Mapstack, launched this week, aims to become a central catalogue for open data, a place where you discover and access datasets to fulfil your geo-data needs:
mapstack will do for open map data what GitHub did for open source, by bringing all of the world’s open maps together in one place and making them easy to discover, easy to access and easy to use.
Most of Mapstack’s functionality is currently centred around creating datasets and providing appropriate descriptions for the data. Setting up a new map involves several steps, including creating a new workspace or team, adding members, and providing a description.
Then you proceed to create the actual dataset. Upload your data, currently limited to GeoJSON and files smaller than 50MB. Then select the fields to keep and provide human-readable names. A downside is that you can’t skip this step. You have to go through each chosen field and individually confirm the label. To finalise, provide more information about the nature of the data, its geographic area, and the feature type, which creates an editable name for your new dataset.
That’s a lot of steps before you can view your dataset for the first time. Much of the information can be done after the project is set up. With the goal of discoverability in mind, however, and considering how badly many datasets are missing meta-data, you could say it’s smart design to force users to provide context.
Once the map is created, the features are limited: You can browse the data, view the attribute of features, and apply filters. There’s an attribute table, which is only available for filtered results, but not for the unfiltered data. Mapstack focuses on hosting data and making the data discoverable rather than on interacting, editing or visualising data.
As such, Mapstack is not a competitor of Felt or Placemark, two products released last year that aim to modernise how we do GIS on the Web. Mapstack complements both, and GIS tooling in general, by providing the data for the tools.
Will it take off? I’m not sure. The marketing copy draws comparisons to GitHub, but there are differences. GitHub became successful because it built on a protocol that developers already used and provided a product for collaboration around the protocol. GitHub added value to the developer’s daily work, so a lot of code ended up on the platform.
Mapstack doesn’t tie in with existing tools. Currently, there is no tooling to create or manage data, collaborate or visualise the data. It’s a place where the result of data processing might be hosted. Open data providers have invested in the infrastructure to host data—it’ll be hard to convince them to migrate to Mapstack instead.
Seek-Optimized ZIP, a new profile for ZIP files, allows random access and selective decompression. With standard ZIP files, you have to download and decompress the ZIP file before accessing its content. While fully compatible with standard ZIP tools, with SOZip, you can now selectively access files within a ZIP, so you won’t have to download the full archive if you want to access just one file.
Currently, there are two implementations for SOZip: It’s available in the development branch GDAL and as a Python module. MapServer (on the development branch) and QGIS, both applications depending on GDAL, support SOZip too.
Seek-Optimized ZIP file adds to a growing suite of cloud-native data formats and APIs, such as COGs, Zarr or GeoParquet, allowing developers and applications to access and process large selectively without the need to download complete datasets.
gpq is a nice little tool created by Tim Schaub to validate GeoParquet data and convert GeoJSON to GeoParquet. gpq also powers a web service, so you can convert GeoJSON in the browser.
Workflows, a new workflow builder introduced by Carto, allows people to build geo-data-processing workflows without writing code. It simplifies the creation of nested SQL queries. It provides means to import data from an external service or send the processing result via email.
The full extent of capabilities is pretty sparse at the moment. Workflows is currently in private beta; the public beta will be released in the “coming weeks.”
Christopher Beddow reported it first (at least in my timeline); the small-scale GeoJSON editor Geojson.io received an update after development had lied dormant for a while.
There are no recent releases, the changelog hasn’t been updated in over four years, and the Mapbox blog is quiet on the topic. It’s hard to precisely summarise what has changed. But based on my memory of the feature set before the update, newly added features include the following:
Project the data using Mapbox’s recently released globe projection.
New base maps, including Outdoors, Light, and Dark styles.
Load XYZ tile layers from external sources.
Create a set of points, ideal if you want to quickly create an artificial dataset for testing.
Enhance existing geometries by automatically adding bounding boxes to each feature.
Import data from text and binary formats, including:
Encoded polylines
Well-know Binary (WKB)
Well-known Text (WKT)
Update: Chris Whong pointed out on Twitter that most of the functionality outlined above was already existing prior to last week’s update. Chris has also updated the changelog. I missed a couple of new features, including:
The underlying mapping library was upgraded to MapboxGL, which enables the globe projection.
Automatic formatting of GeoJSON when pasted.
Code-folding, ideal for working with long GeoJSON documents.
Martijn van Exel wrote a review of Every Door, the OpenStreetMap editor for mobile phones:
We had a lot of fun mapping with Every Door, and I think we were more productive adding and updating POIs than we could have been with any other app! There’s lots of little things that make your life easier.
[…]
I would encourage anyone who likes to get out and survey to try it!! Huge thanks to Ilya for making Every Door available to the community.
I have reported on Every Door before; you should read Martin’s review for an opinion from someone who edits OpenStreetMap much more than I do.
QField, is an open-source app for collecting and managing geographic data in the field that integrates tightly with QGIS, the poster child of open-source desktop GIS. Until recently, the app was only available for Android phones, but since the release 2.4 you can also use it on iPhone devices.
We all love a bit of retro flair on our maps, don’t we? If you agree, then BellTopo Sans might be what you’re looking for. Designed by Sarah Bell, it’s a sans-serif typeface for map labels, inspired by old USGS maps:
When you see this typeface that I’m referring to on these old beautiful maps, you may think it is nothing special. It’s simple. It might even be very similar to a common font that you already know. Perhaps you’re thinking, “Why didn’t she use that font?” But for me, the beauty of this typeface that I see on old USGS maps exists within its subtle differences.
I like BellTopo Sans because, unlike many modern fonts, it is a little rough around the edges — it has character. Look at that upper-case R and that lower-case g; just look at them.
BellTopo Sans works best in medium font sizes and with a bit of character spacing.
JSON documents can be challenging to read, especially GeoJSON, with complex geometries and many feature properties. JSONCrack visualises JSON documents in a graph, making them easier to parse visually and to understand their structure and content.
GeoJSON features visualised in a graph using JSONCrack.
JSONCrack works best with small(ish) files. I initially tested with a 17.7MB GeoJSON file that contains about 16,000 records. While it parses and formats the file without issues, it can’t produce the visualisation. Only at about 500 records did JSONCrack render the visual representation.
