3. Appropriation and use of open government data

3.1 Dissemination and adoption of innovation

Some areas of public administration have a history of supplying open data. Over time, this led to the creation of efficient user communities and networks specialised in intermediaries, such as finance and agriculture. These areas can serve as examples of appropriation and use of open data.

The recommendations of this guide focus on areas in which availability and use of open data are still uncommon; this makes the following recommendations for the dissemination and adoption of innovation more useful. This guide is based on the assumption that the government also has responsibility for promoting dissemination of innovations.

Efficient management of open government data requires understanding how potential users position themselves in relation to innovation. From a broader point of view, the adoption of innovation is a process in which individuals or organisations first become aware, then form opinions in relation to the innovation, followed by the decision to adopt or reject it, and, finally, agreement to implement and consolidate the adoption ¹⁴.

The decision to adopt an innovation is influenced by the factors shown in Table 2.

Quadro 2: Factors that influence the adoption of innovations

Individuals and organisations also have different attitudes toward the adoption of innovation, which in turn is reflected in the tendency to have an aversion to risk, the perceived value, and the resources made available for adoption. The following can be identified as innovators:

1. Those who are willing to take the risk of becoming pioneers.
2. Adopters who are also innovators, but are more conservative and risk-averse.
3. Those who adopt innovation because they are driven by external pressure, and those who refuse to adopt innovation.

These behaviours are also influenced by the nature of innovations: Radical innovations that require new skills and make current skills obsolete represent higher risk than incremental innovations, which are built on current skills and knowledge.

Individuals and organisations also evaluate innovations according to their legitimacy in society, and the recognition and reduction of risks of adoption allow convergence toward similar solutions of reference.

Sharing information about successful experiences with adopting open government data contributes to the dissemination process. Spaces for discussion, like blogs and forums, such as those developed by the United Kingdom15 and the United States16 government introducing creation of groups ¹⁷ focused on helping with the adoption and dissemination of innovations, can be used as examples for adoption by disseminating organizations. These groups also help with the promotion and dissemination of positive experiences, and even provide manuals and guides for orienting new cases.

As promoters of innovation dissemination become familiar with the positions taken by potential adopters towards these factors, they will have better conditions for defining efficient dissemination processes. Investigation of the potential community of users, with possible segmentation into homogenous groups, should be done initially in order to prioritise and find the adequate form of treatment.

These efforts will probably reduce users’ resistance and, therefore, speed up the adoption of innovations (of open government data) that represents continuity related to data that is already being used by an established community, which in turn has developed a culture with regard to current usage. The same can be applied to data with simpler and better-defined semantics, such as (statistical) data previously designed and created with the aim of dissemination. Open government data that depend on collective adoption (i.e., data whose utility depends on co-production with the community) will run into a slower adoption process.

Data that are sub-products of internal governmental administrative processes have more complex semantics, since, in order to be correctly interpreted, they require users to have a proper understanding of these processes.

The natural dynamics of public administration imply frequent process changes and, consequently, data changes as well, which could create difficulties in interpretation of historical data series. Therefore, maintenance of metadata and ongoing guidance services for users represent a significant challenge to data suppliers/publishers, and could result in an eventual need for additional treatment of material prior to publication.

For that reason, starting with open data with simple semantics will be easier for some types of agencies: those that do not have the conditions to provide more structured support to users and comply with legal requirements; or those that already have a history of using the data and experience with institutionalised solutions, or with important data with significant volume for users, so they will be able to create structures themselves, directly or with the help of intermediaries, to make use of the data viable.

Entry barriers for publishers and users are also represented by perceived skill requirements and additional effort, including technical resources needed for implementation, indicating the importance of the government’s role as a driving force in the process.

Introduce mechanisms to help prioritise datasets for release An effective chain of external intermediaries can reduce many of these barriers and serve as an important agent in promoting adoption, taking into account their closer relation with users and capacity to supply more appropriate information that meets user needs. This proximity can be further strengthened, allowing for viable actions, such as tools that allow intermediaries and users to request new datasets or send comments and queries about already published datasets, such as a “Data Request” 18, and also hold events with groups interested in the issue19. Having an email address or other mechanism for contact that is clearly displayed alongside already published datasets, with invitations for feedback, is one way of capturing data requests. Ensuring any email addresses or other communication mechanisms (e.g. social media) are actively monitored to respond to requests as they come in is essential.

3.2 The adoption process

Individual or organisational decisions to adopt innovation also take place in stages in which the promoter plays an important role, as shown in Figure 3.

Figura 3: Stages of adopting innovations

During the initial stages, adopters (individuals or organisations) form opinions (not yet totally well-founded) about innovations and their utility. After that, they decide whether to continue the involvement. As for voluntary adoption of innovation, which is the case with open government data, promoters of innovation dissemination should be limited to the role of just guiding the process. Adopters will then form their own views regarding the innovation and will decide on the best forms of appropriation, which might be different from those sought by data publishers, and make full (or even inadequate) use of the innovation.

