{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T15:24:58Z","timestamp":1773933898521,"version":"3.50.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T00:00:00Z","timestamp":1763596800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T00:00:00Z","timestamp":1763596800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.61902002"],"award-info":[{"award-number":["No.61902002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.61902002"],"award-info":[{"award-number":["No.61902002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["Nos. 2023YFC3807500 and 2023YFC3807501"],"award-info":[{"award-number":["Nos. 2023YFC3807500 and 2023YFC3807501"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["Nos. 2023YFC3807500 and 2023YFC3807501"],"award-info":[{"award-number":["Nos. 2023YFC3807500 and 2023YFC3807501"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1007\/s10586-025-05832-w","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T18:23:21Z","timestamp":1763663001000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Lakehouse storage architecture design methodology for station-city integrated cyberspace"],"prefix":"10.1007","volume":"29","author":[{"given":"Luyang","family":"Wei","sequence":"first","affiliation":[]},{"given":"Huan","family":"Fang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"key":"5832_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/s11116-025-10635-4","author":"J Deng","year":"2025","unstructured":"Deng, J., Cheng, L., Wu, C., Jin, T., Witlox, F.: National-Scale analysis of transit-oriented development levels at high-speed rail stations in China. Transportation (2025). https:\/\/doi.org\/10.1007\/s11116-025-10635-4","journal-title":"Transportation"},{"key":"5832_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10668-024-05902-w","volume":"1","author":"Z Luo","year":"2025","unstructured":"Luo, Z., Chen, Z., Wu, X., Pan, H., Wang, F., Tu, R., Yao, Z., Wang, Y., Chen, S.: Sustainability assessment of station-city integration based on DPSIR-SDGs framework: a case study of Chengdu in China. Environ. Dev. Sustain. 1, 1 (2025). https:\/\/doi.org\/10.1007\/s10668-024-05902-w","journal-title":"Environ. Dev. Sustain."},{"issue":"4","key":"5832_CR3","doi-asserted-by":"publisher","first-page":"132","DOI":"10.3390\/bdcc6040132","volume":"6","author":"A Nambiar","year":"2022","unstructured":"Nambiar, A., Mundra, D.: An overview of data warehouse and data lake in modern enterprise data management. Big Data Cognitive Comput. 6(4), 132 (2022). https:\/\/doi.org\/10.3390\/bdcc6040132","journal-title":"Big Data Cognitive Comput."},{"issue":"1","key":"5832_CR4","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1007\/s10844-020-00608-7","volume":"56","author":"P Sawadogo","year":"2021","unstructured":"Sawadogo, P., Darmont, J.: On data lake architectures and metadata management. J. Intell. Inform. Syst. 56(1), 97\u2013120 (2021). https:\/\/doi.org\/10.1007\/s10844-020-00608-7","journal-title":"J. Intell. Inform. Syst."},{"issue":"2","key":"5832_CR5","doi-asserted-by":"publisher","first-page":"132","DOI":"10.29099\/ijair.v5i2.215","volume":"5","author":"WS Fana","year":"2021","unstructured":"Fana, W.S., Sovia, R., Permana, R., Islam, M.A.: Data Warehouse Design With ETL Method (Extract, Transform, And Load) for Company Information Centre. Int. J. Artif. Intell. Res. 5(2), 132\u2013137 (2021). https:\/\/doi.org\/10.29099\/ijair.v5i2.215","journal-title":"Int. J. Artif. Intell. Res."},{"key":"5832_CR6","doi-asserted-by":"publisher","first-page":"13472","DOI":"10.1109\/ACCESS.2022.3148131","volume":"10","author":"CAU Hassan","year":"2022","unstructured":"Hassan, C.A.U., Hammad, M., Uddin, M., Iqbal, J., Sahi, J., Hussain, S., Ullah, S.S.: Optimizing the Performance of Data Warehouse by Query Cache Mechanism. IEEE Access 10, 13472\u201313480 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3148131","journal-title":"IEEE Access"},{"key":"5832_CR7","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1016\/j.procs.2022.11.085","volume":"213","author":"AA Sukhobokov","year":"2022","unstructured":"Sukhobokov, A.A., Gapanyuk, Y.E., Zenger, A.S., Tsvetkova, A.K.: The concept of an intelligent data lake management system: machine consciousness and a universal data model. Procedia Comput. Sci. 213, 407\u2013414 (2022). https:\/\/doi.org\/10.1016\/j.procs.2022.11.085","journal-title":"Procedia Comput. Sci."