Open DataOpen and Shut Case?

Prof. Rob Kitchin, NIRSA, Maynooth University

A data revolution

• Across public and private sector more data being produced about people, objects, territories, transactions and interactions than any other time in history

• These data are increasingly granular, indexical and relational

• Include:• Scientific data• Business data• Official statistical data• Public administration data• Big data, both public and private

A data revolution

Open data

• These data provide key insights for those that generate and analyze them

• The argument of the open data movement is that much more value could be derived if they were open in nature – available for everyone to examine and use

• ODM almost exclusively focuses on public sector and recasting PSI as a public commons

• Open data will:• create transparency and accountability with respect to public bodies and

services• increase the efficiency and productivity of agencies and enhances their

governance• promote public participation in decision making and social innovation• foster economic innovation and job and wealth creation

• Led to numerous open data initiatives across globe• But still lots of contested questions concerning open data

All-Island Research Observatory (AIRO; www.airo.ie)

Dublin Dashboard (www.dublindashboard.ie)

Digital Repository of Ireland (DRI; www.dri.ie)

Sustainable financial model?

• Open data is not free data• Data can distributed for marginal cost but the initial copy needs

to be paid for along with on-going data management, hosting and customer service

• Open data might be a free resource for end-users, but its production and curation is certainly not without significant cost (especially with respect to appropriate technologies and skilled staffing)

• The state acts as data generator to ensure full coverage as a public good, even for people/places that would be omitted by a private vendor as unprofitable

• In some cases, the data being opened has been a major source of revenue for organisations

• A key question, therefore, centres on how open data projects are funded sustainably, particularly in the context of austerity and the absence of a direct revenue stream?

Funding open data repositories

Source Model Source Model

Institutional Core funded Audience Premium product/service

Consortia (membership) model Freemium product/service

Built-in costs at source Content licensing

Philanthropy/ corporate sponsorship +Matched funding

Infrastructural razor & blades

Public/private partnership Service Pay per purpose

Research Research funded Free with advertising

White-label development/platform licensing

Volunteer Open source

Economic benefits?

• Economic benefit largely unproven beyond high value datasets (e.g. location, weather, travel)

• Difficult to convert open data into a paid consumer product and employment; most apps die

• Many companies surviving on venture capital until sustainable revenue stream secured

• Business sector agenda is to get access to expensively produced data for no cost, and thus a heavily subsidised infrastructural state support from which profit can be leveraged

• For many products, the main consumer is the data generator (i.e. public sector), for which the old licensing model worked fine

Politics of open data?

• ODM largely focuses on gaining access to data• Driven by a belief that opening up data is inherently a good

thing • But largely ignores the politics of the data themselves, what

those data reveal, or how they are used and for whose interests• PSI data is inherently political – systems are designed to

capture certain things, to be used in particular ways, and to serve state and political interests

• Value structures are thus inherent in data sets and these shape subsequent analysis and interpretation

• Has the potential to further empower the empowered and disenfranchise others, especially given imbalance in who has skills to process and use open data and to influence power based on their analysis

• Democratic potential of open data has been overly optimistic?

Usability and utility?

• Helbig et al. (2012) reported that many open data sites are data dumps amounting to “little more than websites linked to miscellaneous data files, with no attention to the usability, quality of the content, or consequences of its use.”

• Full of low hanging fruit – data sets easy to open but with little intrinsic value

• Also lack appropriate tools and contextual materials to support data analysis

• Many sites have low and declining traffic as they do not encourage use and users struggle to work out how the data might be profitably analyzed and used

• Further, analysis from open data has had limited impact on political and policy debates

Opening private data?

• What about opening privately held data?• Particularly data relating to public goods or

public services provided by private contracts (utilities, transport, education, etc)?

• What are the multiplier and spillover effects of companies sharing data, as per open source software?

• Open data debate needs to engage with the notion beyond publicly funded data

Is opening data enough?

• Needs much more than creation of data dumps• Needs proper data infrastructures with:• preservation, archiving and sharing policies; • re-use, privacy and ethics policies; administrative arrangements,

management organisation and governance mechanisms; • financial stability and a long term plan of development and

sustainability

•  

• One thing to open data, another to utilise them to formulate and enact evidence-informed policy and decision making

• Improved governance will come from being data-driven organisations, not simply data transparent ones

• Requires much deeper set of restructuring processes than simply opening data

Conclusion

• Open data: an open and shut case?• There are lots of compelling reasons to open data• The arguments being used are not, however, simply

commonsensical, pragmatic and benign, but are political and ideological

• The open data movement is a diverse group, seeking the same goal of opening data but for a variety of reasons and visions for what that actually means

• Open data focus is often partial and constrained, lacks critical reflection, and little considers potential unanticipated consequences

• We need a wider debate about the relative merits and politics of open data and how we go about opening data

Rob.Kitchin@nuim.ie@robkitchin

http://www.nuim.ie/progcity@progcity

Small data / big data

Characteristic Small data Big data

Volume Limited to large Very large

Exhaustivity Samples Entire populations

Resolution and indexicality

Coarse & weak to tight & strong

Tight & strong

Relationality Weak to strong Strong

Velocity Slow, freeze-framed Fast

Variety Limited to wide Wide

Flexible and scalable Low to middling High

Urban big data

• Directedo Surveillanceo Digitisation of millions of

documents, films, audio recordings

• Automatedo Automated surveillanceo Digital deviceso Sensed and scanned data o Interaction and transactional datao IoT (Internet of things) and M2M

(machine to machine)

• Volunteered o Social mediao Sousveillanceo Crowdsourcingo Citizen science