Welcome to Konstantin Malysh's licentiate thesis seminar on Thursday April 24th at 13:15-15:00 in E:C

Thesis title: Towards understanding inter-organizational data sharing practices and technical tool needs

Author: Konstantin Malysh, Department of Computer Science, Lund University

Faculty opponent: Dr. Magnus Andersson, RISE

Examiner: Dr. Alma Orucevic-Alagic, LTH

Supervisor: Prof. Per Runeson, LTH

Co-supervisor: Dr. Johan Linåker, LTH

Date and time: Thursday 24 April at 13:15

Location: E:C, E-huset, LTH, Klas Anshelms väg 10/Ole Römers väg 3, Lund

Link to download thesis: To be added

Abstract

Background: Data quickly emerges as a core driver of businesses across the world due to rapidly expanding use in different areas, such as Machine Learning. In order for the data-related organizational operations to be efficient, the topic of data sharing has to be explored. This thesis focuses on understanding inter-organizational data sharing by exploring practices and challenges that are present within data-driven businesses.

Aim: The objective of this thesis is to explore inter-organizational data sharing practices and assess the need for governance and tools to support the related processes. We aim to identify and fill the research gaps on the data sharing needs and challenges in order to produce more specific requirements that would help organizations conduct their data sharing efficiently.

Research Methodology: We conducted the research in several steps according to the design science paradigms. We performed literature analysis with the goal of exploring the practices and challenges related to data sharing in existing research. Afterwards, we performed an empirical interview study with the representatives of data-driven companies located in Sweden to collect our own data on challenges and practices. Finally, we performed a case study in order to extend knowledge on data sharing by diving deep into one specific case of industrial data sharing in an industry-academia collaboration context, and validating our findings by exploring several adjacent cases.

Results: We present the results as two papers in this thesis. We observed and categorized the core challenges and aspects that come along with data sharing process, with privacy being considered one of the most important topics. We also presented a conceptual model of organizational entities involved in data sharing processes. Afterwards, we focused on Open Data Ecosystems and platforms, and observed and assessed incentives, challenges, governance and functionalities that are to be present in order for the ecosystem function effectively.

Conclusion: Inter-organizational data sharing is an important and complex concept that needs to be investigated. The process of ensuring the quality of data sharing practices should be done on a case-by-case scenario in order to satisfy the needs of all the actors involved, so that the challenges are minimized and the processes flow as efficiently as possible. Within our research, this will be achieved by having a mature governance model, being supported by a well maintained technological platform. Future work will include separately exploring the topics of technological tools and governance within Open Data Ecosystems and platforms with goal of obtaining a clear set of requirements needed for both aspects to be addressed effectively as a part of data sharing process.