Tutorials / Use the Data Hub CLI
Last Updated: July 24, 2020


Duration is 5 min

The Data Hub CLI (command line interface) allows you to upload, access, and inspect geodata in Data Hub space via the command line interface. In this tutorial, you will learn how to:

  • authenticate the CLI with your HERE credentials
  • upload GeoJSON to a Data Hub space
  • add tags to data being uploaded to a Data Hub space
  • convert and upload other geodata formats (CSV, shapefiles)
  • inspect geodata and tags in a Data Hub space
  • clear features and delete Data Hub spaces
  • open a Data Hub space in a web browser
  • create tokens to access Data Hub spaces

This tutorial requires that you have installed the Data Hub ClI.

HERE credentials

If you haven’t already registered for a HERE Developer Account, you can do so now by signing up here.

Enter your email credentials by typing:

here configure account

(You will be prompted to enter your email address and password. Your email will be echoed, but there will be no feedback when you paste in your password.)

About GeoJSON data

GeoJSON is a format that encodes geographic data and is based on JSON. Below is a sample file that encodes locations of a few HERE offices.

HERE Studio is able to read GeoJSON natively (and can also convert and upload CSVs with latitude/longitude coordinates, and shapefiles/SHP into Data Hub spaces).

  "type": "FeatureCollection",
  "features": [
      "type": "Feature",
      "properties": {
        "name": "HERE Mumbai"
      "geometry": {
        "type": "Point",
        "coordinates": [
      "type": "Feature",
      "properties": {
        "name": "HERE Frankfurt (Schwalbach)"
      "geometry": {
        "type": "Point",
        "coordinates": [
      "type": "Feature",
      "properties": {
        "name": "HERE Chicago"
      "geometry": {
        "type": "Point",
        "coordinates": [

Click this link to save the following to your desktop as xyz.geojson. Download GeoJSON

Upload data to a new Data Hub space

Duration is 5 min

On the command line, use the upload option to automatically create a new Data Hub space and upload your data. You’ll be prompted to add a title and description. (Do this! You will thank yourself later.)

here xyz upload -f xyz.geojson

Hint: cd to the directory where you downloaded the data. On a Mac, you can drag the file to the terminal window after -f.)

Note that you can also upload data to an existing space – just add the spaceID: here xyz upload SPACEID -f xyz.geojson

You can also create the space first if you need to access certain advanced options.

here xyz create -t "my new data hub space" -d "a new space with xyz.geojson"

If successfully executed, your output will be:

xyzspace 'YOUR_SPACE_ID' created successfully

The CLI will return the unique ID of your Data Hub space. Keep track of this ID as you’ll need it to view the GeoJSON on a map.

Hint: You can review all of your Data Hub spaces by typing here xyz list

The CLI will return a summary of the GeoJSON file you uploaded, including a count of features, and their geometry type.

data upload to xyzspace '1f2g3h4j' completed successfully
                      Upload Summary                     
Total 3 features
GeometryType  Count
------------  -----
Point         3    

Note: the upload command will check and warn you about duplicate values in your file, and will not duplicate identical features already in the Data Hub space. You can override this using -o.

Add tags to features while uploading to a Data Hub space

Duration is 5 min

You can add a tag to features while uploading them to a Data Hub space. This makes it easier to filter this data when requesting it from the API, especially when you are uploading data from multiple sources.

When uploading data, use the -t option followed by the tag you want to add. (You can append multiple tags using a comma.)

here xyz upload SPACE_ID -f xyz.geojson -t xyzweek,codelab

This tag will be added to every feature.

In addition to a count of objects, the CLI will show you a list of unique tags.

data upload to xyzspace 'MZZodRsb' completed successfully
                   Upload Summary                     
Total 4 features
GeometryType  Count
------------  -----
Point         3   

Total unique tag Count : 3
Unique tag list  :["xyzweek","codelab","xyz"]
TagName  Count
-------  -----
xyzweek  3    
codelab  3    
xyz      3    

Note that HERE Studio will also add the filename as a tag to make it easier to track multiple uploads, and back out an upload, if necessary.

