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Working Paper 3: Republic of Ireland's Open Data Strategy: Observations and Recommendations

Republic of Ireland’s Open Data Strategy: Observations and Recommendations

Tracey P. Lauriault, Programmable City Project, NIRSA, National University of Ireland Maynooth, County Kildare, Republic of Ireland

The Programmable City Working Paper 3 (Complete Working Paper is available here)

Executive Summary

Working Paper 3 of the Programmable City Project is a response to the Republic of Ireland’s Department of Public Expenditures and Reform (DPER) Open Data launch and the reports produced by Insight at the National University of Ireland Galway (NUIG), who were awarded the contract from a government call for tender (CfT).  The Working Paper provides background context to the open data plan and critically considers governance; infrastructure; records management as well as information management and information technology (IM/IT); Legal, policy and ethical frameworks; public engagement; data curation; data dissemination and publication, and evaluation.  The Paper proposes reconceptualizing open data as a function of government record keeping, information management, shared services and national spatial data infrastructures as opposed to a standalone program.  By doing so, it is suggested, open data simply becomes a good governance strategy and by integrating it into broader government administration information management provides it with sustainability, especially if it becomes a normalized data dissemination strategy and a public engagement mechanism.  The Working Paper also includes a number of recommendations for consideration in addition to or to complement those provided by Insight.  Recommendations are as follows:

1. Good Governance

  • Open data should be a natural extension of good governance strategies and not stand alone programs.
  • Open data should be a key component of government information management (IM), record management, IT and national spatial data infrastructures (NSDI).
  • Open data should be part of a coordinated data and information dissemination strategy, which should also include publicly funded research data, scientific data, data from the humanities, and other qualitative data.
  • Focus on the production and maintenance of good quality public sector, administration, research, geospatial and scientific datasets and less on commercialization, innovation and ‘high value’ datasets.
  • Focus on data that have societal and environmental value, and also on core/framework datasets upon which other datasets can be integrated into.

2. Open Data, Records & Information Management and Thinking more Critically about Data

  • Consider open Data as a good governance strategy and as part of data and information management.
  • Integrate Open Data into IM/IT, Shared Services and integrate with the NSDI
  • Data infrastructures are critically important, Open Data should be considered with cloud computing, high speed internet, and hardware and software.
  • Open datasets should be thought of as government records (data & information) and should be managed accordingly.
  • Adopt a life-cycle and data curation approach to the management, preservation and dissemination of Open Data datasets.
  • Implement the NSDI and consider the CGDI principles for the NSDI and for Open Data in Ireland.
  • Critically reflect on data more broadly and not just as objects at the end of an information pipeline.
  • Consider evaluating the contents of an open data portal to see if these can be used to construct indicators of well-being and quality of life.

3.  The DPER / Insight Roadmap and the Best Practices Handbook

  • 3.1.      Governance

  • Develop an open data public interest mandate, vision and mission, and clear objectives against which performance can be evaluated.
  • Reconsider the organizational structure as per the schematic in Figure 5.
  • Reconsider appointments on the SIG to be expertise and skills based and less political, and that appointments be made by peers.
  • Create an open data institutional entity that will operationalize the work of the ODB, SIG and Working groups and integrate these with other government programs.
  • Open data officers should be appointed in all government offices
  • Create temporary expert working groups to develop and implement infrastructure wide practices (see figure 5).

3.2.      Legal, Policy and Ethical Framework

  • Develop a data and information legal and policy framework with open data as a component of it.
  • Conduct an inventory of collaborative and data sharing instruments (e.g., MOU, procurement contracts, data sharing agreements, etc.).
  • Assess the outputs of the Intellectual Property Activity in Ireland Based on Existing Data report resulting from the RfT in the spring of 2014.
  • Conduct an inventory of all laws, regulation, policies and directives that would govern how data are collected and disseminated.
  • Develop a set of explicit legal, policy and ethical guidelines for the management of public sector data and open data based on laws, regulation, directives, policies and practices in Ireland for public sector officials.
  • Include these guidelines as part of the data dissemination decision-making tree (Figure 6).

