{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:30:21Z","timestamp":1760243421305,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2013,2,18]],"date-time":"2013-02-18T00:00:00Z","timestamp":1361145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The National Spatial Data Infrastructure (NSDI) is defined as the technologies, policies and people necessary to promote sharing of geospatial data throughout all levels of government, the private and non-profit sectors and the academic community. The US Census Bureau is the federal agency lead for administrative units data, one of the seven data themes identified by the NSDI framework. The administrative unit is a unit with administrative responsibilities. These units are organized as nodes\/lines\/areas feature data. The OpenGIS Geography Markup Language (GML) is the XML grammar to express the geographic features. This study at the US Census Bureau investigates how the  general-purpose GML standard could be leveraged and extended to describe the most comprehensive geographic dataset with national coverage in the US. Challenges and problems in dealing with data volume, GML document structure, GML schema design and GML document naming are analyzed, followed by proposed solutions proven for feasibility. Our results show that one key point in making a successful GML deployment for NSDI is to reflect the characteristics of the geographic data through a carefully designed GML schema, structure and organization. The lessons learned may be useful to others transforming NSDI framework data and other large geospatial datasets into  GML structures.<\/jats:p>","DOI":"10.3390\/ijgi2010082","type":"journal-article","created":{"date-parts":[[2013,2,19]],"date-time":"2013-02-19T11:11:16Z","timestamp":1361272276000},"page":"82-93","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Pioneering GML Deployment for NSDI \u2014 Case Study of USTIGER\/GML"],"prefix":"10.3390","volume":"2","author":[{"given":"Lingling","family":"Guo","sequence":"first","affiliation":[{"name":"Public Safety Research School, Tsinghua University, 1001, Liuqing Building, Beijing 100084, China"}]}],"member":"1968","published-online":{"date-parts":[[2013,2,18]]},"reference":[{"key":"ref_1","unstructured":"Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure (Executive Order 12906). 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