The publicly funded ESA Copernicus and NASA Landsat earth observation programs are publishing their data as open data in the promise of 30 billion euro of financial benefit for the EU as well as 50.000 new jobs, both by 2023. The move by these two space agencies fits in a larger pattern of ‘new space’, in which the launch and exploitation of satellites are moved from national agencies to private commercial stakeholders. The data offered by ESA and NASA are published as open data intended for reuse with the objective to create viable value-adding earth observation services, i.e. services which use big and open earth observation as a resource for analytics and provide incentives for all participants, including the client and user, to continue the service provision. Furthermore, the earth observation data are big data, as it satisfies the criteria of high volume, variety and velocity increasing the effort required for handling the data. Even though the market for value-adding earth observation services is growing and has the potential to become the most important market in the whole earth observation value chain from rocket to service, the initial promises of the release of the data are not going to be accomplished at the current pace. Within searched academic literature and during conversations with practitioners, the lack of a structured approach to creating these viable value-adding services has been observed. Furthermore, the research articles on this topic are very much technology-oriented, with only very few articles invoking the interests of stakeholders to make a service design viable. And none of these followed a method for creating the service. This thesis addresses the lack of such a method for the creation of viable services using big and open earth observation data as a resource. Specifically, four knowledge gaps are identified: The first and second knowledge gaps concerned the lack of viable services which used a structured method for their design in the academic literature of respectively the narrow focus area of big and open earth observation data as well as in the larger area of earth observations which includes the previous narrow focus area. The third knowledge gap concerns the lack of factors of big and open earth observation data which influence the viability of a service design within the searched academic literature and the fourth concerns the actual lack of a structured method to guide the design of viable services which use big and open earth observation data as a resource. Together, these knowledge gaps lead to the formulation of the following research objective: “to design a method targeted at service providers for the creation of viable services which use big and open earth observation data as a resource.” The artefact which is developed is a method which guides a service designer through the process of creating a viable service. Following the method results in creating a service design which is both feasible, i.e. technologically possible, and viable, i.e. provides sufficient incentives for all stakeholders involved to carry on its provision. The approach for structuring the creation of the method is the design science research approach for information systems. The demarcation of the problem is the first activity within this approach, and it uses a structured literature review as well unstructured explorative interviews. This is followed by a literature review on influencing factors, using only a structured literature review as a research method. The requirements gathering activity employs a case study method, in which participant-observations and interviews are used for information gathering within three cases. Then, creative methods are used in the design activity to create the artefact. For the following demonstration of the artefact, a case study is again used. Finally, for the evaluation of the artefact a survey based on the combined UTAUT-ECT theory and observations are used to evaluate whether the artefact attains its objectives, and improvements are suggested based on the evaluation and the demonstration. During this research, the author was a research intern at CGI Netherlands in the Space, Defence and Intelligence department, which allowed for rich observations and access to cases. The result is the SIMEO-STOF method consisting of five phases. It combines the Service Innovation Method for Earth Observation (SIMEO) with the STOF model tailored for the earth observation domain. The first phase guides a designer through the process of finding together with a client a new service idea based on the current capabilities of earth observation analytics and the business processes of the client. Linking the earth observation capabilities to the limitations of current earth observation data supply allows for the rapid exclusion of unfeasible or unviable ideas. Any ideas that pass this initial set of limitations can proceed to the second phase. In this service domain, essential aspects of the value proposition are defined. This is followed by the technology phase, where principles of security and big data computing are set as well as a first architecture of the IT systems. Then, acquisition of external resources and inter-organizational relations are discussed in the organizational phase. Finally, the amount and form of value retained by the service provider are discussed in the financial phase. As a demonstration, the artefact is applied to the case of a crude and refined oil transhipment provider in the harbour of Rotterdam. The result of the application is a service design which is most likely to be viable, considering some issues still need resolving. Whilst