Abstract
Data management is central to many CS innovations: Smart home technologies and the Internet of Things, for example, are based on processing data with high velocity. One of the most interesting topics emphasizing several challenges in this field is real-time data analysis. In secondary CS education, it is only considered marginally. So far, there are no tools suitable for general-purpose real-time data analysis in school. In this paper, we discuss this topic from a secondary CS education perspective. Besides central concepts and differences to traditional data analysis using relational databases, we describe the development of a general-purpose \(\textsf {Snap}{\textit{!}}\) extension that allows accessing and processing data from various sources. Thereby, students are enabled to conduct data analyses using, for example, sensor data or web APIs. With the example of a weather station, we outline how this tool can be used in school for analyzing sensor data generated in the classroom.
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- 1.
The “continuous query language” (CQL) is similar in syntax to SQL, but in particular allows using “sliding windows”, which makes it suitable for data stream analysis (cf. [1]).
- 2.
Soft real-time allow even frequent misses of the deadline, as only service quality is being influenced (cf. e.g. [3]).
- 3.
Hard real-time strongly requires adherence to a deadline, as exceeding it results in a system failure. Firm real-time tolerates missing the given deadline infrequently, but the analysis results become irrelevant after the deadline and the quality of service is degraded.
- 4.
“A data stream is a real-time, continuous, ordered (implicitly by arrival time or explicitly by timestamp) sequence of items. It is impossible to control the order in which items arrive, nor is it feasible to locally store a stream in its entirety.” [4].
- 5.
- 6.
We limited processing of queries to one time per second to prevent performance issues. Yet, this limit can easily be changed by modifying the block in \(\textsf {Snap}{\textit{!}}\).
- 7.
- 8.
An exemplary project was described by the Raspberry Pi Foundation: https://www.raspberrypi.org/blog/school-weather-station-project/.
- 9.
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Grillenberger, A., Romeike, R. (2017). Real-Time Data Analyses in Secondary Schools Using a Block-Based Programming Language. In: Dagienė, V., Hellas, A. (eds) Informatics in Schools: Focus on Learning Programming. ISSEP 2017. Lecture Notes in Computer Science(), vol 10696. Springer, Cham. https://doi.org/10.1007/978-3-319-71483-7_17
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DOI: https://doi.org/10.1007/978-3-319-71483-7_17
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