"},{"ID":338542,"user_firstname":"Zoya","user_lastname":"Domashnev","nickname":"Zoya Domashnev","user_nicename":"zdomashnev","display_name":"Zoya Domashnev","user_email":"zdomashnev@esri.com","user_url":"","user_registered":"2023-05-04 18:13:57","user_description":"Zoya is a Product Engineering Writer for ArcGIS Instant Apps and ArcGIS Web Editor and has been with Esri since 2022. A lifelong Pittsburgher, she proudly embraces her Yinzer roots and has a lasting interest in the intersection of GIS and urban planning. When she\u2019s not writing documentation, you can usually find her tackling a crossword puzzle, hanging with friends, or doting on her cats.","user_avatar":"
"}],"short_description":"Explore multiple indicators from a single dataset in one interactive app using the ArcGIS Instant Apps Indicator template.","flexible_content":[{"acf_fc_layout":"sidebar","content":"To build an Indicator app, you’ll need to do the following:<\/p>\n
You can then stylize your layer without needing to create multiple layers, maps, or do too much data maintenance.<\/p>\n","image_reference":false,"layout":"standard","image_reference_figure":"","snippet":"","spotlight_name":"","section_title":"","position":"Right","spotlight_image":false},{"acf_fc_layout":"content","content":"
One location can tell more than one story. The ArcGIS Instant Apps Indicator template provides a streamlined way to explore multiple indicators from a single, large dataset in one interactive app. A single dataset might contain population, income, employment, health outcomes, environmental measures, or dozens of other indicators for the same geographic areas. Exploring those variables on a map can provide valuable context, but creating and stylizing separate web maps for every indicator can quickly become time-consuming and difficult to maintain.<\/p>\n
The Instant Apps Indicator template reads your data as it\u2019s stored in the layer. You don\u2019t need to reshape, pivot, or copy your layer to use the template or stylize the different values in the feature layer.<\/p>\n"},{"acf_fc_layout":"content","content":"
Indicator is built around answering a single question: How does this measure vary for the same geographic areas?<\/em><\/p>\n Rather than navigating between multiple maps, viewers explore your different measures through a simple set of filters:<\/p>\n If your data spans multiple days, months, or years, viewers can also step through time to see how an indicator changes. And when they want details about a specific place, they can click it to open the pop-up you configured on your layer.<\/p>\n"},{"acf_fc_layout":"content","content":" Don\u2019t know if your data is tall or wide? We will help you decide. Indicator data is usually stored in one of two data schema, and Indicator supports both. You don\u2019t need to reshape your data to fit the app.<\/p>\n Wide data stores one row per place and one column per indicator. Adding an indicator means adding a field or value per place. In the following example table, the county column indicates the geography fields, the column headings are indicator names, and the data entries listed below the indicators are the numeric values of the indicators. In this example, the indicator data is stored by county.<\/p>\n Tall data stores one row per place per indicator. The column data contains the various indicators, a separate column holds corresponding values, and an optional column identifies categories for the indicators. Many statistical agencies and open data portals publish data this way because new indicators can be added as rows without changing the schema. In the following example table, each indicator name is stored in a column as is the indicator value. Therefore, multiple row entries will exist for each geography. In this example, each county has multiple entries (one per indicator).<\/p>\n Sample data for illustration only. The tall table shows its first four rows.<\/em><\/p>\n The two tables above contain the same information. The difference is how it’s organized, and that difference changes how the app configuration reads the data, letting your users work with it accordingly.<\/span><\/p>\n When you select your layer during configuration, Indicator looks at its structure and automatically selects the schema it thinks your data uses. It considers how many numeric fields the layer has and whether field names suggest an indicator and value pair. A preview table shows what each schema looks like so you can compare it with your own data.<\/p>\n Indicator\u2019s detection capabilities do most of the work, but you know your data best. The configuration prompts you to confirm the choice before moving on.