EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 562 (2024) E3S Web of Conf., 562 (2024) 10003 References
Open Access
Issue
E3S Web of Conf.
Volume 562, 2024
BuildSim Nordic 2024
Article Number 10003
Number of page(s) 11
Section Digital Twin & Smart Buildings
DOI https://doi.org/10.1051/e3sconf/202456210003
Published online 07 August 2024
  1. European Commission, The European Commission’s priorities (2019). https://commission.europa.eu/strategy-and-policy/priorities-2019-2024_en#documents [Google Scholar]
  2. European Commission, Fourth Report on the State of the Energy Union (2019). https://commission.europa.eu/publications/fourth-report-state-energy-union_en [Google Scholar]
  3. European Commission, Driving energy efficiency in the European building stock: New recommendations on the modernisation of buildings (2019). https://commission.europa.eu/news/driving-energy-efficiency-european-building-stock-new-recommendations-modernisation-buildings-2019-06-21_en [Google Scholar]
  4. European Commission, Commission Recommendation (EU) 2019/1019 of 7 June 2019 on building modernisation (2019). https://eur-lex.europa.eu/legalcontent/EN/TXT/?uri=CELEX:32019H1019 [Google Scholar]
  5. C. Miller, F. Meggers, The Building Data Genome Project An Open, Public Data Set from Non-Residential Building Electrical Meters. Energy Procedia 122, 439-444 (2017). [Google Scholar]
  6. C. Miller, A. Kathirgamanathan, B. Picchetti, P. Arjunan, J.Y. Park, Z. Nagy, P. Raftery, B.W. Hobson, Z. Shi, F. Meggers, The Building Data Genome Project 2, energy meter data from the ASHRAE Great Energy Predictor III competition. Scientific Data 7, 368 (2020). [CrossRef] [PubMed] [Google Scholar]
  7. X. Jin, C. Fu, H. Kazmi, A. Balint, A. Canaydin, Q. Matias, F. Biljecki, F. Xiao, C. Miller, The Building Data Genome Directory – An open, comprehensive data sharing platform for building performance research. Journal of Physics: Conference Series 2600, 032003 (2023). [CrossRef] [Google Scholar]
  8. B. Dong, Y. Liu, W. Mu, et al., A Global Building Occupant Behavior Database. Scientific Data 9, 369 (2022). [CrossRef] [PubMed] [Google Scholar]
  9. European Commission, E-infrastructures for data and computing intensive science and the European Open Science Cloud (2023). https://joinup.ec.europa.eu/collection/rolling-plan-ict-standardisation/e-infrastructures-data-and-computing-intensive-science-andeuropean-open-science-cloud [Google Scholar]
  10. European Commission, European data strategy: Making the EU a role model for a society empowered by data (2023). https://commission.europa.eu/strategy-andpolicy/priorities-2019-2024/europe-fit-digital-age/european-data-strategy_en [Google Scholar]
  11. European Commission, European Strategy for Data, Real-time Linked Dataspaces (2024). https://dataspaces.info/common-european-data-spaces/#page-content [Google Scholar]
  12. European Commission, Common European Energy Data Space (2023). https://op.europa.eu/en/publication-detail/-/publication/43b8d2d1-6975-11ee-922001aa75ed71a1/language-en [Google Scholar]
  13. K.H. Andersen, S.K. Lien, K.B. Lindberg, H.T. Walnum, I Sartori, Further development and validation of the “PROFet” energy demand load profiles estimator. Proceedings of the IBPSA Building Simulation Conference. Bruges (Belgium), 1-3 September 2021. [Google Scholar]
  14. R. Kimball, J. Caserta, The Data Warehouse ETL Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data. WILEY & Sons (2004). [Google Scholar]
  15. M. Matskin, S. Tahmasebi, A. Layegh, A.H. Payberah, A. Thomas, N. Nikolov, D. Roman, A survey of big data pipeline orchestration tools from the perspective of the datacloud project. Proceedings of the Data Analytics Management Data Intensive Domains, 23rd International Conference DAMDID/RCDL. Moscow (Russia), 26-29 October 2021. [Google Scholar]
  16. A.A. Corodescu, N. Nikolov, A.Q. Khan, A. Soylu, M. Matskin, A.H. Payberah, D. Roman, Big Data Workflows: Locality-Aware Orchestration Using Software Containers. Sensors 21, 8212 (2021). [CrossRef] [PubMed] [Google Scholar]
  17. A. Thomas, N. Nikolov, A. Pultier, D. Roman, B. Elvesæter, A. Soylu, SIM-PIPE DryRunner: An approach for testing container-based big data pipelines and generating simulation data. Proceedings of the 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). Los Alamitos (USA), 27 June1 July 2022. [Google Scholar]
  18. Stackoverflow, Developer Survey (2023). https://survey.stackoverflow.co/2023/ [Google Scholar]
  19. D.J. Abadi, Column-stores vs. row-stores: how different are they really? Proceedings of the 2008 ACM SIGMOD international conference on Management of data. Vancouver (Canada), 9-12 June 2008. [Google Scholar]
  20. A. Khelifati, M. Khayati, A. Dignös, D. Difallah, P. Cudré-Mauroux, TSM-Bench: Benchmarking Time Series Database Systems for Monitoring Applications. Proceedings of the VLDB Endowment 16, 3363–3376 (2023). [CrossRef] [Google Scholar]
  21. Fang, C., Song, S., Guan, H., Huang, X., Wang, C., Wang, J. (2023). Grouping time series for efficient columnar storage. Proceedings of the ACM on Management of Data 1, 23 (2023). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.