{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T23:36:24Z","timestamp":1778542584457,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":23,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,6,15]],"date-time":"2019-06-15T00:00:00Z","timestamp":1560556800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["Research Training Group 2153"],"award-info":[{"award-number":["Research Training Group 2153"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,6,15]]},"DOI":"10.1145\/3307772.3331021","type":"proceedings-article","created":{"date-parts":[[2019,6,13]],"date-time":"2019-06-13T12:09:40Z","timestamp":1560427780000},"page":"460-473","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Industrial Demand-Side Flexibility"],"prefix":"10.1145","author":[{"given":"Nicole","family":"Ludwig","sequence":"first","affiliation":[{"name":"Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lukas","family":"Barth","sequence":"additional","affiliation":[{"name":"Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dorothea","family":"Wagner","sequence":"additional","affiliation":[{"name":"Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Karlsruhe, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Veit","family":"Hagenmeyer","sequence":"additional","affiliation":[{"name":"Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,6,15]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2005.05.002"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3208903.3208909"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00450-017-0343-x"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3208903.3210278"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eneco.2017.04.006"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1089\/10665270252935430"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/956750.956808"},{"key":"e_1_3_2_1_8_1","volume-title":"A density-based algorithm for discovering clusters in large spatial databases with noise","author":"Ester Martin","unstructured":"Martin Ester , Hans-Peter Kriegel , J\u00c3\u0171rg Sander , and Xiaowei Xu. 1996. A density-based algorithm for discovering clusters in large spatial databases with noise . AAAI Press , 226--231. Martin Ester, Hans-Peter Kriegel, J\u00c3\u0171rg Sander, and Xiaowei Xu. 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. AAAI Press, 226--231."},{"key":"e_1_3_2_1_9_1","unstructured":"Cheng Fan. 2015. TSMining: Mining Univariate and Multivariate Motifs in Time-Series Data. R package version 1.0.  Cheng Fan. 2015. TSMining: Mining Univariate and Multivariate Motifs in Time-Series Data. R package version 1.0."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2013.07.003"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2011.10.016"},{"key":"e_1_3_2_1_12_1","volume-title":"A Classification Scheme for Project Scheduling","author":"Herroelen Willy","unstructured":"Willy Herroelen , Erik Demeulemeester , and Bert De Reyck . 1999. A Classification Scheme for Project Scheduling . Springer US , Boston, MA , 1--26. Willy Herroelen, Erik Demeulemeester, and Bert De Reyck. 1999. A Classification Scheme for Project Scheduling. Springer US, Boston, MA, 1--26."},{"key":"e_1_3_2_1_13_1","volume-title":"Benchmark Instances for Project Scheduling Problems","author":"Kolisch Rainer","unstructured":"Rainer Kolisch , Christoph Schwindt , and Arno Sprecher . 1999. Benchmark Instances for Project Scheduling Problems . In Project Scheduling, Jan W\u0119glarz (Ed.). Springer , Boston, MA , 197--212. Rainer Kolisch, Christoph Schwindt, and Arno Sprecher. 1999. Benchmark Instances for Project Scheduling Problems. In Project Scheduling, Jan W\u0119glarz (Ed.). Springer, Boston, MA, 197--212."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0377-2217(96)00170-1"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2012.2218262"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2012.2195686"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Nicole Ludwig Lukas Barth Dorothea Wagner and Veit Hagenmeyer. 2019. Benchmark Dataset for \"Industrial Demand-Side Flexibility: A Benchmark Data Set\". KITOpen Repository. (2019).  Nicole Ludwig Lukas Barth Dorothea Wagner and Veit Hagenmeyer. 2019. Benchmark Dataset for \"Industrial Demand-Side Flexibility: A Benchmark Data Set\". KITOpen Repository. (2019).","DOI":"10.1145\/3307772.3331021"},{"key":"e_1_3_2_1_18_1","volume-title":"Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23","author":"Ludwig Nicole","year":"2017","unstructured":"Nicole Ludwig , Simon Waczowicz , Ralf Mikut , and Veit Hagenmeyer . 2017 . Mining Flexibility Patterns in Energy Time Series from Industrial Processes . In Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23 . - 24. November 2017, Frank Hoffmann, E. H\u00fcllermeier, and Ralf Mikut (Eds.). KIT Scientific Publishing, 13--32. Nicole Ludwig, Simon Waczowicz, Ralf Mikut, and Veit Hagenmeyer. 2017. Mining Flexibility Patterns in Energy Time Series from Industrial Processes. In Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017, Frank Hoffmann, E. H\u00fcllermeier, and Ralf Mikut (Eds.). KIT Scientific Publishing, 13--32."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3208903.3212051"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSG.2014.2336261"},{"key":"e_1_3_2_1_21_1","volume-title":"Plataniotis and Dimitris Hatzinakos","author":"Kostantinos","year":"2000","unstructured":"Kostantinos N. Plataniotis and Dimitris Hatzinakos . 2000 . Gaussian mixtures and their applications to signal processing. In Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real Time Systems, Stergios Stergiopoulos (Ed.). CRC Press , Boca Raton, Chapter 3. Kostantinos N. Plataniotis and Dimitris Hatzinakos. 2000. Gaussian mixtures and their applications to signal processing. In Advanced Signal Processing Handbook: Theory and Implementation for Radar, Sonar, and Medical Imaging Real Time Systems, Stergios Stergiopoulos (Ed.). CRC Press, Boca Raton, Chapter 3."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010997814183"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/SmartGridComm.2014.7007741"}],"event":{"name":"e-Energy '19: The Tenth ACM International Conference on Future Energy Systems","location":"Phoenix AZ USA","acronym":"e-Energy '19","sponsor":["SIGEnergy ACM Special Interest Group on Energy Systems and Informatics"]},"container-title":["Proceedings of the Tenth ACM International Conference on Future Energy Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3307772.3331021","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3307772.3331021","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:54:07Z","timestamp":1750204447000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3307772.3331021"}},"subtitle":["A Benchmark Data Set"],"short-title":[],"issued":{"date-parts":[[2019,6,15]]},"references-count":23,"alternative-id":["10.1145\/3307772.3331021","10.1145\/3307772"],"URL":"https:\/\/doi.org\/10.1145\/3307772.3331021","relation":{},"subject":[],"published":{"date-parts":[[2019,6,15]]},"assertion":[{"value":"2019-06-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}