<\/p>\n <\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2988481,"id":2988481,"title":"schema panel","filename":"schema-panel.png","filesize":29914,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/instant-apps\/announcements\/arcgis-instant-apps-introducing-indicator\/schema-panel","alt":"Data schema configuration","author":"338542","description":"","caption":"","name":"schema-panel","status":"inherit","uploaded_to":2984022,"date":"2026-11-09 20:29:21","modified":"2026-11-09 21:25:22","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":578,"height":431,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel.png","medium-width":350,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel.png","medium_large-width":578,"medium_large-height":431,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel.png","large-width":578,"large-height":431,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel.png","1536x1536-width":578,"1536x1536-height":431,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel.png","2048x2048-width":578,"2048x2048-height":431,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel.png","card_image-width":578,"card_image-height":431,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/10\/schema-panel.png","wide_image-width":578,"wide_image-height":431}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":" Indicator works best when you want to explore multiple measures across geographic areas without creating a separate map for each one. The type of comparison you want to make can help determine the best styling approach.<\/p>\n Choosing the right approach depends on your data and what you want viewers to understand from it.<\/p>\n"},{"acf_fc_layout":"sidebar","content":" Note: <\/strong>If your measures require unique symbology, class breaks, and differing classification methods per indicator, creating separate web maps in Map Viewer may be a better fit.<\/p>\n","image_reference":false,"layout":"standard","image_reference_figure":"","snippet":"","spotlight_name":"","section_title":"","position":"Center","spotlight_image":false},{"acf_fc_layout":"content","content":" Indicator follows the same configuration patterns as other Instant Apps templates, and Express<\/strong> setup keeps you focused on the settings you need for a working app. Setting it up takes minutes.<\/p>\n Let\u2019s walk through a fictional example. Say your organization tracks development indicators for South Asia at the subnational level. The dataset covers hundreds of indicators across categories such as Vision, Green and Blue Planet and Resilient Populations, and Effective Macroeconomic and Fiscal Management. Your dataset is stored as a tall table with one row per region, indicator, and year.<\/p>\n Without Indicator, sharing this data could mean dozens of maps, each with its own rendering and legend, and a gallery page to tie them together. Every update means touching each map.<\/p>\n With Indicator, all of that data can be contained in one app. A viewer interested in Bangladesh selects it from the Geography<\/strong> drop-down menu, picks Green and Blue Planet and Resilient Populations<\/strong> as the category, and chooses an indicator. The map zooms to Bangladesh and draws the indicator for each region, with a legend built for that indicator\u2019s range.<\/p>\n"},{"acf_fc_layout":"content","content":" <\/p>\n"},{"acf_fc_layout":"content","content":"\n
\n
\n
Bring your data as it is: tall or wide<\/h1>\n
\n
\n County<\/th>\n Median income ($)<\/th>\n Uninsured (%)<\/th>\n Unemployment (%)<\/th>\n<\/tr>\n \n County A<\/td>\n 61,200<\/td>\n 9.8<\/td>\n 4.1<\/td>\n<\/tr>\n \n County B<\/td>\n 54,700<\/td>\n 12.3<\/td>\n 5.6<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n \n
\n County<\/th>\n Category<\/th>\n Indicator<\/th>\n Value<\/th>\n<\/tr>\n \n County A<\/td>\n Economy<\/td>\n Median income ($)<\/td>\n 61,200<\/td>\n<\/tr>\n \n County A<\/td>\n Health<\/td>\n Uninsured (%)<\/td>\n 9.8<\/td>\n<\/tr>\n \n County A<\/td>\n Economy<\/td>\n Unemployment (%)<\/td>\n 4.1<\/td>\n<\/tr>\n \n County B<\/td>\n Economy<\/td>\n Median income ($)<\/td>\n 54,700<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n Schema detection<\/h2>\n
Is Indicator right for your data?<\/h2>\n
\n
Configure your Indicator app<\/h1>\n
\n
\nFrom Map Viewer, click Create app<\/strong> > Instant Apps<\/strong> and choose Indicator from the home page.<\/li>\n\n
\nPick a color ramp, a classification method, and the number of classes. These settings define how every indicator will be drawn.
\nWhile you select style settings, a histogram shows how your indicator\u2019s values are distributed across places. Drag the slider to highlight the places within a range of values, especially if you choose to go with themes<\/a> for unclassed numeric data on a continuous scale.<\/li>\nUse case: development indicators across South Asia<\/h1>\n