Adopters depend on the information and support provided by producers, intermediary chains, or communities of users, which shows the need for a proactive stance by producers in coordination these activities.

Projects can be considered successfully concluded only when innovations are no longer a subject that still deserves attention (unless they fail) and when the changes brought about in user environments and daily practices have been consolidated. In the case of open data, this can be represented by consolidation of chains of intermediaries and creation of social traditions using the data.

Ensuring continuity of use is an ongoing challenge. Users will evaluate discrepancies between their expectations and usage experiences, the investments made for adoption, and established behaviours, which demonstrates the importance of the quality of the service provided by publishers and support for users.

Increasing familiarity with open government data will motivate users to employ more advanced and critical uses for continuity of their businesses, with growing expectations of comprehensiveness, availability, and data quality. Government organizations will then face the challenge of continuing to improve and mature service provision, delivery, and support, and managing producer and intermediary chains.

The appropriation of open government data can be seen as a causal chain between enablers (resources) and impacts (generated values), mediated by innovation mechanisms. Among enabler factors, besides producers’ technical resources, this guide gives special mention to the ability of potential users and intermediaries to gather open government data (organisational and technical); producers from government organizations or official funding agencies play an important role in this process.

The mechanisms used by innovation intermediaries for appropriation (generation and implementation of innovation, dissemination, and mobilisation) are necessarily shared among producers, intermediaries, and users.

In this process of enabling, implementing, and delivering benefits, the leadership role is essentially played by the government:

• Offering the necessary resources: open government data itself, under a licence that enables anyone to access, use and share the data - commercially and non- commercially;access infrastructure; skills; useful information about the dataset; and management.
• Creating favourable “conversion factors” that encourage innovation mechanisms to use open government data for generation of ideas, conversion of ideas into products and services, and dissemination of innovations.

In other words, when they have access to data, information about the dataset, resources for their use, and the skills to evaluate evaluating their utility, users will feel free to make a qualified decision about adoption, according to the Figure 4 below.

Figura 4: Chain of events in deciding to adopt innovation

This chain is not complete without evaluation activities, in order to get evidence of social and economic gains that serve as feedback and motivation for the process.

It is important to point out that the efficacy of open government data initiatives is systemic in nature and depends, in large part, on the competencies and attitudes of networks of intermediaries and users. Therefore, it becomes more evident that effective dissemination of open government data requires continuous cooperation between producers/publishers and chains of intermediaries and users.

Incremental innovations can be identified by consultation with users and observation of tendencies, whereas radical innovations (also known as disruptive innovations) depend more on innovative entrepreneurs who seek to meet needs that are not yet fully recognised by users. These innovations, although initially relying on small markets, can generate greater and more sustainable competitive advantages.

Although more visible open government data innovations deal with creating new products and services, there is also the creation of new processes and businesses, and management of the government.

Classic textbooks on the subject of innovation help in understanding the concepts, identification of opportunities, and guidance for implementation. Some examples are:

• Funding Authority for Studies and Projects (FINEP), Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data, 3rd edition, 1997, available at http://www.finep.gov.br/images/apoio-e-financiamento/manualoslo.pdf
• Clayton M. Christensen, The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, M.Books, 2012.

Among the institutions supporting innovation and entrepreneurship, the following can be mentioned:

• Innovation Unit Subsecretary under Secretary for Innovation and Partnerships, State of São Paulo, which created the Paulista Network for Government Innovation (igovsp.net) and operates the SPUK project with support from the government of the United Kingdo.
• Web Technologies Study Center of the Brazilian Network Information Center.
• Brazilian Service to Support Micro and Small Businesses (Sebrae) (www.sebrae.com.br).
• Financing Agency for Studies and Projects (www.finep.gov.br).
• Nesta (www.nesta.org.uk).
• International business lounges from the Apps for Europe competition (www.appsforeurope.eu).
• Open Data Institute?

International research conducted by the Open Data Institute²¹ indicates that most open data companies are new (in existence for less than 10 years and employing less than 10 workers), although there are also some major companies that generate important business based on open data. Therefore, the link between dissemination of open government data and promotion of entrepreneurship becomes more evident, because public policies motivate participation of individual entrepreneurs and start-ups in the sector.

There are several national and international institutions specialised in developing open data ecosystems that promoters of open government data dissemination can tap into. Among the more active non-governmental entities are:

• Open Data Institute (ODI) (theodi.org).
• Open Data Foundation (www.opendatafoundation.org).
• Open Data 500 Global Network (www.opendata500.com).
• Center for Technology in Government (www.ctg.albany.edu), in Albany, New York.

Government organizations include:

• Brazilian Open Data Portal (dados.gov.br).
• Open Government São Paulo (http://www.governoaberto.sp.gov.br/).
• Open Government Project of the United Kingdom (data.gov.uk).
• JoinUp programme of the European Union (https://joinup.ec.europa.eu/).
• Open Data project of the US government (https://www.data.gov/).

These projects have generated knowledge and useful practices that contribute to a whole chain of specialised support formed by start-ups, entrepreneurs, and other supporting institutions, investors, consultants, promoters, and so on.