Assign the value of GeoJSON properties as a tag

Duration is 15 min

Assign the value of a GeoJSON property using -p

You can assign the value of a GeoJSON property as a tag using -p. (This is most useful when there are a reasonable number of discrete values. As an example, a set of road classifications would make good tags, while length of roads would not.)

Download this file of airports from Natural Earth:


This GeoJSON file includes various properties, including the type of the airport. Here’s a single feature in that GeoJSON file showing Schipol, Amsterdam’s airport.

"properties": {
   "abbrev": "AMS",
   "featurecla": "Airport",
   "gps_code": "EHAM",
   "iata_code": "AMS",
   "location": "terminal",
   "name": "Schiphol",
   "natlscale": 150,
   "scalerank": 2,
   "type": "major",
   "wikipedia": "http://en.wikipedia.org/wiki/Amsterdam_Schiphol_Airport"

You can assign the type of each airport as a tag using -p type:

here xyz upload SPACE_ID -f ne_10m_airports.geojson -p type

Note you can also load data directly via URL:

here xyz upload SPACE_ID -f "https://raw.githubusercontent.com/nvkelso/natural-earth-vector/master/geojson/ne_10m_airports.geojson" -p type

After the data has been loaded into the Data Hub space, a list and count of unique tags generated:

data upload to xyzspace 'zcispwpB' completed successfully
                     Upload Summary                     
Total 891 features

GeometryType  Count
------------  -----
Point         891  

Total unique tag Count : 19
Unique tag list  :["small","type@small","ne_10m_airports","mid","type@mid","mid_and_military","type@mid_and_military","major_and_military","type@major_and_military","military_mid","type@military_mid","military","type@military","major","type@major","military_major","type@military_major","spaceport","type@spaceport"]
TagName                  Count
-----------------------  -----
ne_10m_airports          891  
mid                      475  
type@mid                 475  
type@major               367  
major                    367  
type@mid_and_military    14   
major_and_military       14   
type@major_and_military  14   
mid_and_military         14   
type@military_mid        10   
military_mid             10   
type@military_major      4    
military_major           4    
spaceport                3    
type@spaceport           3    
type@military            2    
military                 2    
type@small               2    
small                    2  

Note: for the convenience of the user, tags will be generated both as the value and key@value of the tagged property.

Inspect GeoJSON properties using -a

If you don’t already know the names and value ranges of properties, you can use the -a option to inspect and select property names and their values before uploading them.

here xyz upload SPACE_ID -f ne_10m_airports.geojson -a

This will reveal an interactive command line prompt that lets you inspect the names of properties, and show a sample of their values to help you decide if they will make an appropriate tag. (You can choose more than one property to be a tag.)

Select attributes which needs to be added as tags like key@value
 ◯ 1 : scalerank : 9 , 9 , 9
 ◯ 2 : featurecla : Airport , Airport , Airport
 ◉ 3 : type : small , mid , mid
❯◯ 4 : name : Sahnewal , Solapur , Birsa Munda
 ◯ 5 : abbrev : LUH , SSE , IXR
 ◯ 6 : location : terminal , terminal , terminal
 ◯ 7 : gps_code : VILD , VASL , VERC
(Move up and down to reveal more choices)

Use the arrow keys to scroll through the properties, and press space to select (or unselect) a property.

The -a interface will also allow you to assign a property to be a unique ID. In most cases, it is best to skip this step and let the upload proceed by hitting return.

If you are certain that a property value contains a legitimately unique ID, this can help you retrieve individual features using the API using that ID.

Select attributes which would be used as Id, please note that ID field has to be unique
 ◯ 5 : abbrev : LUH , SSE , IXR
 ◯ 6 : location : terminal , terminal , terminal
 ◯ 7 : gps_code : VILD , VASL , VERC
❯◉ 8 : iata_code : LUH , SSE , IXR
 ◯ 9 : wikipedia : http://en.wikipedia.org/wiki/Sahnewal_Airport , http://en.wikipedia.org/wiki/Solapur_Airport , http://en.wikipedia.org/wiki/Birsa_Munda_Airport
 ◯ 10 : natlscale : 8 , 8 , 8
 ◯ 1 : scalerank : 9 , 9 , 9

Note that you can select multiple properties to be joined together as a unique ID.

