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Currently, a quantitative review of the state and trends in GeoKG is still scarce. Thus, a bibliometric analysis was performed in this study to fill the gap. Specifically, based on 294 research articles published from 2012 to 2023, we conducted analyses in terms of the (1) trends in publications and citations; (2) identification of the major papers, sources, researchers, institutions, and countries; (3) scientific collaboration analysis; and (4) detection of major research topics and tendencies. The results revealed that the interest in GeoKG research has rapidly increased after 2019 and is continually expanding. China is the most productive country in this field. Co-authorship analysis shows that inter-national and inter-institutional collaboration should be reinforced. Keyword analysis indicated that geoscience knowledge representation, information extraction, GeoKG construction, and GeoKG-based multi-source data integration were current hotspots. In addition, several important but currently neglected issues, such as the integration of Large Language Models, are highlighted. The findings of this review provide a systematic overview of the development of GeoKG and provide a valuable reference for future research.<\/jats:p>","DOI":"10.3390\/ijgi13070255","type":"journal-article","created":{"date-parts":[[2024,7,17]],"date-time":"2024-07-17T08:48:29Z","timestamp":1721206109000},"page":"255","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Bibliometric Analysis on the Research of Geoscience Knowledge Graph (GeoKG) from 2012 to 2023"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2170-3250","authenticated-orcid":false,"given":"Zhi-Wei","family":"Hou","sequence":"first","affiliation":[{"name":"Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8777-7300","authenticated-orcid":false,"given":"Xulong","family":"Liu","sequence":"additional","affiliation":[{"name":"Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511485, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengnan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511485, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8021-3943","authenticated-orcid":false,"given":"Wenlong","family":"Jing","sequence":"additional","affiliation":[{"name":"Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511485, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4092-2264","authenticated-orcid":false,"given":"Ji","family":"Yang","sequence":"additional","affiliation":[{"name":"Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou 511485, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1145\/3418294","article-title":"Knowledge graphs","volume":"64","author":"Hogan","year":"2021","journal-title":"Commun. ACM"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2480","DOI":"10.1111\/tgis.12985","article-title":"Geoscience Knowledge Graph (GeoKG): Development, construction and challenges","volume":"26","author":"Zhang","year":"2022","journal-title":"Trans. GIS"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1007\/s11430-020-9750-4","article-title":"Geoscience knowledge graph in the big data era","volume":"64","author":"Zhou","year":"2021","journal-title":"Sci. China Earth Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2563","DOI":"10.1007\/s11430-022-1169-9","article-title":"An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships","volume":"66","author":"Zhu","year":"2023","journal-title":"Sci. China Earth Sci."},{"key":"ref_5","first-page":"1091","article-title":"Spatiotemporal knowledge graph: Advances and perspectives","volume":"25","author":"Lu","year":"2023","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"nwab027","DOI":"10.1093\/nsr\/nwab027","article-title":"The Deep-Time Digital Earth program: Data-driven discovery in geosciences","volume":"8","author":"Wang","year":"2021","journal-title":"Natl. Sci. Rev."},{"key":"ref_7","first-page":"38","article-title":"Basic Issues and Research Agenda of Geospatial Knowledge Service","volume":"44","author":"Chen","year":"2019","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"105082","DOI":"10.1016\/j.cageo.2022.105082","article-title":"Knowledge graph construction and application in geosciences: A review","volume":"161","author":"Ma","year":"2022","journal-title":"Comput. Geosci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3118","DOI":"10.1111\/tgis.13012","article-title":"Symbolic and subsymbolic GeoAI: Geospatial knowledge graphs and spatially explicit machine learning","volume":"26","author":"Mai","year":"2022","journal-title":"Trans. GIS"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"625","DOI":"10.1080\/13658816.2019.1684500","article-title":"GeoAI: Spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond","volume":"34","author":"Janowicz","year":"2020","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_11","first-page":"1865","article-title":"A Review of Recent Researches and Reflections on Geospatial Artificial Intelligence","volume":"45","author":"Gao","year":"2020","journal-title":"Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1145\/3295499","article-title":"Spatiotemporal Representation Learning for Translation-Based POI Recommendation","volume":"37","author":"Qian","year":"2019","journal-title":"ACM Trans. Inf. Syst. (TOIS)"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/17538947.2020.1738568","article-title":"Geo-analytical question-answering with