The GeoSeer Blog

Data portals - not always the solution

Posted on 2020-01-10

There are lots of Open Data portals out there, many promising a wealth of data, be it spatial or otherwise.

We want to ask: how effective is this strategy of deploying lots of data portals? GeoSeer uses many of these portals as its seeds so we think we're in a good place to investigate them. data portal front end

How many are there?

The first problem is the sheer number of them. Lets start with CKAN; CKAN is "the world’s leading Open Source data portal platform" and it offers an API which GeoSeer can use to harvest geospatial web services from portals that use this software. It seems to be the software of choice for many government based data portals and as it stands right now, GeoSeer is aware of 191 working CKAN portals.

The other big data "portal" isn't really a piece of software but a standard: CSW - Catalog Services for the Web. Basically it's a standard for serving metadata via XML, and most deployments we're aware of are either GeoNetwork or PyCSW; there's also ESRI's geoportal software but almost no-one seems to use that, and then whatever the European Commission rolled themselves for the INSPIRE CSW which is different again. GeoSeer has 325 working CSW services in its index (and 47 non-working). Note that some of these may be hosted by the same organisation but be sharing metadata for different types of data. I.e. and

Lots of portals == Good?

If you haven't done the maths in your head, that's 516 working data portals. There's actually some overlap between these groups; some CKAN portals also have CSW backends, but the general point stands.

Great, loads of data portals, that is great right? Well, not quite, you see, what if you want to actually find data? That is the ostensible purpose of all of these things isn't it? Well now as an end user you've got 516 data portals to search through... And of course those are just the data portals that support those two API's, there are many bespoke data portals that don't have nice API's that GeoSeer doesn't crawl (for example, Belgium, or the DKAN software).

Lets say you want some data for a location in Colorado, USA. Do you use the local data portals, such as Denver Opendata, or go to the state level (Colorado's portal (which is actually what's behind Denver's portal)), or the national or maybe domain specific ones like NETL's, NOAA's, NASA's, the USGS's, etc.? And that's ignoring the fact many of those organisations have multiple portals! You can see how this gets difficult fast.

And mostly unpopulated

The dataportals themselves, at least the national ones, usually boast many datasets, but how many of the spatial web services that are out there are actually in these portals? GeoSeer has the largest index of these services that we know of (by a large margin), so we thought we'd compare them. Here's a table, then we'll break it down.

Number of Hosts5,002259
Number of Services215,6997,783
Number of Datasets2,044,64465,959

Only includes hosts/services/datasets that were live in December 2019.
Note: CKAN numbers *exclude* the USA' CKAN portal because their API is different from the other 190 out there.

So, what does this show?
The GeoSeer column shows how many of these things GeoSeer has in its index today. The CSW and CKAN columns show how many of these things each portal type has in it. So between 190 CKAN portals they only point to 65,959 spatial web service datasets across all of them, which is 3.23% of the number that are actually out there. And the 325 CSW services point to 130,065 such datasets between them.

There are also two column headers that end in a +. These columns represent the addition of some of GeoSeer's secret sauce. Basically we know and understand the spatial web standards and the software behind them, and using this knowledge we make intelligent guesses at what else might exist on a server. These two columns therefore represent how many things there actually are on the services that the CKAN/CSW portals point to, or at least a minimum number.

But what does all that mean?

Well, there are several things we can say with surety:

  • As a general rule, if a spatial web service is put online, at most only half of datasets/services that are online on that box are actually put onto data portals. It may be (and almost certainly is) less than half.
  • That even if you did search 515 CSW and CKAN Open Data portals (excludes CKAN USA), you'd only be searching a tiny small fraction of the spatial web services out there. On the order of less than 8%!

Wrapping up

The above only covers False Negatives - things that should be in the data portals but are not. There's also the issue of False Positives: things the portals say exist but don't; with any luck we'll get around to analysing them in the future.

What's the solution to this? We don't claim to have answers, but if your organisation is considering rolling its own data portal ask yourself - is it worth it? For the considerable costs you're going to incur what value are you going to add that putting your data in the national database won't add? And if you run a national portal, make it easier to search, host and maintain data for local communities.

In the mean time, you freely can use GeoSeer to search across all those portals and many more easily and quickly. And you can integrate it into your own webgis/projects using the API or GeoSeer Licensed.

GeoSeer Licensed Products Released

Posted on 2019-11-27

We hinted at it in August and now it's here; today we're releasing a licensed version of the database that sits behind GeoSeer, creatively called: GeoSeer Licensed.

GeoSeer Licensed content allows organisations and businesses to host and integrate their own local copy of GeoSeer's industry leading database of spatial web services directly into their own applications, products, or services. We figure this can improve end-user workflows, make discovery of third-party data and services much easier, and help organisations realise some of vast economic benefits Open Data presents - estimated at €75 billion across the EU in 2020 alone. Also, you can build cool things with it.

This nicely compliments the GeoSeer API which was released back in April. Where the API allows organisations to easily build GeoSeer's search into web applications by making calls to our servers (like the GeoSeer WebGIS demo does), GeoSeer Licensed allows organisations to host the database locally, or release it in a product, meaning any sort of application can be built around it, not just search.

The Value Add

Lets be honest, there's nothing stopping you from building your own spider, finding 550+ dataportals to use as seeds, scraping half a million web-pages a month, and building your own database of geospatial web services. So why use GeoSeer Licensed?