Upload CSV and Shapefiles to a Data Hub space

Duration is 5 min

Geospatial data is often stored in formats other than GeoJSON. Data Hub spaces can upload and convert most .shp / ESRI shapefiles and .csv / comma separated values, with latitude and longitude fields simply by using upload -f – the Data Hub CLI will detect the file type and convert and upload automatically.

Note: -a and -p can be used to assign tags when converting CSV and SHP files.


The Data Hub CLI will recognize many common field names used in CSV files to designate latitude and longitude, including

y, ycoord, ycoordinate, coordy, coordinatey, latitude, lat


x, xcoord, xcoordinate, coordx, coordinatex, longitude, lon

If your CSV uses some other field name for latitude or longitude, you will get an error:

Could not identify latitude and/or Could not identify longitude

In this case, you may be able use the here transform command and then pipe the output and upload to a Data Hub space. If lt and ln were used as the latitude and longitude fields:

here tranform csv2geo --lat lt --lon ln geodata.csv | here xyz upload SPACE_ID


To upload a shapefile, add the file ending in .shp after upload -f – the Data Hub CLI will automatically read the other files that accompany the .shp file in the folder once it is unzipped.

If a .prj file is present, the CLI should automatically reproject it to WGS84.

Note: if the shapefile contains individual features that are very large polygons (more than 10 to 20MB), it may cause an upload error. mapshaper and QGIS can simplify and reduce the size of unnecessarily complex polygons and lines.

Upload data from a website to a Data Hub space

Duration is 5 min

The Data Hub CLI can attempt to download GeoJSON and CSV files directly from a website. Use the -f option – if you get an error, try enclosing the URL with quotation marks.

here xyz upload SPACE_ID -f "https://s3.amazonaws.com/xyz-demo/data/offices.geojson"

Note: downloading very large files may cause the service to time out. If so, try downloading it to your computer and then uploading as a file.

Stream large files

Duration is 5 min

To allow the upload of large GeoJSON and CSV files (greater than 200MB) via the CLI, you can use the -s option to “stream” to the HERE Studio API. (Files above 200MB can cause node.js to run out of memory.) Certain features like -a, that interactively assign tags by property, are not available while streaming, though you can use -p to designate what property values should become tags.

here xyz upload <spaceID> -f extremely_large.geojson -s -p category

Note that -s enables the upload of multi-GB GeoJSON and CSV files.

Work with GeoJSONL

Duration is 5 min

GeoJSONL is supported by the Data Hub CLI.

GeoJSONL is an emerging standard designed to lessen the memory requirements for parsing large GeoJSON files (from hundreds of MB to many GB). More information on GeoJSONL is available at interline.io.

The Data Hub CLI will recognize files with the geojsonl suffix, and no special command line flags need to be used.

here xyz upload <spaceID> -f extremely_large.geojsonl

A sample 27MB GeoJSONL file can be downloaded here.


Get information and statistics on a Data Hub space

Duration is 10 min

You can use the config option to get information about a space, including title and description.

here xyz config <spaceID>

The --stats option will give you more detailed information, including information on properties and tags in the space.

here xyz config <spaceID> --stats

You can share the space with others, so they can read it with their own access tokens. (They will not be able to write to it by default.)

here xyz config <spaceID> --shared true

You can also set the title, description, copyright information, and a schema definition with config. See here xyz config -h for more detailed information.

Inspect and view tags and data in a Data Hub space

Duration is 15 min

You can get lots of information about data in a Data Hub space via the command line. You can also use the command line to open your data in a map.

Count objects and tags in a Data Hub space

You can use the describe command to get a more detailed count of features and a list of tags used in a Data Hub space.

here xyz describe SPACE_ID

This command can take several seconds to a minute to complete depending on the size of the space. The output is similar to that after upload is run.

Note: describe only goes through the first 500,000 features. Also, for spaces containing large polygons, you may need to append the limit parameter, -l 100 -l 10 to prevent the command from timing out.)