GIS","volume":"14","author":"Scheider","year":"2020","journal-title":"Int. J. Digit. Earth"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"46782","DOI":"10.1109\/ACCESS.2020.3033997","article-title":"Interactive Analysis of Epidemic Situations Based on a Spatiotemporal Information Knowledge Graph of COVID-19","volume":"10","author":"Jiang","year":"2022","journal-title":"IEEE Access"},{"key":"ref_15","first-page":"723","article-title":"On Geographic Knowledge Graph","volume":"19","author":"Lu","year":"2017","journal-title":"J. Geo-Inf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e12404","DOI":"10.1111\/gec3.12404","article-title":"Geo-text data and data-driven geospatial semantics","volume":"12","author":"Hu","year":"2018","journal-title":"Geogr. Compass"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ma, X., Mookerjee, M., Hsu, L., and Hills, D. (2023). Text mining and knowledge graph construction from geoscience literature legacy: A review. Recent Advancement in Geoinformatics and Data Science, Geological Society of America.","DOI":"10.1130\/SPE558"},{"key":"ref_18","first-page":"382","article-title":"Comparative Analysis and Enlightenment of Geoscience Knowledge Graphs: A Perspective of Construction Methods and Contents","volume":"29","author":"Zhu","year":"2023","journal-title":"Geol. J. China Univ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.jbusres.2021.04.070","article-title":"How to conduct a bibliometric analysis: An overview and guidelines","volume":"133","author":"Donthu","year":"2021","journal-title":"J. Bus. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1016\/j.jbusres.2022.04.042","article-title":"Guidelines for advancing theory and practice through bibliometric research","volume":"148","author":"Mukherjee","year":"2022","journal-title":"J. Bus. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1016\/j.jbusres.2022.06.039","article-title":"Mapping the conceptual and intellectual structure of the consumer vulnerability field: A bibliometric analysis","volume":"150","author":"Khare","year":"2022","journal-title":"J. Bus. Res."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Li, J., Goerlandt, F., and Li, K.W. (2019). Slip and Fall Incidents at Work: A Visual Analytics Analysis of the Research Domain. Int. J. Environ. Res. Public Health, 16.","DOI":"10.3390\/ijerph16244972"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1007\/s11192-015-1789-x","article-title":"Global research trends of geographical information system from 1961 to 2010: A bibliometric analysis","volume":"106","author":"Liu","year":"2016","journal-title":"Scientometrics"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/j.neucom.2021.02.098","article-title":"Topic analysis and development in knowledge graph research: A bibliometric review on three decades","volume":"461","author":"Chen","year":"2021","journal-title":"Neurocomputing"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"55537","DOI":"10.1109\/ACCESS.2021.3070395","article-title":"Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review","volume":"9","author":"Buchgeher","year":"2021","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cageo.2016.10.006","article-title":"A bibliometric and visual analysis of global geo-ontology research","volume":"99","author":"Li","year":"2017","journal-title":"Comput. Geosci."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5113","DOI":"10.1007\/s11192-021-03948-5","article-title":"The journal coverage of Web of Science, Scopus and Dimensions: A comparative analysis","volume":"126","author":"Singh","year":"2021","journal-title":"Scientometrics"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1080\/20964471.2019.1652003","article-title":"Geospatial semantics, ontology and knowledge graphs for big Earth data","volume":"3","author":"Zhu","year":"2019","journal-title":"Big Earth Data"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wang, S., Zhang, X., Ye, P., Du, M., Lu, Y., and Xue, H. (2019). Geographic knowledge graph (GeoKG): A formalized geographic knowledge representation. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8040184"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1068\/d14148p","article-title":"Wet Ontologies, Fluid Spaces: Giving Depth to Volume through Oceanic Thinking","volume":"33","author":"Steinberg","year":"2015","journal-title":"Environ. Plan. D Soc. Space"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1177\/1474474013500226","article-title":"Ontologies of Indigeneity: The politics of embodying a concept","volume":"21","author":"Hunt","year":"2013","journal-title":"Cult. Geogr."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1016\/j.joi.2017.08.007","article-title":"bibliometrix: An R-tool for comprehensive science mapping analysis","volume":"11","author":"Aria","year":"2017","journal-title":"J. Informetr."