Evaluation of Open Data is a systematic determination of open data merit, worth and significance, using criteria governed by a set of standards (Farbey, Land, & Targett, 1999). It is an essential procedure trying to ignite a learning and innovation process leading to a more effective data exploitation. Examples of questions to be answered by open data evaluation could be: what is the current status of published data against the best practices identified, how effectively these data are published or used, what are the most valuable data for users, what are the problems and barriers discouraging the publication and use of open data and in which extend these barriers affects users’ behaviour towards data usage. The answers on these questions will affect the next developments of an open data portal or initiative and the publication procedure.@en

Governments create and collect enormous amounts of data, for instance concerning voting results, transport, energy, education, and employment. These datasets are often stored in an archive that is not accessible for others than the organization’s employees. To attain benefits such as transparency, engagement, and innovation, many governmental organizations are now also providing public access to this data. However, in opening up their data, these organizations face many issues, including the lack of standard procedures, the threat of privacy violations when releasing data, accidentally releasing policy-sensitive data, the risk of data misuse, challenges regarding the ownership of data and required changes at different organizational layers. These issues often hinder the easy publication of government data.@en

The concept of open data itself is strongly associated with innovative capacity and transformative power (Davies, Perini, & Alonso, 2013). It is increasingly recognized that proactively opening public data can create considerable benefits for several stakeholders, such as firms and individuals interested in the development of value added digital services or mobile applications, by combining various types of Open Government Data (OGD), and possibly other private data. On the other hand, OGD also empowers scientists, journalists and active citizens who want to understand various public issues and policies through advanced data processing and production of analytics (Janssen, 2011a; Zuiderwijk, Helbig, Gil-García, & Janssen, 2014).@en

The chapter focuses on innovation processes aspiring to generate value through a purposeful and effective exploitation of data released in an open format. On the one hand, such processes represent a great opportunity for private and public organizations while, on the other, they pose a number of challenges having to do with creating the technical, legal and procedural preconditions as well as identifying appropriate business models that may guarantee the long term financial viability of such activities. As a matter of fact, while information sharing is widely recognized as a value multiplier, the release of information in an open data format through creative common licenses generates information-based common goods characterized by nonrivalry and nonexcludability in fruition. An aspect posing significant challenges for the pursuit of sustainable competitive advantages.@en

Data represents a key asset in virtually any aspect of society and economy. Open Data in particular represents a source of immense value, as social capital (Lampoltshammer & Scholz, 2017) as well as an asset for business cases. Governments and their public administrations are generating and collecting during their service a plethora of different kinds of data, as well as an enormous amount in terms of volume. To tab into the potential this data holds in terms of stimulating economy, as well as the development and enhancement of governmental service for the benefit of the public (see Fig. 6.1), a sophisticate Open Data Infrastructure is required.@en

The opening of data has grown tremendously over the past decade. More and more datasets have been opened to the public, application programming interfaces (APIs) gave been design for enabling the public to make use of real-time data and new apps based on this data have been developed. Data about policy-making, software code (open sources), documents, minutes, financial data and so on has been opened resulting in a large repository of government data that can be on open data portals and government websites. Nevertheless the potential is even more higher, as most of the data still are closed and not directly accessible by the public. Furthermore, more and more data is collected and can be share in nowadays words driven by The Internet of Things (IoT). The IoT consist of devices that are able to collect data such as GPS (geographical location), Compass, temperature, movement, pollution and so on. Devices collecting data combined with data analytics are expected to transform the government and society. This can provide insight into the energy consumption of smart cities (https://amsterdamsmartcity.com/projects/energy-atlas ) or the pollution (http://airindex.eea.europa.eu/ ). These initiates are all driven by the opening of data and extended by user-friendly apps to enable a large use by the public.@en

In developing open data policies, organizations aim to stimulate and guide the publication and use of data and to gain advantages from this. Often open data policies are guided by a high-level directive, such as those of the United States (Obama, 2009b) and the European Commission (European Commission, 2013c). Open data policies are important, as their purpose is often to ensure the long-term availability of government information to create transparency and thereby to contribute to citizens’ rights to public access to government information. This right is considered a fundamental tenet of democracy (Allen, 1992). Moreover, open data policies have the potential to increase the participation, interaction, self-empowerment and social inclusion of open data users (e.g. citizens) and providers alike, stimulating economic growth and innovation and realizing many other advantages.@en

Open data can be defined as data that is free of charge or provided at marginal cost, under an open licence, machine readable, and provided in an open format@en

Semantic technologies enable open data interoperability beyond the point of pure format and structure alignment.@en