},{"issue":"8","key":"5832_CR8","doi-asserted-by":"publisher","first-page":"5235","DOI":"10.1109\/TSMC.2021.3119871","volume":"52","author":"H Yu","year":"2022","unstructured":"Yu, H., Cai, H., Liu, Z., Xu, B., Jiang, L.: An automated metadata generation method for data lake of industrial wot applications. IEEE Trans. Syst. Man. Cybernet. Syst. 52(8), 5235\u20135248 (2022). https:\/\/doi.org\/10.1109\/TSMC.2021.3119871","journal-title":"IEEE Trans. Syst. Man. Cybernet. Syst."},{"key":"5832_CR9","doi-asserted-by":"publisher","unstructured":"Megdiche, I., Ravat, F., Zhao, Y.: Metadata Management on Data Processing in Data Lakes. In: Bure\u0161, T., Dondi, R., Gamper, J., Guerrini, G., Jurdzi\u0144ski, T., Pahl, C., Sikora, F., Wong, P.W.H. (eds.) SOFSEM 2021: Theory and Practice of Computer Science, pp. 553\u2013562. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-67731-2_40","DOI":"10.1007\/978-3-030-67731-2_40"},{"key":"5832_CR10","unstructured":"Armbrust, M., Ghodsi, A., Xin, R., Zaharia, M.: Lakehouse: a New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics. (2021)"},{"key":"5832_CR11","doi-asserted-by":"publisher","unstructured":"Shiyal, B.: Modern Data Warehouses and Data Lakehouses. In: Shiyal, B. (ed.) Beginning Azure Synapse Analytics: Transition from Data Warehouse to Data Lakehouse, pp. 21\u201348. Apress, Berkeley (2021). https:\/\/doi.org\/10.1007\/978-1-4842-7061-5_2","DOI":"10.1007\/978-1-4842-7061-5_2"},{"key":"5832_CR12","doi-asserted-by":"publisher","unstructured":"Liu, Y., Ma, P., Tian, J.: Research on Technology and Industry Situation of Lakehouse. In: 2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp. 2198\u20132203 (2023). https:\/\/doi.org\/10.1109\/TrustCom60117.2023.00308","DOI":"10.1109\/TrustCom60117.2023.00308"},{"issue":"1","key":"5832_CR13","doi-asserted-by":"publisher","first-page":"34","DOI":"10.3390\/genes16010034","volume":"16","author":"T Koreeda","year":"2024","unstructured":"Koreeda, T., Honda, H., Onami, J..-i: Snowflake Data Warehouse for Large-Scale and Diverse Biological Data Management and Analysis. Genes 16(1), 34 (2024). https:\/\/doi.org\/10.3390\/genes16010034","journal-title":"Genes"},{"key":"5832_CR14","doi-asserted-by":"publisher","unstructured":"Begoli, E., Goethert, I., Knight, K.: A Lakehouse Architecture for the Management and Analysis of Heterogeneous Data for Biomedical Research and Mega-biobanks. In: 2021 IEEE International Conference on Big Data (Big Data), pp. 4643\u20134651 (2021). https:\/\/doi.org\/10.1109\/BigData52589.2021.9671534","DOI":"10.1109\/BigData52589.2021.9671534"},{"key":"5832_CR15","doi-asserted-by":"publisher","unstructured":"Ore\u0161\u010danin, D., Hlupi\u0107, T.: Data Lakehouse\u2014a Novel Step in Analytics Architecture. In: 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO), pp. 1242\u20131246 (2021). https:\/\/doi.org\/10.23919\/MIPRO52101.2021.9597091","DOI":"10.23919\/MIPRO52101.2021.9597091"},{"issue":"8","key":"5832_CR16","doi-asserted-by":"publisher","first-page":"1943","DOI":"10.3390\/electronics12081943","volume":"12","author":"S Park","year":"2023","unstructured":"Park, S., Yang, C.-S., Kim, J.: Design of vessel data lakehouse with big data and aI analysis technology for vessel monitoring system. Electronics 12(8), 1943 (2023). https:\/\/doi.org\/10.3390\/electronics12081943","journal-title":"Electronics"},{"key":"5832_CR17","doi-asserted-by":"publisher","unstructured":"Harby, A.A., Zulkernine, F.: From Data Warehouse to Lakehouse: a Comparative Review. In: 2022 IEEE International Conference on Big Data (Big Data), pp. 389\u2013395 (2022). https:\/\/doi.org\/10.1109\/BigData55660.2022.10020719","DOI":"10.1109\/BigData55660.2022.10020719"},{"key":"5832_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2024.102460","volume":"127","author":"AA Harby","year":"2025","unstructured":"Harby, A.A., Zulkernine, F.: Data lakehouse: a survey and experimental study. Inform. Syst. 127, 102460 (2025). https:\/\/doi.org\/10.1016\/j.is.2024.102460","journal-title":"Inform. Syst."