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"e13046","DOI":"10.1016\/j.heliyon.2023.e13046","article-title":"A scientometric analysis on entrepreneurial intention literature: Delving deeper into local citation","volume":"9","year":"2023","journal-title":"Heliyon"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"113764","DOI":"10.1016\/j.eswa.2020.113764","article-title":"A survey of research hotspots and frontier trends of recommendation systems from the perspective of knowledge graph","volume":"165","author":"Shao","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1002\/asi.23437","article-title":"Comparing keywords plus of WOS and author keywords: A case study of patient adherence research","volume":"67","author":"Zhang","year":"2016","journal-title":"J. Assoc. Inf. Sci. Technol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zeng, L., Li, Z., Zhao, Z., and Mao, M. (2018, January 8\u201312). Landscapes and Emerging Trends of Virtual Reality in Recent 30 Years: A Bibliometric Analysis. Proceedings of the 2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld\/SCALCOM\/UIC\/ATC\/CBDCom\/IOP\/SCI), Guangzhou, China.","DOI":"10.1109\/SmartWorld.2018.00311"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"125924","DOI":"10.1016\/j.jclepro.2021.125924","article-title":"Past, present, future: Engagement with sustainable urban development through 35 city labels in the scientific literature 1990\u20132019","volume":"292","author":"Schraven","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1080\/13658816.2021.1962527","article-title":"A knowledge representation model based on the geographic spatiotemporal process","volume":"36","author":"Zheng","year":"2022","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"104620","DOI":"10.1016\/j.cageo.2020.104620","article-title":"A new structure for representing and tracking version information in a deep time knowledge graph","volume":"145","author":"Ma","year":"2020","journal-title":"Comput. Geosci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.cageo.2017.12.007","article-title":"Information extraction and knowledge graph construction from geoscience literature","volume":"112","author":"Wang","year":"2018","journal-title":"Comput. Geosci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"52286","DOI":"10.1109\/ACCESS.2018.2870203","article-title":"Prospecting Information Extraction by Text Mining Based on Convolutional Neural Networks\u2013A Case Study of the Lala Copper Deposit, China","volume":"6","author":"Li","year":"2018","journal-title":"IEEE Access"},{"key":"ref_42","first-page":"30","article-title":"Know, Know Where, KnowWhereGraph: A densely connected, cross-domain knowledge graph and geo-enrichment service stack for applications in environmental intelligence","volume":"43","author":"Janowicz","year":"2022","journal-title":"AI Mag."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.future.2020.11.003","article-title":"Linking OpenStreetMap with knowledge graphs\u2014Link discovery for schema-agnostic volunteered geographic information","volume":"116","author":"Tempelmeier","year":"2021","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1637","DOI":"10.1080\/17538947.2020.1773950","article-title":"The construction of personalized virtual landslide disaster environments based on knowledge graphs and deep neural networks","volume":"13","author":"Zhang","year":"2020","journal-title":"Int. J. Digit. Earth"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Li, W., Wang, S., Chen, X., Tian, Y., Gu, Z., Lopez-Carr, A., Schroeder, A., Currier, K., Schildhauer, M., and Zhu, R. (2023). GeoGraphVis: A Knowledge Graph and Geovisualization Empowered Cyberinfrastructure to Support Disaster Response and Humanitarian Aid. ISPRS Int. J. Geo-Inf., 12.","DOI":"10.3390\/ijgi12030112"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Liu, Y., Ding, J., and Li, Y. (2022, January 1). Developing knowledge graph based system for urban computing. Proceedings of the 1st ACM SIGSPATIAL International Workshop on Geospatial Knowledge Graphs, Seattle, WA, USA.","DOI":"10.1145\/3557990.3567586"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"923","DOI":"10.1080\/17538947.2016.1266041","article-title":"Multidimensional and quantitative interlinking approach for Linked Geospatial Data","volume":"10","author":"Zhu","year":"2017","journal-title":"Int. J. Digit. Earth"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"265","DOI":"10.3233\/SW-200392","article-title":"WarSampo knowledge graph: Finland in the Second World War as Linked Open Data","volume":"12","author":"Koho","year":"2021","journal-title":"Semant. Web"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Wang, Y., Zhang, H., and Xie, H. (2019). Geography-Enhanced Link Prediction Framework for Knowledge Graph Completion. Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding, Proceedings of the 4th China Conference, CCKS 2019, Hangzhou, China, 24\u201327 August 2019, Springer.","DOI":"10.1007\/978-981-15-1956-7_18"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"109951","DOI":"10.1016\/j.knosys.2022.109951","article-title":"Building and exploiting spatial\u2013temporal knowledge graph for next POI recommendation","volume":"258","author":"Chen","year":"2022","journal-title":"Knowl.-Based Syst."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"103369","DOI":"10.1016\/j.ipm.2023.103369","article-title":"Towards travel recommendation interpretability: Disentangling tourist decision-making process via knowledge graph","volume":"60","author":"Gao","year":"2023","journal-title":"Inf. Process. Manag."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"105215","DOI":"10.1016\/j.cageo.2022.105215","article-title":"LinkClimate: An interoperable knowledge graph platform for climate data","volume":"169","author":"Wu","year":"2022","journal-title":"Comput. Geosci."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Qin, C.-Z., and Zhu, A.-X. (2022). Towards Domain-Knowledge-Based Intelligent Geographical Modeling. New Thinking in GIScience, Springer.","DOI":"10.1007\/978-981-19-3816-0_19"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Hou, Z.