3.3.      Public Engagement

  • Engage with stakeholders on developing the mission, vision and mandate for the Open Data strategy.
  • Engage with stakeholders to shape how an Open Data roadmap and strategy could look.
  • Engage with, study, build upon and harmonize the Open Data strategy with existing public sector data dissemination programs.
  • Review and assess existing technologically mediated engagement tools and social media applications in other jurisdictions.
  • Public sector officials and departments should develop processes and be receptive to evidence based public input into public policy and planning, and learn to solicit feedback from the public in a useful and educated way.
  • Consider crowdsourcing, VGI and citizen science as a public engagement strategy.

4. Data Curation or a Data Audit?

  • Adopt a digital data curation and life-cycle approach to the management of data and conduct the data audit accordingly.
  • Adopt the Data Audit Framework.
  • Ensure that additional elements are added into the data audit (e.g. geocoded, scale, time).
  • The high value approach to the selection of data should be reconsidered, and an evaluation of what current data ‘clients’ value, should be considered.
  • Recognize the limitations of a machine only audit, and broaden search criteria to include all data not just those in open formats and under an open licence.
  • Conduct a full inventory of portals and catalogues from all sectors in Ireland and integrate their metadata to ensure cross disciplinary discoverability.
  • Publish the results of the data audit.

5. Data Dissemination and Publication

  • It is highly recommended that DPER consider adopting the well established data curation life cycle management approach similar to the one developed by the Digital Curation Centre, and consider taking a data curatorial approach in lieu of a data audit.
  • Adopt the Data Audit Framework for data curation as well as those developed by the Digital Curation Centre and consider developing an Information Management Directive which incorporates the ideals of Open Data, preservation and archives.
  • Create a decision making tree to help public officials determine what can and cannot be published.  Figure 6 is an example to guide decisions on the management and dissemination of sensitive data.
  • The outcomes of the decision derived from the application of the open data publication decision making tree would then form the basis for the decision supporting why some datasets are not published by default.
  • A data management and dissemination WG should be created along with those in Figure 5, and invite experts from the Digital Repository of Ireland, library and archives and information studies, geospatial community to help develop a comprehensive access, dissemination, data management and preservation plan for Ireland.

6.  Evaluation

  • Assess current performance and evaluation frameworks within the Irish public sector, including auditing frameworks, or those commonly adopted and reported on in other countries that have well established Open Data programs such as Canada, the US and the UK and as per the RfT.
  • Reassess the Open Data Barometer evaluation recommendation in the DPER/Insight report in light of its objectives and its target use and determine if it is a suitable model for a western developed national Open Data program.
  • Consider high impact datasets, those of public, social and environmental significance along with those considered to be of high value.

Preservation of Geospatial Data Primer

This document (French and English) is the last in a series that I wrote while in Canada on the preservation of geospatial data and I just received the finals today.  Fitting, since I have now been in Ireland for exactly one year today.  The past is however always part of the present and the future is it not?  In my view, the preservation of data should be part of any spatial data infrastructure and open data strategy.  It is simply part of the lifecycle management of a nations knowledge resources.  Data are modern artifacts as important as manuscripts, films or paintings.  If we invest so much in their capture, then we should also invest in their long term maintenance.

This primer is part of a series of Operational Policy documents developed by GeoConnections intended to inform Canadian Geospatial Data Infrastructure (CGDI) stakeholders about the nature and scope of digital geospatial data archiving and preservation and the realities, challenges and good practices of related operational policies.  GeoConnections produces a number of excellent documents on a wide range of contemporary data topics such as VGI, managing sensitive environmental data, data licences, data access, best practices for sharing data, open source, and a host of many others that are very relevant to governments world wide.

This primer starts by examining preservation responsibilities, legislation, acts, directives and policies.  3 preservation frameworks were also discussed:

  1. the Reference Model for an Open Archival Information System (OAIS) (CCSDS, 2012), developed by the Consultative Committee for Space Data Systems (CCSDS);
  2. the European Long Term Preservation of Earth Observation Space Data: European LTDP Common Guidelines (LTDP Working Group, 2012), developed by the Long Term Data Preservation (LTDP) Working Group of the Ground Segment Coordination Body (GSCB); and
  3. the Trustworthy Repositories Audit & Certification (TRAC) Audit and Certification: Criteria and Checklist (OCLC and CRL, 2007), developed by the Center for Research Libraries and the Online Computer Library Center, Inc.

