Editing Geographic information system (section)

===Web mapping===
{{Main|Web mapping}}

In recent years there has been a proliferation of free-to-use and easily accessible mapping software such as the [[proprietary software|proprietary]] web applications [[Google&nbsp;Maps]] and [[Bing&nbsp;Maps]], as well as the [[free and open-source software|free and open-source]] alternative [[OpenStreetMap]]. These services give the public access to huge amounts of geographic data, perceived by many users to be as trustworthy and usable as professional information.<ref name = activities>{{cite journal|last1=Parker|first1=Christopher J.|last2=May|first2=Andrew J.|last3=Mitchell|first3=Val |title=The role of VGI and PGI in supporting outdoor activities|journal=Applied Ergonomics|date=2013|volume=44|issue=6|pages=886–94|doi= 10.1016/j.apergo.2012.04.013 |pmid=22795180|s2cid=12918341 |url=https://dspace.lboro.ac.uk/2134/10350}}</ref> For example, during the COVID-19 pandemic, web maps hosted on dashboards were used to rapidly disseminate case data to the general public.<ref name=Everts1>{{cite journal |last1=Everts |first1=Jonathan |title=The dashboard pandemic |journal=Dialogues in Human Geography |year=2020 |volume=10 |issue=2 |pages=260–264 |doi=10.1177/2043820620935355 |s2cid=220418162 |doi-access=free }}</ref>

Some of them, like Google Maps and [[OpenLayers]], expose an [[application programming interface]] (API) that enable users to create custom applications. These toolkits commonly offer street maps, aerial/satellite imagery, geocoding, searches, and routing functionality. Web mapping has also uncovered the potential of [[crowdsourcing]] geodata in projects like [[OpenStreetMap]], which is a collaborative project to create a free editable map of the world. These [[Mashup (web application hybrid)|mashup]] projects have been proven to provide a high level of value and benefit to end users outside that possible through traditional geographic information.<ref>{{cite journal|last1=Parker|first1=Christopher J.|last2=May|first2=Andrew J.|last3=Mitchel|first3=Val|title=User Centred Design of Neogeography: The Impact of Volunteered Geographic Information on Trust of Online Map 'Mashups|journal=Ergonomics|date=2014|volume=57|issue=7|pages=987–997|doi=10.1080/00140139.2014.909950|pmid=24827070|s2cid=13458260|url=https://dspace.lboro.ac.uk/dspace-jspui/bitstream/2134/23845/3/Parker%2c%20May%2c%20Mitchell%20-%202014%20-%20User-centred%20design%20of%20neogeography%20the%20impact%20of%20volunteered%20geographic%20information%20on%20users%27%20perception.pdf |archive-url=https://web.archive.org/web/20170830034140/https://dspace.lboro.ac.uk/dspace-jspui/bitstream/2134/23845/3/Parker%2c%20May%2c%20Mitchell%20-%202014%20-%20User-centred%20design%20of%20neogeography%20the%20impact%20of%20volunteered%20geographic%20information%20on%20users%27%20perception.pdf |archive-date=2017-08-30 |url-status=live}}</ref><ref>{{cite journal|last1=May|first1=Andrew|last2=Parker|first2=Christopher J.|last3=Taylor|first3=Neil|last4=Ross|first4=Tracy|title=Evaluating a concept design of a crowd-sourced 'mashup' providing ease-of-access information for people with limited mobility|journal=Transportation Research Part C: Emerging Technologies|date=2014|volume=49|pages=103–113|doi=10.1016/j.trc.2014.10.007|doi-access=free|bibcode=2014TRPC...49..103M }}</ref>

Web mapping is not without its drawbacks. Web mapping allows for the creation and distribution of maps by people without proper cartographic training.<ref name="Plewe1">{{cite journal |last1=Plewe |first1=Brandon |title=Web Cartography in the United States |journal=Cartography and Geographic Information Science |date=2007 |volume=34 |issue=2 |pages=133–136 |doi=10.1559/152304007781002235|bibcode=2007CGISc..34..133P |s2cid=140717290 }}</ref> This has led to maps that ignore cartographic conventions and are potentially misleading, with one study finding that more than half of United States state government COVID-19 dashboards did not follow these conventions.<ref name=Adams1>{{cite journal |last1=Adams |first1=Aaron |last2=Xiang |first2=Chen |last3=Weidong |first3=Li |last4=Zhang |first4=Chuanrong |title=The disguised pandemic: The importance of data normalization in COVID-19 web mapping |journal=Public Health |date=May 2020 |volume=183 |issue=3 |pages=36–37 |doi = 10.1016/j.puhe.2020.04.034|pmid=32416476 |pmc=7203028 }}</ref><ref name="Adams2">{{cite journal |last1=Adams |first1=Aaron M. |last2=Chen |first2=Xiang |last3=Li |first3=Weidong |last4=Chuanrong |first4=Zhang |title=Normalizing the pandemic: exploring the cartographic issues in state government COVID-19 dashboards |journal=Journal of Maps |date=27 July 2023 |volume=19 |issue=5 |pages=1–9 |doi=10.1080/17445647.2023.2235385|bibcode=2023JMaps..19Q...1A |doi-access=free }}</ref>