JSON Dataset of Simulated Building Heat Control for System of Systems Interoperability

SND-ID: 2022-45

Creator/Principal investigator(s)

Jacob Nilsson - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering (EISLAB) orcid

Description

Interoperability in systems-of-systems is a difficult problem due to the abundance of data standards and formats.
Current approaches to interoperability rely on hand-made adapters or methods using ontological metadata.
This dataset was created to facilitate research on data-driven interoperability solutions.
The data comes from a simulation of a building heating system, and the messages sent within control systems-of-systems. For more information see attached data documentation.

Language

English

Research principal, contributors, and funding

Research principal

Luleå University of Technology

Funding

  • Funding agency: ECSEL Joint Undertaking (JU)
  • Funding agency's reference number: 826452
  • Project name on the application: Arrowhead Tools
Protection and ethical review

Data contains personal data

No

Method and time period
Geographic coverage

Geographic spread

Geographic location: Luleå Municipality

Geographic description: Some temperature data is taken from the SMHI weather station in Luleå

Publications

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Nilsson, J., Delsing, J., & Sandin, F. (2020). Autoencoder Alignment Approach to Run-Time Interoperability for System of Systems Engineering. In IEEE 24th International Conference on Intelligent Engineering Systems (pp. 139–144). https://doi.org/10.1109/INES49302.2020.9147168
URN: urn:nbn:se:ltu:diva-80561
DOI: https://doi.org/10.1109/INES49302.2020.9147168

Nilsson, J., Delsing, J., Liwicki, M., & Sandin, F. (n.d.). Machine Learning based System–of–Systems Interoperability : A SenML–JSON Case Study. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-87849
URN: urn:nbn:se:ltu:diva-87849

If you have published anything based on these data, please notify us with a reference to your publication(s). If you are responsible for the catalogue entry, you can update the metadata/data description in DORIS.

Dataset 1
JSON Dataset of Simulated Building Heat Control for System of Systems Interoperability

Description

The data comes in two semicolon-separated (;) csv files, training.csv and test.csv. The train/test split is not random; training data comes from the first 80% of simulated timesteps, and the test data is the last 20%. There is no specific validation dataset, the validation data should instead be randomly selected from the training data. The simulation runs for as many time steps as there are outside temperature values available. The original SMHI data only samples once every hour, which we linea

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Version 1

Citation

Jacob Nilsson. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering (EISLAB) (2022). JSON Dataset of Simulated Building Heat Control for System of Systems Interoperability. Swedish National Data Service. Version 1. https://doi.org/10.5878/1tv7-9x76

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Data format / data structure

Other

Creator/Principal investigator(s)

Jacob Nilsson - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering (EISLAB) orcid

Data collection

  • Mode of collection: Simulation
  • Description of the mode of collection: Building temperature simulation.
  • Data collector: Luleå University of Technology
  • Instrument: Python script
  • Source of the data: Events/Interactions, Physical objects

License

Creative Commons  Attribution 4.0 International (CC BY 4.0)
Dataset 2
Temperature Data Luleå Summer 2018

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Associated documentation

Description

This dataset is used as input for the thermodynamic building simulation found on Github, where it is used to get the outside temperature and corresponding timestamps.

The temperature measurements were downloaded from SMHI.

Version 1

Citation

Jacob Nilsson. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering (EISLAB) (2022). Temperature Data Luleå Summer 2018. Swedish National Data Service. Version 1. https://doi.org/10.5878/257p-e437

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Data format / data structure

Numeric

Text

Other

Creator/Principal investigator(s)

Jacob Nilsson - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering (EISLAB) orcid

Data collection

  • Mode of collection: Non-participant field observation
  • Description of the mode of collection: Temperature data from SMHI
  • Data collector: SMHI

Copyright

SMHI under Creative Commons Attribution 4.0 SE

License

Creative Commons  Attribution 4.0 International (CC BY 4.0)

Contact for questions about the data

This resource has the following relations

Published: 2022-04-19