View data in a Data Hub space

If you want to list individual features in a Data Hub space via the CLI, use the show command:

here xyz show YOUR_SPACE_ID

Hint: You can review all of your Data Hub spaces by typing here xyz list


here xyz show YOUR_SPACE_ID
id          geometry.type  tags  createdAt            updatedAt          
----------  -------------  ----  -------------------  -------------------
GlwPZ2KQ3W  LineString           5/21/2018, 11:37 AM  5/21/2018, 11:37 AM
qZIBhaZpcV  LineString           5/21/2018, 11:37 AM  5/21/2018, 11:37 AM
nZs1Z6exSS  LineString           5/21/2018, 11:37 AM  5/21/2018, 11:37 AM
dY5VxSyo3G  LineString           5/21/2018, 11:37 AM  5/21/2018, 11:37 AM
CsIq06n2nL  LineString           5/21/2018, 11:37 AM  5/21/2018, 11:37 AM

This will iterate through all the features and show the feature ID, the geometry type, feature properties and upload and modification time.

Note: this may be a very long list.

You can view the in a data in a space as GeoJSON using -r. This too will result in a lot of data, and it is best redirected to a file.

here xyz show SPACE_ID -r > my.geojson

You can also apply tags to download a filtered view of your dataset.

here xyz show SPACE_ID -r -t my_tag > my_filtered.geojson

View data on a map

Once you upload data to a space, you can see that space in HERE Studio’s data view and add it to a project. You can also use the command line to preview your data on a map.

The show command can also be used to open a Data Hub space in the GeoJSON Viewer, a web tool designed to quickly preview a moderate amount of GeoJSON data.

here xyz show SPACE_ID -w

This will generate a URL that includes your SPACE_ID and TOKEN_ID, and open it in your default browser. As an example, here is a map of a Data Hub space showing trains in India that depart from stations in Mumbai.


Note that the geojson.tools preview is designed for a few hundred to a few thousand points. If your dataset is larger than that, you can try

here xyz show SPACE_ID -v

which will open XYZ Space Invader, a Tangram-based preview and inspection tool that can show hundreds of thousands of features, and lets you filter by tags and color features by property.


Click on features to select a property to analyze by range or by rank, and choose from many different color schemes and basemaps.


The URL will save the state of the map so you can share it with others.

Delete features and spaces

Duration is 5 min

There will be instances where you may want to clear out the features of a space without deleting the space (especially if the URL is hard-coded into your application or scene file).

You can clear features from an existing Data Hub space by tag:

here xyz clear SPACE_ID -t TAG_NAME

You can also clear all features in a space by using a * as a tag wildcard.

here xyz clear SPACE_ID -t *

You can also clear individual features by their ID:

here xyz clear SPACE_ID -i FEATURE_ID

Note: once you clear features, you cannot reverse it.

To delete a Data Hub space, use the delete command:

here xyz delete SPACE_ID

Note: deleting features and spaces cannot be undone, so use caution!

View tokens for a Data Hub space

Duration is 5 min

The HERE Studio API and service require a token. Using a token will protect your account. If your token is ever stolen, you can revoke it and generate a new one.

You can see the tokens for your account by typing

here xyz token

The output will resemble this (though your tokens will be randomly generated hexidecimal strings)

Current CLI token is : token4
id                      type       iat         description                                                                   
----------------------  ---------  ----------  ------------------------------------------------------------------------------
token1                  PERMANENT  1534378300  xyz-hub=readFeatures                                                          
token2                  PERMANENT  1534528693  xyz-hub=readFeatures                                                          
token3                  PERMANENT  1534533359  xyz-hub=readFeatures                                                          
token4                  PERMANENT  1534533456  xyz-hub=readFeatures,createFeatures,updateFeatures,deleteFeatures,manageSpaces

Be sure to make note of the rights of tokens you use publicly – for example, you would not want to distribute token4 as it would give others write permission on your account.

View, create and edit Data Hub spaces via Swagger

Duration is 5 min

The Swagger UI makes it easy to see the full range of options for the HERE Studio API.

You can get information about your Data Hub spaces using the Swagger interface.

Note: you will need to enter a token to get access to your Data Hub space via Swagger.

You can use the Swagger interface learn how to use the API to list your spaces, iterate through a space, upload data, add tags, and filter data using tags, as well as updating and deleting spaces and features.


For more information and a list of all available CLI commands, please take a look at the official CLI documentation.