Design Principles for A Big Data Platform: a Value Conscious Exploration
Kinnunen, Antti (2019)
Kuvaus
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Tiivistelmä
Problem space covering the design of Big Data is vast and multi-faceted. First and foremost, it relates to the disturbance caused by the Big Data phenomenon, affecting both the people and the processes of organizations. These disturbances are a result of design choices made, both relating to technology and to the approaches used in the exploitation of opportunities offered by Big Data. These design choices are, in the end, based on the values of the designers and processed either consciously or unconsciously.
This problem space was explored with the methods of Design Science. The objective was to develop a continuously evolving and growing Big Data platform. To ensure the platform would be maintainable and developable during the whole life cycle, including situations that are impossible to foretell, it was hypothesized that by examining the purpose of the platform and by identifying consciously the values related to the platform, Big Data technologies, and to the actual usage in the envisioned environment, design principles could be created with integrating the identified values. These design princi-ples would guide the development of the platform in the unpredictable situations of the future.
To discover the goals, benefits and the harms for the stakeholders created by the devel-opment and the usage of such a platform, methods of Value Sensitive Design were incorporated within the Design Science approach. These included empirical, conceptual, and technological investigations. During the technological investigations, two prototypes were built, the last of which will continue existence as the base of future development, and a cloud-based solution was briefly probed. Empirical investigations included project review of existing project documentation, organization of a workshop, employment of an empirical method to identify stakeholders, and the themed interviews of 16 stakeholders. Conceptual investigations were used in the identification of values.
Based on these investigations and literature seven general design principles of Big Data platforms were identified and their instantiations in the case project were described. Application of these principles in the project was also documented.
This problem space was explored with the methods of Design Science. The objective was to develop a continuously evolving and growing Big Data platform. To ensure the platform would be maintainable and developable during the whole life cycle, including situations that are impossible to foretell, it was hypothesized that by examining the purpose of the platform and by identifying consciously the values related to the platform, Big Data technologies, and to the actual usage in the envisioned environment, design principles could be created with integrating the identified values. These design princi-ples would guide the development of the platform in the unpredictable situations of the future.
To discover the goals, benefits and the harms for the stakeholders created by the devel-opment and the usage of such a platform, methods of Value Sensitive Design were incorporated within the Design Science approach. These included empirical, conceptual, and technological investigations. During the technological investigations, two prototypes were built, the last of which will continue existence as the base of future development, and a cloud-based solution was briefly probed. Empirical investigations included project review of existing project documentation, organization of a workshop, employment of an empirical method to identify stakeholders, and the themed interviews of 16 stakeholders. Conceptual investigations were used in the identification of values.
Based on these investigations and literature seven general design principles of Big Data platforms were identified and their instantiations in the case project were described. Application of these principles in the project was also documented.