  • Industry Leading Database - At the time of writing we're not aware of any database of geospatial web services anywhere near as large as this (and we've looked).
  • Current - We run regular crawls to make sure everything in GeoSeer Licensed is current. We provide monthly updates so you always have the latest data.
  • Pre-Cleaned - despite these being standards, everyone likes to do things differently. We've pre-cleaned the fields and tried to standardise them to make them consistent. For example we've found no less than 55 ways to say "No license fees" across 12 languages and turned that into a simple: "No".
  • XML Free - it's 2019 and fewer people want to deal with the hassle of namespaces, esoteric data models, and the other complexities XML brings. We've extracted the data from the XML documents and put it into a database, with some JSON sprinkled in where necessary.
  • Spatial Extents - For GeoSeer Datasets we include the extents bounding boxes in WGS84 format, along with scale-appropriate textual representations of the locations, potentially down to county level (like you see in GeoSeer Search).
  • Quick start - Because we've done all the hard work, written up documentation about what each field means (so you don't have to read the standards), and packaged it in an SQLite database, it's super easy to get started with. Simply open your favourite database admin tool (it probably supports SQLite), and get querying with good old fashioned SQL.

The Products

GeoSeer Services is a database with all of the current geospatial web services that GeoSeer knows about in it, as well as information about their endpoints, hosts, and more. At the time of writing it has over 215,000 services in it from across 4,930 different hosts. This information is good for investigating who is hosting services, what sorts of services exist, INSPIRE deployment patterns/conformity, etc.

GeoSeer Datasets builds on GeoSeer Services, including not only all of the service information, but all of the dataset metadata as well. This includes: dataset extent bounding boxes, dataset keywords, declared projections, scale-appropriate textual location, metadata urls, and more. GeoSeer Datasets is well suited to building search engines (surprise!), GIS, web-GIS, academic research, and much more.

Both products are available with a number of different license types, from a research license through to commercial licenses. We can also provide subsets of the database if you don't want everything.

We like to think we've built a great search engine around this data, so now it's your turn - what can you build with it? Find out more about GeoSeer licensing.

Plotting Dataset Extents

Posted on 2019-10-31

Back at the start of September we released some historical statistics and, almost as an afterthought, mentioned the new extents plots. In this post we explore those dataset extents plots in more detail.

Extent Plots; What Are They?

Put simply, every dataset that GeoSeer indexes follows various standards which say that the datasets should declare a rectangular bounding box which represents its spatial extent, i.e., where does the dataset cover? So if it's a dataset covering Germany, it should declare a box covering Germany, but because Germany isn't a rectangle, the box will overlap with surrounding countries to various degrees, including all of tiny Luxembourg.

What we've done is taken all of those extents boxes and stacked them all up, overlapping them to create what we call extent plots which show how many datasets cover a given area. As you can imagine there are a lot of caveats to this process (as well as to the dataset extents themselves, like the Luxembourg example above), these are covered in detail on the datasets extent plots page.

What do they show?

One important caveat to remember is that the plots only show dataset extents that are entirely within the plot extent. The exception to this is the Global plot where we're also excluding the 191,052 global datasets (about 10% of all datasets) as they add nothing to the plot. It's interesting to note that ~10% of all datasets are global though.

So the plots show where in the world there are lots of spatial datasets available via WMS (Web Map Service), WFS (Web Feature Service), WCS (Web Coverage Service), and/or WMTS (Web Map Tile Service). There are two colour schemes, we're mostly using the spectral one here because it brings out more detail even if it's not very aesthetically pleasing.

Global extent plot Starting with the global plot (above) it's obvious that the EU's INSPIRE directive has had a considerable effect, particularly in central Europe. The USA and Brazil also have considerable coverage.

Looking closer at West Europe (below), it becomes apparent that the rectangular nature of the extents are causing lots of overlaps in the region of the Netherlands/Belgium/Germany tripoint (apparently called the Vaalserberg), hence the very high values there. That said, there's still a lot of datasets covering the region. West Europe

Zooming even closer to one specific country such as the UK (below), it's possible to see a lot of nuance that's swamped out at the smaller scales. It's now clear that Wales has excellent national coverage compared to England (which is mostly just the South East, not even London), and certainly Scotland (just Glasgow and Edinburgh). UK Extent plot

Bad data

Do you notice anything odd about this plot of Africa (apart from it being green)? Africa plot with bad data

Yep, there's a very large number of datasets covering a tiny area off the west coast of Africa. Why? As you've probably guessed it's because 6,527 datasets are wrongly declaring their extent as being entirely around 0, 0 (lat/lon). This floods out Africa which unfortunately doesn't have many datasets in the first place. So we filter these bad datasets out of the plot extents to get the below. Now we can see that east Africa has a respectable number of datasets covering it, as do the Canary Islands. Africa plot with good data

Technical; How We Make Them

We use Python to create these plots by reading in all of the WGS84 (coordinate system) bounding boxes from the GeoSeer index, stacking them together with NumPy as a two dimensional array, and then plotting them out via MatPlotLib. NumPy does the magic of summing the extents together remarkably quickly so we can rebuild them every month with the updates.

Closing Remarks

There are other interesting insights that can be gleaned from these, take a look at the Datasets Extent Plots page for more. This is a good case study of the sort of cool stuff you can do with Python, and GeoSeer Datasets, for example if you have a research itch you need to scratch.

Because we like to share, the plots are available for use under the CC-BY 4.0 license, which means you can do anything you want with them but please link back to GeoSeer.

Finally, if there's any particular area you think would make an interesting plot, let us know and we'll take a look.