology_for_publishing_datasets_as_open_data.pdf.
  6. Open Data Strategies. In: data.gov.uk [online]. [Accessed 2015-05-02]. Available from: http://data.gov.uk/open-data-strategies.



Categories for use in section 3.2

  • Policies and legislation (legal requirements, licenses etc..) / Licensing of information/data and metadata
  • Open Data platform(s) / Publication and deployment of information/data and metadata
  • Dataset criteria and priorities and value and scope w.r.t. datasets
  • Charging issues and proposals
  • Techniques w.r.t. opening up of data / Technical requirements and tools
  • Organisational structures and skills
  • Dataset structures, formats, APIs / Structuring of information/data, formats, APIs
  • Encouraging (commercial) re-use
  • Persistence and maintenance of information/data and metadata
  • Data quality issues and solutions / Quality assurance, feedback channels and evaluation
  • Documentation of information/data, creation of metadata
  • Selection of information/data to be published according to various criteria
  • Data discoverability