Exploration of data analytics for ground segment in space systems

Bedir Tekinerdogan*, Bedia Acar, Çağrı Cabıoğlu, Damla Savaş, Nebi Vuran, Şenol Tekdal, Ümit Gürsoy

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review


Space systems have to deal with massive spatio-temporal Earth and Space observation data collected by space-borne and ground-based sensors. Despite the data latency in communications, data is collected at enormous rates, and a sophisticated network of ground stations is set up to collect and archive telemetry data. The data that is received at the ground segment can be made available to the end-users. Beyond archiving data, the available data provides opportunities for data analytics that can support the decision-making process or provide new insight for the target requirements. Unfortunately, for practitioners, it is not easy to identify the potential and challenges for data analytics in the space domain. In this paper, we reflect on and synthesize the findings of existing literature and provide an integrated overview for setting up and applying data analytics in the space systems context. To this end, we first present the process as adopted in space systems, and describe the data science and machine learning processes. Finally, we identify the key questions that can be mapped to data analytics problems.

Original languageEnglish
Title of host publicationBusiness Modeling and Software Design - 10th International Symposium, BMSD 2020, Proceedings
EditorsBoris Shishkov
Number of pages10
ISBN (Print)9783030523053
Publication statusPublished - 7 Jul 2020
Event10th International Symposium on Business Modeling and Software Design, BMSD 2020 - Berlin, Germany
Duration: 6 Jul 20208 Jul 2020

Publication series

NameLecture Notes in Business Information Processing
Volume391 LNBIP
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356


Conference10th International Symposium on Business Modeling and Software Design, BMSD 2020


  • Data analytics
  • Ground segment
  • Space systems


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