The stucture of the document loosely follows the The International Research on Permanent Authentic Records in Electronic Systems (InterPARES) 2 record creator and preserver guidelines.  The work is grounded in the stufy of four cases were and includes challenges and best practices :

  1. The Canada centre for Remote Sensing (CCRS) Earth Observation Data Management System (EODMS)
  2. Land Information Ontario (LIO) Geographic Information Archive (GIA)
  3. Department of Fisheries and Oceans Canada (DFO), the Integrated Science Data Management Service (ISDM)
  4. International Polar Year (IPY) Data Preservation

Finally, the section on Establishing a Geospatial Data Preservation System guides data creators and preservers through a series of processes based on the frameworks, case studies, and guidelines.

GeoConnections has been studying the preservation and archiving of geospatial data since 2005. The following are the three reports in this series.

  1. Archiving, management and preservation of geospatial data summary report and recommendations (2005)
  2. Geospatial Data Archiving and Preservation – Research and Recommendations Executive Summary. (2011), Tracey P. Lauriault and Ed Kennedy, Hickling Arthurs and Low (HAL) NOTE – if you email me or GeoConnections, we can send you the full document.
  3. Geospatial Data Preservation Primer GeoConnections (2013) Tracey P. Lauriault, Ed Kennedy, with digital preservation subject matter expertise from Yvette Hackett, Library and Archives Canada Retired, reviewed by Marcel Fortin, Geographic Information Systems (GIS) & Map Librarian. Map and Data Library, University of Toronto. Hickling Arthurs and Low (HAL)

These documents are not for the faint at heart, but they inform practioners in all sectors, they are governmentality in action and are the datasets upon which critical data studies take shape.

 

The Data Revolution book published

Rob Kitchin’s latest book The Data Revolution: Big Data, Open Data, Data Infrastructure and Their Consequences was published on August 23rd by Sage.  There’s a dedicated website with a bunch of resources (including open access links to related papers and a hyperlinked bibliography), plus a promo video (below).  The publisher has made the preface and chapters one (Conceptualising Data) and four (Big Data) open access.  The website has a full table of contents and chapter outlines though the title gives a pretty good description as to what it’s about.  The book has had a decent amount of advance praise.  The site includes details about buying the book, including electronically through just about every format going.

New Paper: Towards Critical Data Studies: Charting and Unpacking Data Assemblages and Their Work

Rob Kitchin and Tracey Lauriault have just published the second Programmable City Working Paper – Towards Critical Data Studies: Charting and Unpacking Data Assemblages and Their Work. It is a pre-print of a chapter written for the book, Geoweb and Big Data, edited by Joe Eckert, Andy Shears and Jim Thatcher, to be published by University of Nebraska Press.

Abstract
The growth of big data and the development of digital data infrastructures raises numerous questions about the nature of data, how they are being produced, organized, analyzed and employed, and how best to make sense of them and the work they do. Critical data studies endeavours to answer such questions. This paper sets out a vision for critical data studies, building on the initial provocations of Dalton and Thatcher (2014). It is divided into three sections. The first details the recent step change in the production and employment of data and how data and databases are being reconceptualised. The second forwards the notion of a data assemblage that encompasses all of the technological, political, social and economic apparatuses and elements that constitutes and frames the generation, circulation and deployment of data. Drawing on the ideas of Michel Foucault and Ian Hacking it is posited that one way to enact critical data studies is to chart and unpack data assemblages. The third starts to unpack some the ways that data assemblages do work in the world with respect to dataveillance and the erosion of privacy, profiling and social sorting, anticipatory governance, and secondary uses and control creep. The paper concludes by arguing for greater conceptual work and empirical research to underpin and flesh out critical data studies.

Key words
big data, critical data studies, data assemblages, data infrastructures, civil liberties

ERC Video for the Programmable City Project

This video introduces the Programmable City. In the video Rob Kitchin outlines the aims and objectives of the project and highlights the importance of the support received from the European Research Council (ERC). Each researcher on the Programmable City team also briefly discusses their work. The video was made by the Programmable City team in order to promote the project and the ERC.

Post in 'Big Data, Big Questions' series on LSE Impact blog

Rob Kitchin provides the first interview in a new series on the LSE Impact blog entitled ‘Big Data, Big Questions’ curated by Mark Carrigan.  The post concerns the philosophy of data science, the nature of ‘big data’,  the opportunities and challenges presented for scholarship with its growing influence, the hype and hubris surrounding its advent, and the distinction between data-driven science and empiricism.  You can read more over at the LSE Impact blog.