Using an Elastic Stack as a Base for Logging and Evaluation of Public Displays
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ISSN der Zeitschrift
Mensch und Computer 2023 - Workshopband
MCI-WS13: Methods and Tools for (Semi-)Automated Evaluation in Long-Term In-the-Wild Deployment Studies
This paper describes the usage of the Elastic Stack as a powerful and flexible base for capturing, storing, analyzing, and visualizing log data, as well as conducting evaluations of public displays. Nowadays, public displays are an essential element in providing information from a variety of applications and systems. As 24/7 in-person observations are impossible, support is needed for evaluation of the usage for single unit installations as well as large-scale public display networks. A software-supported solution can automate the most common data collection steps and provide a common base for further evaluation. In this paper, we present an ongoing case study on our technical solution for supporting long-term 24/7 evaluation with the Elastic Stack in any kind of public display installation. The solution is based on a logging framework and the Elasticsearch, Logstash, and Kibana – tool stack. We present the technical solution, the requirements for our implementation, and possible evaluation approaches.