-W., Qin, C.-Z., Zhu, A.-X., Liang, P., Wang, Y.-J., and Zhu, Y.-Q. (2019). From Manual to Intelligent: A Review of Input Data Preparation Methods for Geographic Modeling. ISPRS Int. J. Geo-Inf., 8.","DOI":"10.3390\/ijgi8090376"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1017\/S0269888900007098","article-title":"Case-based reasoning: A review","volume":"9","author":"Watson","year":"1994","journal-title":"Knowl. Eng. Rev."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3379","DOI":"10.5194\/hess-20-3379-2016","article-title":"Case-based knowledge formalization and reasoning method for digital terrain analysis\u2014Application to extracting drainage networks","volume":"20","author":"Qin","year":"2016","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1007\/s12145-020-00466-5","article-title":"Using the most similar case method to automatically select environmental covariates for predictive mapping","volume":"13","author":"Liang","year":"2020","journal-title":"Earth Sci. Inform."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Wilson, J.P. (2018). Environmental Applications of Digital Terrain Modeling, Wiley-Blackwell.","DOI":"10.1002\/9781118938188"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"103223","DOI":"10.1016\/j.earscirev.2020.103223","article-title":"Position paper: Open web-distributed integrated geographic modelling and simulation to enable broader participation and applications","volume":"207","author":"Chen","year":"2020","journal-title":"Earth-Sci. Rev."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1080\/19475683.2019.1670735","article-title":"Automatic data matching for geospatial models: A new paradigm for geospatial data and models sharing","volume":"25","author":"Zhu","year":"2019","journal-title":"Ann. GIS"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1016\/j.envsoft.2008.09.009","article-title":"Modelling with knowledge: A review of emerging semantic approaches to environmental modelling","volume":"24","author":"Villa","year":"2009","journal-title":"Environ. Model. Softw."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1080\/13658816.2017.1300805","article-title":"A similarity-based automatic data recommendation approach for geographic models","volume":"31","author":"Zhu","year":"2017","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"1163","DOI":"10.2166\/hydro.2019.029","article-title":"A knowledge-based method for the automatic determination of hydrological model structures","volume":"21","author":"Jiang","year":"2019","journal-title":"J. Hydroinform."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1111\/tgis.13134","article-title":"Construction of an open knowledge framework for geoscientific models","volume":"28","author":"Xu","year":"2024","journal-title":"Trans. GIS"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Zhu, X., Li, Z., Wang, X., Jiang, X., Sun, P., Wang, X., Xiao, Y., and Yuan, N.J. (2022). Multi-Modal Knowledge Graph Construction and Application: A Survey. arXiv.","DOI":"10.1109\/TKDE.2022.3224228"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"560","DOI":"10.1007\/s11442-014-1106-2","article-title":"A new geographical language: A perspective of GIS","volume":"24","author":"Hu","year":"2014","journal-title":"J. Geogr. Sci."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1109\/TPAMI.2018.2798607","article-title":"Multimodal Machine Learning: A Survey and Taxonomy","volume":"41","author":"Baltrusaitis","year":"2019","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Deng, C., Jia, Y., Xu, H., Zhang, C., Tang, J., Fu, L., Zhang, W., Zhang, H., Wang, X., and Zhou, C. (2021, January 1\u20135). GAKG: A Multimodal Geoscience Academic Knowledge Graph. Proceedings of the 30th ACM International Conference on Information & Knowledge Management, Virtual.","DOI":"10.1145\/3459637.3482003"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"3580","DOI":"10.1109\/TKDE.2024.3352100","article-title":"Unifying large language models and knowledge graphs: A roadmap","volume":"36","author":"Pan","year":"2024","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_70","first-page":"2:1","article-title":"Large Language Models and Knowledge Graphs: Opportunities and Challenges","volume":"1","author":"Pan","year":"2023","journal-title":"TGDK"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"2353122","DOI":"10.1080\/17538947.2024.2353122","article-title":"GPT, large language models (LLMs) and generative artificial intelligence (GAI) models in geospatial science: A systematic review","volume":"17","author":"Wang","year":"2024","journal-title":"Int. J. Digit. Earth"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Deng, C., Zhang, T., He, Z., Chen, Q., Shi, Y., Xu, Y., Fu, L., Zhang, W., Wang, X., and Zhou, C. (2024, January 4\u20138). K2: A foundation language model for geoscience knowledge understanding and utilization. Proceedings of the 17th ACM International Conference on Web Search and Data Mining, Merida, Mexico.","DOI":"10.1145\/3616855.3635772"}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/13\/7\/255\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:17:47Z","timestamp":1760109467000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/13\/7\/255"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,16]]},"references-count":72,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["ijgi13070255"],"URL":"https:\/\/doi.org\/10.3390\/ijgi13070255","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,16]]}}}