},{"key":"5832_CR19","doi-asserted-by":"publisher","first-page":"143037","DOI":"10.1109\/ACCESS.2023.3343953","volume":"11","author":"Y Zhang","year":"2023","unstructured":"Zhang, Y., Peng, B., Du, Y., Su, J.: GeoLake: bringing geospatial support to lakehouses. IEEE Access 11, 143037\u2013143049 (2023). https:\/\/doi.org\/10.1109\/ACCESS.2023.3343953","journal-title":"IEEE Access"},{"key":"5832_CR20","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1016\/j.jpdc.2023.02.007","volume":"176","author":"S Ait Errami","year":"2023","unstructured":"Ait Errami, S., Hajji, H., Ait El Kadi, K., Badir, H.: Spatial big data architecture: from Data Warehouses and Data Lakes to the LakeHouse. J. Parallel Distributed Comput. 176, 70\u201379 (2023). https:\/\/doi.org\/10.1016\/j.jpdc.2023.02.007","journal-title":"J. Parallel Distributed Comput."},{"issue":"9","key":"5832_CR21","doi-asserted-by":"publisher","first-page":"485","DOI":"10.3390\/ijgi11090485","volume":"11","author":"D Wang","year":"2022","unstructured":"Wang, D., Dewancker, B., Duan, Y., Zhao, M.: Exploring spatial features of population activities and functional facilities in rail transit station realm based on real-time positioning data: a case of Xi\u2019an metro line 2. ISPRS Int. J. Geo Inf. 11(9), 485 (2022). https:\/\/doi.org\/10.3390\/ijgi11090485","journal-title":"ISPRS Int. J. Geo Inf."},{"issue":"11","key":"5832_CR22","doi-asserted-by":"publisher","first-page":"04023108","DOI":"10.1061\/JTEPBS.TEENG-7855","volume":"149","author":"Y Yue","year":"2023","unstructured":"Yue, Y., Chen, J., Feng, T., Wang, W., Wang, C., Ma, X.: New classification scheme and evolution characteristics analysis of high-speed railway stations using large-scale mobile phone data: a case study in jiangsu, china. J. Trans. Eng. Part A: Syst. 149(11), 04023108 (2023). https:\/\/doi.org\/10.1061\/JTEPBS.TEENG-7855","journal-title":"J. Trans. Eng. Part A: Syst."},{"key":"5832_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.eiar.2024.107685","volume":"110","author":"C Enshan","year":"2025","unstructured":"Enshan, C., van de Spek, S., van der Hoeven, F., Triggianese, M.: Evaluate user satisfaction for urban design of railway station areas: an assessment framework using agent-based simulation. Environ. Impact Assess. Rev. 110, 107685 (2025). https:\/\/doi.org\/10.1016\/j.eiar.2024.107685","journal-title":"Environ. Impact Assess. Rev."},{"issue":"8","key":"5832_CR24","doi-asserted-by":"publisher","first-page":"1233","DOI":"10.3390\/land13081233","volume":"13","author":"H Chen","year":"2024","unstructured":"Chen, H., Zhao, K., Zhang, Z., Zhang, H., Lu, L.: Methods for the performance evaluation and design optimization of metro transit-oriented development sites based on urban big data. Land 13(8), 1233 (2024). https:\/\/doi.org\/10.3390\/land13081233","journal-title":"Land"},{"issue":"4","key":"5832_CR25","doi-asserted-by":"publisher","first-page":"1086","DOI":"10.1109\/TBDATA.2022.3233031","volume":"9","author":"H Li","year":"2023","unstructured":"Li, H., Xia, J., Luo, W., Fang, H.: Cost-efficient scheduling of streaming applications in apache flink on cloud. IEEE Trans. Big Data. 9(4), 1086\u20131101 (2023). https:\/\/doi.org\/10.1109\/TBDATA.2022.3233031","journal-title":"IEEE Trans. Big Data."},{"key":"5832_CR26","doi-asserted-by":"publisher","unstructured":"Sharma, G., Tripathi, V., Srivastava, A.: Recent Trends in Big Data Ingestion Tools: A Study. In: Kumar, R., Quang, N.H., Kumar\u00a0Solanki, V., Cardona, M., Pattnaik, P.K. (eds.) Research in Intelligent and Computing in Engineering, pp. 873\u2013881. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-15-7527-3_83","DOI":"10.1007\/978-981-15-7527-3_83"},{"issue":"2","key":"5832_CR27","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1108\/DLP-10-2022-0079","volume":"40","author":"RK Singh","year":"2024","unstructured":"Singh, R.K.: Developing a big data analytics platform using apache hadoop ecosystem for delivering big data services in libraries. Digit. Libr. Perspect. 40(2), 160\u2013186 (2024). https:\/\/doi.org\/10.1108\/DLP-10-2022-0079","journal-title":"Digit. Libr. Perspect."