not being definitively viable, the identification of issues which require resolution to achieve viability is an outcome which gets as close as possible to a viable design. The artefact is evaluated for internal and external validity, respectively whether it fulfils the quality requirements and whether it fulfils its objective. Both were included in a survey held amongst employees of a service providing company interested in the use of the SIMEO-STOF method. Whilst the limited number of responses did not allow for any statistical analysis, the descriptive statistics and observations allowed for the concussion of a generally positive evaluation. Measured by the attitude towards using the SIMEO-STOF method, the method fulfils its objective of facilitating the creation of viable services which use big and open earth observation data as a resource. Whilst there is a mixed response to the quality requirements, observations indicate that part of these can be explained by different levels of expectation. Some participants thought of a future use for the artefact and judged the quality requirement based on this instead of the actual objective. In terms of academic contributions, this research contributes to all four identified knowledge gaps. Foremost, it provides a viable service design method in form of the SIMEO-STOF method. This extends the service design literature to the application domain of earth observations, which has not previously been viewed from this perspective. Furthermore, factors of big and open earth observation data that contribute to the understanding of its effects on viable service design have been identified, in direct response to a further knowledge gap. Ultimately, the result of the SIMEO-STOF method demonstration is a viable service design created with a structured method, which is a contribution to the first and second knowledge gaps. In terms of societal contributions, the SIEMO-STOF method may accelerate growth in the ‘value-added EO services’ market, not only allowing service providers to more efficiently and effectively design viable service and create value, it may also lead to increased market growth on the suppliers side and an argument for open data publishers for the value of their activities. Though the use of the SIMEO-STOF method, EO service providers may be able to achieve the expected breakthrough of EO services within the broader society, which is one of the objectives of the ESA open data portal. One of the principal limitations of this research comes from the choice of case study as the main research method, which limits the generality of the results. This is valid for the environment form which requirements are gathered, the type of data used and the design perspective of a service provider which is taken. The author suggests further research to include cases which cover aspects previously not included, for example, a business to consumer service, non-satellite earth observation data, and the inclusion of cases from different service providers. Another important limitation concerns the novel application of the UTAUT-ECT theory in a novel wats, including to an information system which is not a practical implementation of a technology but a method. Combined with the reduced number of respondents in the survey, the UTAUT-ECT-model adapted from theory for this research could not be tested statistically. Future research could focus on repeating the novel application of the theory with sufficient respondents to allow for validation of its application. The objective of this research is the design of a method targeted at service providers for the creation of viable services which use big and open earth observation data as a resource. Considering the successful demonstration, and the generally positive evaluation of the SIMEO-STOF method, the author considers this objective to be attained.

To address complex societal issues, cross-sector partnerships are needed that specifically aim to create value to address such challenges. Data collaboratives are initiatives that encourage and promote such partnerships, by the collection, sharing, or processing of data. Data collaboratives are faced with barriers that complicate collaboration between data contributors and data users. As a result, the potential of public value creation is not being reached. To overcome these barriers, decision-makers in data collaboratives need a better understanding of the Trusted Data Intermediary as a coordination mechanism. Trusted Data Intermediaries are entities entrusted with enabling data transactions between data contributors and data users across sectors, thereby generating value for collaborators, and enabling the creation of public value. Currently, academic knowledge on how these intermediary entities is absent. By a qualitative, exploratory multiple-case study, descriptive business models of six cases are developed and analyzed. From the analysis, it was found that Trusted Data Intermediaries implement different business models, depending on their characteristics in specialization to specific segments of data contributors and users. Further, the implementation may depend on the profit motive and chosen centrality of data storage. Based on these dependencies, two Trusted Data Intermediaries' business model archetypes are developed: the Generic archetype and the Specialized archetype. In addition, variations to these archetypes are discussed. As the two archetypes offer an initial theory on Trusted Data Intermediaries, next steps may include the testing of the archetypes on more cases, as well as extending the theory for Trusted Data Intermediaries with other characteristics.