Omnisci platform looks promising. My usecase is not around dashboards but building a web-mapping application. I am building a webmapping prototype with mapbox GL as base library and leverage OmniSci serving the geospatial vector datasets. I have a few questions in this regard.
- Is is possible to add layers from Omnisci on top of mapbox with Community Edition license?
- Is there a feature to download the geospatial data from webmapping dashboards? So, far I only have seen downloading data from Charts from within Dashboard demos.
- Is it possible to query (summarize counts between geographies) across multiple layers?
- One of the main reasons to use mapbox as base library is that it supports rasters, wms protocols, ability to overlay third party vector-tile datasets. These are not supported in Omnisci yet as I understand it. Please correct me if I misunderstood here.
Glad you’re having fun with the platform. Good questions, let me take a stab
no you can’t, since that function would require the renderer API which is only in the enterprise edition
For more control and options, I once wrote a python WFS3 client which downloaded geojson, but with some sanity limits by default (<100k features or so). Its been awhile, but it was a “flask app” on the server which used pymapd to grab the features, and geopandas to serve out into various formats. The issues I delegated to geopandas were reprojection and file formats. In that way you can support download of zipped shapefiles in various coordinate systems for example.
To summarize across various vector feature geographies you generally need to figure out a scheme for subdividing them with some common geo key. Visually, you can do this in Immerse using the heat maps charts for either grids or hexes. To do it analytically, varies based on feature types and size relationships. Generally its a two-step. First you add a column to each input geometry layer and assign it a hex ID or lat/lon bin ID. Then you join on those IDs across layers.
Partially. We use normal Mapbox, to which you can add whatever you please. We also add “cross filtering” (through an OS library), which is often considered a major feature/improvement over the standard slippery map. OmniSci does support WMS within Immerse, and Mapbox lets you do that for a custom front end as well. We don’t usually worry about 3rd party vector tile sets because we’re usually dealing with dataset sizes you would never want to send across the wire. But in concept you could do it just by adding Mapbox config pointing to various other GIS resources.
You are correct that there is no raster support per se. However, the server doesn’t mind billions of points, and does provide a heatmap grid render. So my recommended workflow is to use GDAL to convert rasters to points, then render them as points or heatmaps. The performance is just fine, and you get the additional benefit of being able to cross-filter points dynamically (which rasters don’t usually let you do). For example, if you have a raster of land use, you can create an interactive histogram of land use class by record count or area. Selecting one or more of those bars will instantly update the map display (and everything else cross filtered).
Good luck, and if you can tell us more about your specific use case and I can perhaps provide more targeted advice.