},{"issue":"10","key":"5832_CR28","doi-asserted-by":"publisher","first-page":"382","DOI":"10.3390\/fi16100382","volume":"16","author":"SV Salunke","year":"2024","unstructured":"Salunke, S.V., Ouda, A.: A performance benchmark for the postgreSQL and mySQL databases. Future Internet 16(10), 382 (2024). https:\/\/doi.org\/10.3390\/fi16100382","journal-title":"Future Internet"},{"key":"5832_CR29","doi-asserted-by":"publisher","unstructured":"Lu, Y., Liu, Q., Dai, D., Xiao, X., Lin, H., Han, X., Sun, L., Wu, H.: Unified Structure Generation for Universal Information Extraction. (2022). arXiv. https:\/\/doi.org\/10.48550\/arXiv.2203.12277","DOI":"10.48550\/arXiv.2203.12277"},{"key":"5832_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2023.108850","volume":"110","author":"W Zhang","year":"2023","unstructured":"Zhang, W., Ying, H.: Low carbon urban rail transit station city integration based on building information modeling and sensor fusion. Comput Electrical Eng 110, 108850 (2023). https:\/\/doi.org\/10.1016\/j.compeleceng.2023.108850","journal-title":"Comput Electrical Eng"},{"issue":"1","key":"5832_CR31","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1007\/s43762-021-00031-w","volume":"2","author":"Y Pi","year":"2022","unstructured":"Pi, Y., Duffield, N., Behzadan, A.H., Lomax, T.: Visual recognition for urban traffic data retrieval and analysis in major events using convolutional neural networks. Comput Urban Sci 2(1), 2 (2022). https:\/\/doi.org\/10.1007\/s43762-021-00031-w","journal-title":"Comput Urban Sci"},{"key":"5832_CR32","doi-asserted-by":"publisher","unstructured":"Xiong, G., Zhang, W., Liu, X., Yuan, Z., Zhu, F., Zhang, Z.: Framework and Key Technologies for High-speed Railway Comprehensive Transport Hub. In: 2023 IEEE 3rd International Conference on Digital Twins and Parallel Intelligence (DTPI), pp. 1\u20135 (2023). https:\/\/doi.org\/10.1109\/DTPI59677.2023.10365423","DOI":"10.1109\/DTPI59677.2023.10365423"},{"key":"5832_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.jobe.2021.103954","volume":"48","author":"M Mishra","year":"2022","unstructured":"Mishra, M., Louren\u00e7o, P.B., Ramana, G.V.: Structural health monitoring of civil engineering structures by using the internet of things: a review. J Build Eng 48, 103954 (2022). https:\/\/doi.org\/10.1016\/j.jobe.2021.103954","journal-title":"J Build Eng"},{"key":"5832_CR34","doi-asserted-by":"publisher","unstructured":"Wang, M., Ma, F., Cao, X.: Exploration of Underground Space Planning in Station-City Integration Area in the Context of High-Quality Development\u2014a Case Study of Hangzhouxi Railway Station Area. In: Wu, W., Leung, C.F., Zhou, Y., Li, X. (eds.) Proceedings of the 18th Conference of the Associated Research Centers for the Urban Underground Space, pp. 439\u2013444. Springer, Singapore (2024). https:\/\/doi.org\/10.1007\/978-981-97-1257-1_56","DOI":"10.1007\/978-981-97-1257-1_56"},{"key":"5832_CR35","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/978-3-030-58369-9_4","volume-title":"Fire Protection Engineering Applications for Large Transportation Systems in China","author":"F Li","year":"2021","unstructured":"Li, F., Li, H.: Fire Safety Strategies for Typical Space of Large Transportation Hubs. In: Li, F., Li, H. (eds.) Fire Protection Engineering Applications for Large Transportation Systems in China, pp. 99\u2013131. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-58369-9_4"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05832-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-025-05832-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05832-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T13:07:12Z","timestamp":1773925632000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-025-05832-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,20]]},"references-count":35,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["5832"],"URL":"https:\/\/doi.org\/10.1007\/s10586-025-05832-w","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,20]]},"assertion":[{"value":"17 March 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 October 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 October 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 November 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}}],"article-number":"44"}}