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Update on the Geospatial Data Act of 2017

Whatever happened to the bipartisan Geospatial Data Act (GDA) of 2017, you may be wondering? This important bill is designed to facilitate and support geospatial data development, sharing, and coordination across federal agencies and partnerships with state and local governments, towards a more robust National Spatial Data Infrastructure (NSDI). Unfortunately, the bill has yet to reach congressional floors for a vote. Back in mid-November 2017, parallel versions of a revised Geospatial Data Act of 2017 made their way to their respective committees in the Senate (S. 2128) and the House (H.R. 4395). You can find the committee assignments at the links to the bills above. Those identical bills had been modified to remove language in two places, Sections 11 and 12, that UCGIS and many other organizations and individuals had previously regarded as problematic to the pursuit of open GIS and mapping activities in academic and public sectors.

Since that time, actions have been largely behind the scenes and the bills remain on their respective congressional dockets. Further discussions and debate around data and mapping language have taken place but have yielded no changes to the text.

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UCGIS Publishes Statement on Data Science

As a long-established information science discipline, the Geographic Information Science & Technology (GIS&T) community has key contributions to make to evolving data science curricula. This statement articulates the University Consortium for Geographic Information Science’s (UCGIS) position for the academic GIS&T community and provides recommendations and action items for the benefit of both internal and external audiences. On May 22-24, 2018, UCGIS held its annual Symposium under the theme of Frontiers of Geospatial Data Science, coordinated this year with the AutoCarto conference of the Cartography and Geographic Information Society (CaGIS). Drawing from discussions at that event, together with many months of internal exchanges, UCGIS offers these statements for the benefit of its member organizations as well as the broader geospatial community. The goals of this white paper and its recommendations are to 1) describe and clarify the value of incorporating geospatial knowledge, skills, and data for students, employees, and employers within the emerging field of data science; 2) highlight potential pathways and opportunities for academic geospatial scientists to establish connections with data science programs and personnel on their university campuses; and 3) initiate a national dialogue about the synergistic benefits of mutually enriching data science and geospatial science curricula.

Please find our white paper, A UCGIS Call to Action: Bringing the Geospatial Perspective to Data Science Degrees and Curricula, available here (pdf)

Set of CaGIS Journal Open-Access articles

Papers in Cartography & Geographic Information Science, available for free (open-access) but only through Thursday, May 31, 2018. Thank you, Taylor and Francis publishers.

  • Marc P. Armstrong (2017) How large is Aroostook County? Exploring the historical mutability of US county area measurements, Cartography and Geographic Information Science, DOI: 10.1080/15230406.2017.1370392
  • Sarah E. Battersby, Daniel “daan” Strebe & Michael P. Finn (2017) Shapes on a plane: evaluating the impact of projection distortion on spatial binning, Cartography and Geographic Information Science, 44:5, 410-421, DOI: 10.1080/15230406.2016.1180263
  • Barry J. Kronenfeld (2018) Manual construction of continuous cartograms through mesh transformation, Cartography and Geographic Information Science, 45:1, 76-94, DOI: 10.1080/15230406.2016.1270775
  • Lawrence V. Stanislawski, Kornelijus Survila, Jeffrey Wendel, Yan Liu & Barbara P. Buttenfield (2018) An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions, Cartography and Geographic Information Science, 45:4, 319-328, DOI: 10.1080/15230406.2017.1337524
  • Waldo Tobler (2018) A new companion for Mercator, Cartography and Geographic Information Science, 45:3, 284-285, DOI: 10.1080/15230406.2017.1308837
  •  Xinyue Ye, Qunying Huang & Wenwen Li (2016) Integrating big social data, computing and modeling for spatial social science, Cartography and Geographic Information Science, 43:5, 377-378, DOI: 10.1080/15230406.2016.1212302