Published June 5, 2018 | Version v1
Conference paper Open


  • 1. 1. International Centre for Decision Sciences and Forecasting, Progress & Business Foundation, J. Lea street 12B, PL-30-048 Kraków, Poland 2. Department of Decision Sciences, AGH University of Science and Technology, Kraków, Poland


Large digital knowledge repositories (DKRs) are an important component of Open Science. The latter is a challenging area of rapid technological and social development, where ICT innovations and their use cases are coordinated with research policy measures at different levels, from regional to European. DKR development is deeply rooted in the PEST environment and re­quires a thorough strategic plan of the social, economic and research impact over a mid to long-term perspective. It should also be aligned with technological progress, specifically in the emerging areas of Artificial Intelligence, Big Data, Internet of Things, and Global Expert Systems.

Despite of the aforementioned relevance, there exist very few publicly accessible DKR strategies or desc­riptions of strategy building approaches, and those available refer only to e-learning course reposi­tories. This has created a need to develop methodological foundations for DKR-oriented strategic planning, to build new ICT-based tools and collaborative approaches, and apply them to satisfy the project goals in the context of EU S&T policies. This paper reports the strategy building process for an innovative knowledge repository (referred to as the Platform) developed within the flagship Horizon 2020 project “Training towards a society of data-savvy inform­ation professionals to enable open leadership Innovation” (acronym MOVING,, its methodological background and outcomes. Relevant input to the strategy results from a forward-looking activity focussed on the identification of internal and environmental factors influencing the future performance and impact of the Platform. It combines a four-round/real-time novel policy and decision Delphi survey with an impact model established with Anticipatory Networks. The forecasting model parameters are those delivered as outcomes of the survey. They are supplied by the project partners, or result from the project Description of Work. The survey results are then used in a final collaborative roadmapping on the Platform exploitation in the PEST context.

The strategy building process presented here involves two stages. Stage 1 is devoted to establishing the boundary conditions for the Platform’s activity and user community building, while Stage 2 delivers the Final Strategy with plausible exploitation resulting scenarios. The second stage includes an action plan aimed at ensuring the Platform’s digital sustainability, financial viability and social acceptance. In this presentation of the DKR strategy building process, we will show in more detail the methodology of generating future visions of the Platform functioning with a flexi­ble Delphi survey support system that is based on a novel forward extrapolation methodology. It offers a variety of question and/or state­ment types, so­phi­sticated statistical analysis and other uncertainty handling methods, as well as a user-friendly interface. It can be run in various  modes that suit the survey goals and gather expert knowledge in multiple rounds, as a real-time Delphi or as a hybrid of both. The cloud-based Delphi application is offe­red to the project team in SaaS mode, with some PaaS features ( It can also be used as a ba­sis for designing further customised expert information retrieval and fusion exercises for a broad spectrum of research needs.


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MOVING – Training towards a society of data-savvy information professionals to enable open leadership innovation 693092
European Commission