{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T04:23:34Z","timestamp":1744777414749,"version":"3.40.4"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031877773","type":"print"},{"value":"9783031877780","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-87778-0_29","type":"book-chapter","created":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T16:22:27Z","timestamp":1744734147000},"page":"294-305","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Benchmarking STAC Ecosystem Server Backends in\u00a0Dataset Creation Applications"],"prefix":"10.1007","author":[{"given":"Alexandru","family":"Munteanu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriel","family":"Iuhasz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Silviu","family":"Panica","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,4,16]]},"reference":[{"key":"29_CR1","unstructured":"Abernathey, R., Paul, K., Hamman, J., et\u00a0al.: Pangeo NSF Earthcube proposal (2017)"},{"key":"29_CR2","unstructured":"Apache Software Foundation: Hadoop. https:\/\/hadoop.apache.org"},{"key":"29_CR3","doi-asserted-by":"publisher","unstructured":"Baumann, P., Misev, D., Merticariu, V., et\u00a0al.: Rasdaman: Spatio-temporal datacubes on steroids. In: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 604\u2013607. SIGSPATIAL 2018, Association for Computing Machinery (2018). https:\/\/doi.org\/10.1145\/3274895.3274988","DOI":"10.1145\/3274895.3274988"},{"key":"29_CR4","doi-asserted-by":"crossref","unstructured":"Brewer, E.A.: Kubernetes and the path to cloud native. In: Proceedings of the sixth ACM Symposium on Cloud Computing, p. 167 (2015)","DOI":"10.1145\/2806777.2809955"},{"issue":"21","key":"29_CR5","doi-asserted-by":"publisher","first-page":"8398","DOI":"10.1080\/01431161.2021.1978584","volume":"42","author":"M Chaves","year":"2021","unstructured":"Chaves, M., Soares, A.R., Sanches, I.D., Fronza, J.G.: CBERS data cubes for land use and land cover mapping in the Brazilian Cerrado agricultural belt. Int. J. Remote Sens. 42(21), 8398\u20138432 (2021). https:\/\/doi.org\/10.1080\/01431161.2021.1978584","journal-title":"Int. J. Remote Sens."},{"key":"29_CR6","unstructured":"Committee, P.P.S., et\u00a0al.: PostGIS, spatial and geographic objects for PostGreSQL (2024). https:\/\/postgis.net"},{"key":"29_CR7","unstructured":"Dask Development Team: Dask: Library for dynamic task scheduling (2016). http:\/\/dask.pydata.org"},{"key":"29_CR8","unstructured":"Elastic: Elasticsearch - Distributed, RESTful Search and Analytics Engine (2024). https:\/\/www.elastic.co\/elasticsearch"},{"key":"29_CR9","doi-asserted-by":"publisher","unstructured":"Eldawy, A.: SpatialHadoop: towards flexible and scalable spatial processing using MapReduce. In: Proceedings of the 2014 SIGMOD PhD Symposium, pp. 46\u201350. SIGMOD 2014 PhD Symposium, Association for Computing Machinery (2014). https:\/\/doi.org\/10.1145\/2602622.2602625","DOI":"10.1145\/2602622.2602625"},{"key":"29_CR10","unstructured":"Emanuele, R.: Using SpatioTemporal Asset Catalogs (STAC) to Modularize End-to-End Machine Learning Workflows for Remote Sensing Data. AGU Fall Meeting Abstracts 2020, IN007\u201301 (2020). https:\/\/ui.adsabs.harvard.edu\/abs\/2020AGUFMIN007.01E"},{"key":"29_CR11","unstructured":"Eynard-Bontemps, G., Abernathey, R., Hamman, J., Ponte, A., Rath, W.: The Pangeo big data ecosystem and its use at CNES. In: Big Data from Space (BiDS 2019) Turning Data into insights (2019)"},{"issue":"1","key":"29_CR12","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1080\/20964471.2017.1398903","volume":"1","author":"G Giuliani","year":"2017","unstructured":"Giuliani, G., Chatenoux, B., De Bono, A., Rodila, D., Richard, J.P., et al.: Building an earth observations data cube: lessons learned from the swiss data cube (SDC) on generating analysis ready data (ARD). Big Earth Data 1(1), 100\u2013117 (2017). https:\/\/doi.org\/10.1080\/20964471.2017.1398903","journal-title":"Big Earth Data"},{"key":"29_CR13","unstructured":"Group, P.G.D.: PostgreSQL (2024). http:\/\/www.postgresql.org"},{"key":"29_CR14","doi-asserted-by":"crossref","unstructured":"Killough, B.: Overview of the open data cube initiative. In: IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, pp. 8629\u20138632 (2018). https:\/\/doi.org\/10\/grpd8g, ISSN: 2153-7003","DOI":"10.1109\/IGARSS.2018.8517694"},{"issue":"3","key":"29_CR15","doi-asserted-by":"publisher","first-page":"94","DOI":"10.3390\/data4030094","volume":"4","author":"S Kopp","year":"2019","unstructured":"Kopp, S., Becker, P., Doshi, A., Wright, D.J., Zhang, K., et al.: Achieving the full vision of earth observation data cubes. Data 4(3), 94 (2019). https:\/\/doi.org\/10.3390\/data4030094","journal-title":"Data"},{"key":"29_CR16","doi-asserted-by":"crossref","unstructured":"Lewis, A., Oliver, S., Lymburner, L., Evans, B., Wyborn, L., et\u00a0al.: The australian geoscience data cube \u2014 foundations and lessons learned. Rem. Sens. Environ. 202, 276\u2013292 (2017). https:\/\/doi.org\/10\/gcr3rp","DOI":"10.1016\/j.rse.2017.03.015"},{"key":"29_CR17","doi-asserted-by":"publisher","unstructured":"Microsoft, O.S., McFarland, M., Emanuele, R., Morris, D., Augspurger, T.: Microsoft\/PlanetaryComputer: October 2022. https:\/\/doi.org\/10.5281\/zenodo.7261897","DOI":"10.5281\/zenodo.7261897"},{"key":"29_CR18","doi-asserted-by":"publisher","unstructured":"Milcinski, G., Bojanowski, J., Clarijs, D., de\u00a0la Mar, J.: Copernicus data space ecosystem - platform that enables federated earth observation services and applications. In: IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, pp. 875\u2013877 (2024). https:\/\/doi.org\/10.1109\/IGARSS53475.2024.10642308","DOI":"10.1109\/IGARSS53475.2024.10642308"},{"key":"29_CR19","unstructured":"MinIO, Inc.: MinIO: High performance, ZKubernetes native object storage (2024). https:\/\/min.io"},{"key":"29_CR20","unstructured":"MongoDB, I.: MongoDB (2024). https:\/\/www.mongodb.com"},{"key":"29_CR21","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1016\/j.rse.2015.11.003","volume":"174","author":"N Mueller","year":"2016","unstructured":"Mueller, N., Lewis, A., Roberts, D., et al.: Water observations from space: mapping surface water from 25 years of Landsat imagery across Australia. Remote Sens. Environ. 174, 341\u2013352 (2016). https:\/\/doi.org\/10.1016\/j.rse.2015.11.003","journal-title":"Remote Sens. Environ."},{"key":"29_CR22","doi-asserted-by":"publisher","unstructured":"Musial, J., Leszczenski, J., Bojanowski, J., Milcinski, G., Vrecko, A., et\u00a0al.: Overview of the Copernicus data space ecosystem APIs. In: EGU General Assembly 2024 (2024). https:\/\/doi.org\/10.5194\/egusphere-egu24-10109","DOI":"10.5194\/egusphere-egu24-10109"},{"key":"29_CR23","doi-asserted-by":"publisher","unstructured":"Neagul, M., Nedelcu, I., Munteanu, A.: Building a national Spatio-temporal datacube. In: IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium, pp. 5089\u20135092. IEEE (2023). https:\/\/doi.org\/10.1109\/IGARSS52108.2023.10281405","DOI":"10.1109\/IGARSS52108.2023.10281405"},{"key":"29_CR24","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1007\/978-3-030-44728-1_12","volume-title":"Tools and Techniques for High Performance Computing","author":"TE Odaka","year":"2020","unstructured":"Odaka, T.E., et al.: The Pangeo ecosystem: interactive computing tools for the geosciences: benchmarking on HPC. In: Juckeland, G., Chandrasekaran, S. (eds.) HUST\/SE-HER\/WIHPC -2019. CCIS, vol. 1190, pp. 190\u2013204. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-44728-1_12"},{"key":"29_CR25","doi-asserted-by":"publisher","unstructured":"Picoli, M.C.A., Simoes, R., Chaves, M., Santos, L.A., Sanchez, A., et\u00a0al.: CBERS data cube: a powerful technology for mapping and monitoring Brazilian biomes. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. V-3-2020, 533\u2013539 (2020). https:\/\/doi.org\/10.5194\/isprs-annals-V-3-2020-533-2020","DOI":"10.5194\/isprs-annals-V-3-2020-533-2020"},{"issue":"22","key":"29_CR26","doi-asserted-by":"publisher","first-page":"3803","DOI":"10.3390\/rs12223803","volume":"12","author":"R Schneider","year":"2020","unstructured":"Schneider, R., Vicedo-Cabrera, A.M., Sera, F., Masselot, P., Stafoggia, M., et al.: A satellite-based spatio-temporal machine learning model to reconstruct daily pm2. 5 concentrations across great Britain. Remote Sens. 12(22), 3803 (2020)","journal-title":"Remote Sens."},{"issue":"13","key":"29_CR27","doi-asserted-by":"publisher","first-page":"2428","DOI":"10.3390\/rs13132428","volume":"13","author":"R Simoes","year":"2021","unstructured":"Simoes, R., et al.: Satellite image time series analysis for big earth observation data. Remote Sens. 13(13), 2428 (2021). https:\/\/doi.org\/10.3390\/rs13132428","journal-title":"Remote Sens."},{"key":"29_CR28","unstructured":"STAC Contributors: SpatioTemporal Asset Catalog (STAC) specification (2021). https:\/\/stacspec.org"},{"key":"29_CR29","doi-asserted-by":"publisher","unstructured":"Storch, T., Reck, C., Holzwarth, S., Keuck, V.: Code-de-the German operational environment for accessing and processing Copernicus sentinel products. In: IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium, pp. 6520\u20136523. IEEE (2018). https:\/\/doi.org\/10.1109\/IGARSS.2018.8519422","DOI":"10.1109\/IGARSS.2018.8519422"},{"issue":"4","key":"29_CR30","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1080\/20964471.2019.1692297","volume":"3","author":"T Storch","year":"2019","unstructured":"Storch, T., Reck, C., Holzwarth, S., Wiegers, B., et al.: Insights into code-de-Germany\u2019s Copernicus data and exploitation platform. Big Earth Data 3(4), 338\u2013361 (2019). https:\/\/doi.org\/10.1080\/20964471.2019.1692297","journal-title":"Big Earth Data"},{"issue":"9","key":"29_CR31","doi-asserted-by":"publisher","first-page":"9799","DOI":"10.1007\/s10489-022-03979-2","volume":"53","author":"S Villarroya","year":"2023","unstructured":"Villarroya, S., Baumann, P.: A survey on ml in array databases. Appl. Intell. 53(9), 9799\u20139822 (2023). https:\/\/doi.org\/10.1007\/s10489-022-03979-2","journal-title":"Appl. Intell."},{"key":"29_CR32","doi-asserted-by":"crossref","unstructured":"Yu, J., Wu, J., Sarwat, M.: GeoSpark: a cluster computing framework for processing large-scale spatial data. In: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp.\u00a01\u20134 (2015)","DOI":"10.1145\/2820783.2820860"},{"issue":"11","key":"29_CR33","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1145\/2934664","volume":"59","author":"M Zaharia","year":"2016","unstructured":"Zaharia, M., Xin, R.S., Wendell, P., et al.: Apache spark: a unified engine for big data processing. Commun. ACM 59(11), 56\u201365 (2016)","journal-title":"Commun. ACM"}],"container-title":["Lecture Notes on Data Engineering and Communications Technologies","Advanced Information Networking and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-87778-0_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,15]],"date-time":"2025-04-15T16:22:36Z","timestamp":1744734156000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-87778-0_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031877773","9783031877780"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-87778-0_29","relation":{},"ISSN":["2367-4512","2367-4520"],"issn-type":[{"value":"2367-4512","type":"print"},{"value":"2367-4520","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"16 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AINA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Information Networking and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Barcelona","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 April 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 April 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"39","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aina0","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/voyager.ce.fit.ac.jp\/conf\/aina\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}