Re: Looking for Developer for customer work on Map Block
Hi Steven, and welcome to the community!
I decided to respond openly in this thread for the benefit of other users and perhaps consultants who can rally to help you create a great solution. While my dance card is very full at the moment, I enjoy sharing some guidance and past success patterns.
Yes, this is a delicate question, and especially the case with integrated blocks.
Indeed, this is an ideal viewing context; seeing the location data aligned with actual data is quite nice. However, extending the functionality of the Map Block is not so easy. At the outset, Airtable has not made the source code to this block available for extending. As such, to take this a few steps forward would require commissioning a Custom Block whose development which will certainly be non-trivial.
I’m delighted this feature made the shortlist of your requirements. I have promoted this concept with great success and it is one of those things that are often discovered as a critical [missed] requirement soon after the location science project has been completed and deployed.
Achieving relevant search results in a mapping context from Airtable data requires some clever integration between Airtable, the mapping platform, and some sort of indexing technology. I use (and recommend) the same indexation algorithm that ElasticSearch is built upon, an open-source platform that started with Lucene.
By combining the underlying index platform with Mapbox and Airtable data, I’ve created a number of geo-search solutions that each extend from this Airtable Search project and whose influence found their way into these example solutions.
Adding marker points from a mapping solution into Airtable is pretty simple; polygons, not so much. Map points are simple numeric pairs, while polys are complex pairs; collections of lat/lng values. This data is best described in a Geo-JSON object. I encourage anyone who must meet this requirement to embrace this specification which will require some special handling of the data in Airtable as well as some unique approaches to using the data once captured in Airtable. Luckily, Airtable has recently embraced this approach by announcing early access to the JSON Editor which at the very least sanctions the idea that JSON data objects are welcome to be stored in the Airtable platform.
This is made possible through integrated MapBox and Google maps methods and while seemingly straightforward, developers often get this wrong because of subtle nuances concerning the zoom settings and tile-size computations. It’s not uncommon to see MapBox used with Google APIs to create ideal location metrics.
I believe both location platforms are capable of meeting your short list; it’s largely a matter of economics and developer experience, but I would tend to lean toward MapBox for this project partly because of my bias which was created through experience tackling location data science for many companies and governments. Here’s a brief portfolio of other solutions I’ve created, the vast majority of which are MapBox solutions some based on Airtable, most not.
Almost anything is possible with Airtable and location science; it’s a simple matter of skills, time, and money. :winking_face:
