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Fraunhofer-Institut für System- und Innovationsforschung ISI
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PublicationWP5 Recommendations and observatory. D5.2 Final report( 2018)
;Bachlechner, Daniel ;Akca Prill, Melek ;Abels, Sven ;Gabor, Marcel ;Ursic, Helena ;Heijnen, Vivian ;Custers, Bart ;Lahiguera, Rubén ;Castillo, Conrado ;Merlo, LauraHeilingbrunner, KláraAs a final report, this document provides an overview of the main project results. It includes a description of the EuDEco model, an overview of the online survey and the final set of recommendations, and presentations of the tools developed within the scope of the project. The observatory is not addressed since a dedicated deliverable is prepared at the same time. -
PublicationWP5 Recommendations and observatory. D5.3 Observatory report( 2018)Bachlechner, DanielThe report will show the results of the observatory on the European Data Economy and its development.
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PublicationWP5 Recommendations and observatory. D5.1 Validation report( 2017)
;Bachlechner, Daniel ;Ursic, Helena ;Lahiguera, Rubén ;Abels, Sven ;Gabor, MarcelWeigandt, ChristofThis report integrates legal, socio-economic and technological requirements and barriers, and presents the results of a comprehensive validation of the requirements and barriers as well as other intermediate results. The validation consists of two steps: the internal reflection of results in the light of all previous research attaching particular emphasis to the final model and the preliminary set of recommendations, and the external validation of results within the scope of stakeholder workshops. Of particular relevance was the final validation workshop held co-located with the i-KNOW 2017 conference. -
PublicationWP3 Test of the model. D3.2 Test report( 2017)
;Bachlechner, Daniel ;Ursic, Helena ;Custers, Bart ;Castillo, Conrado ;Merlo, Laura ;Olmedo, Michel ;Lahiguera, Rubén ;Süveges- Heilingbrunner, Klara ;Süveges, TamásFehér, SándorThe report will present the results of the test phase of the refined model. -
PublicationWP3 Test of the model. D3.3 Report on the analysis of test results( 2017)
;Bachlechner, Daniel ;Ursic, Helena ;Custers, Bart ;Heijnen, Vivian ;Abels, Sven ;Weigandt, Christof ;Castillo, Conrado ;Merlo, Laura ;Lahiguera, RubénSüveges-Heilingbrunner, KlaraThe report will provide the results of the legal, socio-economic and technological analysis of the test results. -
PublicationWP3 Test of the model. D3.1 Report on the refined model( 2016)
;Bachlechner, Daniel ;Rung, Sven ;Ursic, Helena ;Custers, Bart ;Abels, Sven ;Olmedo, MichelMosqueda, Maria L.The report will present the results of the second integration of results into the refined model of the data economy. -
PublicationWP1 Mapping the scene. D1.2 Report on the analysis of framework conditions( 2015)
;Bachlechner, Daniel ;Rung, Sven ;Alfaro, Antonio ;Merlo, Laura ;Ruz, Franz ;Abels, Sven ;Gabor, Marcel ;Haut, Leonardo ;Dupont, Anthony ;Laude, Ida ;Dos Santos, Stephanie ;Custers, BartUrsic, HelenaD1.2 reports on the findings of an analysis of framework conditions relevant in the context of the data economy from a legal, a socio-economic and a technological perspective. The analysis is a key foundation for the creation of an initial, heuristic model of the European data economy. The deliverable clearly pays most attention to the discussion of the framework conditions but also presents a first integrative discussion as well as a pragmatic approach towards a conceptual framework. -
PublicationWP1 Mapping the scene - D1.3 Case study report( 2015)
;Huertas, Diana C. ;Merlo, Laura ;Rung, Sven ;Bachlechner, Daniel ;Alfaro, Antonio ;Castillo, Conrado ;Olmedo, Michel ;Mosqueda, Maria L. ;Abels, Sven ;Gabor, Marcel ;Haut, Leonardo ;Dupont, Anthony ;Laude, Ida ;Custers, BartUrsic, HelenaD1.3 describes a set of five case studies relevant in the context of the EuDEco project. Case studies are considered relevant if they are initiatives focusing on the promotion of big data and data reuse or pilots facilitating data reuse in one form or the other. The case studies were expected to allow gaining a better understanding of the pitfalls and challenges related to big data and data reuse.