Mapping the IVAucher

Featured

As a reaction to the record high of fuel prices, the Portuguese government has updated the IVAucher program, to allow each citizen to recover 10 cents per each liter of fuel spent, up to a maximum of 5 EUR/month. This blog post is not going to discuss whether this is good way of spending the public budget, or if it is going to make a real impact in the lives of the people that manage to subscribe to this program. Instead, I want to focus on data.

Once you subscribe to the program as a consumer, you just need to fill the tank in one of the gas stations that subscribed the program, as businesses. The IVAucher website publishes a list of subscribed stations, which seems to be updated, from time to time. The list is published as a PDF, with 2746 records, ordered by “districto” and “concelho” administrative units.

When I look for the stations around me, in the “concelho” of Lisbon, I found 67 records. In order to know where to go, I would literally need to go through each and check if I know the address or the name of the station. Lisbon is a big city, and I admit that there are lots of street names that I don’t know – and I don’t need to, because this is “why” we have maps. My first though was that this data belonged in a map, and my second though was that the data should be published in such a way that it would enable other people to create maps – and this is how this project was born.

In the five-star deployment scheme for Open Data, PDF is at the very bottom, and it is easy to understand why. There is so much you can do with a format, which is largely unstructured.

In order to be able to process these data, I had to transform it into a structured format, preferentially non proprietary, so I chosen CSV (3 stars). This was achieved using a combination of command-line processing tools (e.g.: pdftotext, sed and grep).

The next step was to publish these data, following the FAIR principles, so that it is Findable, Accessible, Interoperable and Reusable. In order to do that, I have chosen the OGC API Features standard, which allows to publish vector geospatial data on the web. This standard defines a RESTfull API with JSON encodings, which fits the expectations of modern web applications. I used a Python implementation of OGC API Features, called pygeoapi.

Before getting the data into pygeoapi, I had to georeference it. In order to do forward geocoding, I used the OpenCage API, and more specifically a Python client, which is one of the many supported SDKs. After tweaking the parameters, the results were quite good, and I was even able to georeference some incomplete addresses, something that was not possible using the Nominatum OSM API.

The next thing was to get the data into a format which supports geometry. The CSV was transformed into a GeoJSON using GDAL/ogr2ogr. I could have published it as a GeoJSON int pygeoapi, but indexing into a database adds support to more functionality, so I decided to store it in a MongoDB NoSQL data store. Everything was virtualized into docker containers, and orchestrated using this docker-compose file.

The application was deployed in AWS and the collection is available at this endpoint:

https://features.byteroad.net/collections/gas_stations

This means that anyone is able to consume this data and create their own maps, whether they are using QGIS, ArcGIS, JavaScript, Python, etc. All they need is an application which implements the OGC API Features standard.

I also created a map, using React.js and the Leaflet library. Although Leaflet does not support OGC API Features natively, I was able to fetch the data as GeoJSON, by following this approach.

The resulting application is available here:

https://ivaucher.byteroad.net

Now you can navigate through the map until you find you area of interest, or even type an address in the search box, to let the map fly to that location.

Hopefully, this application will make the user experience of the IVAucher program a bit easier, but it will also demonstrate the importance of using standards in order to leverage the use of geospatial information. Making data available on the web is good, but it is time that we move a step forward and question “how” we are making the data available, in order to ensure that its full potential is unlocked.

DevRel – What is that?

Almost a year ago, I heard the term DevRel for the first time when Sara Safavi, from Planet, gave a talk at CodeOp and used that word to describe her new role. I knew Sara as a developer, like myself, so I was curious to learn what this role entailed and understand how it could attract someone with a strong technical background.

It turns out that DevRel – Developer Relations – is as close as you can be to the developer world, without actually writing code. All these things that I used to do in my spare time, like participating in hackathons, writing blog posts, participating in conversations on Twitter, speaking at events, are now the core part of my job. I did them, because they are fun, and also because I believe that ultimately, writing code has an impact in society, and in order to run that last mile we need to get out of our compilers and reach out to the world. Technology is like a piece of art – it only fulfills its mission when it leaves the artist’s basement and it reaches the museums, or at least the living room of someone who appreciates it.

I am happy to say that I am now the DevRel at the Open Geospatial Consortium. In a way, it is a bit ironic that I ended up taking this role in an organization that does not actually produce software as its main outcome. But in a way OGC is the ultimate software facilitator, by producing the standards that will be used by developers to build their interoperable, geospatial aware, products and services. If you are reading this and you are not a geogeek, you may think of W3C as a somehow similar organization: it produces the HTML specification, which is not itself a software, but how could we build all these frontend applications using React, Vue and so many other frameworks, without using HTML? It is that important. Now you may be thinking, “so tell me an OGC standard that I use, or at least know”, and, again, if you are not a geogeek, maybe you won’t know any of the standards I will mention. Even if you use, or have used at some point location data. And this is part of the reason why I am at OGC.

Location data is increasingly part of the mainstream. We all carry devices in our pockets that produce geo referenced data with an accuracy that was undreamed ten years ago. Getting hold of these data opens a world of possibilities for data scientists and data engineers, but in order for all these applications to be able to understand each other we need sound, well articulated standards in place. My main goal as DevRel at OGC will be to bring the OGC standards closer to the developer community, by making them easier to use, and by making sure that they are actually used. And maybe, just maybe, I will also get to write some code along the way.

Interactive Maps within React.js

Recently, I have been teaching a Full-stack development bootcamp at CodeOp (great experience!).

When the students reached project phase, I was very pleased to see a lot of interest in using maps. And that is easy to understand, right? geospatial information is associated to most activities these days (e.g.: travel, home exchange, volunteering), and interactive maps are the backbone of any application which uses geospatial information.

This made me think of a nice way of introducing the students to interactive mapping. I realized that most of them want to do one thing: read an address and display it on the map, which also requires the use of a geocoder. In order to demonstrate how to put all these things together within a React application, which is the framework they are using, I created a small demo on GitHub. This was also an opportunity to practice and improve my front end skills! 🙂

Following a good tradition of GitHub, I started by forking an existing project, which I thought was similar to what I wanted to achieve. Although the project is extremely cool, I realized that I wanted to move in quite a different direction, so I ended up diverging a lot from the original code base.

To implement the map, I used my favourite library for interactive maps, Leaflet. This library is actually packaged as a React component, so it is really easy to incorporate it into an application.

Of course, maps only understand coordinates, and most of the time people have nominal locations such as street names, cities, or even postcodes. This was also the case with my students. Translating strings with addresses to a pair of coordinates is not a trivial task, so the best thing is to leave it up to the experts. I used the Open Cage geocoder, an API to convert coordinates to and from places. Why? It has a much more generous free tier than the Google Maps API, and it is open-source. And although it is built on top of OSM Nominatum, it contains several improvements.

The good news are OpenCage also has a package for JavaScript and Node, and it is really easy to use. This is the piece of code, to retrieve the coordinates from a given string:

    // Adds marker to map and flies to it with an animation
    addLocation =() =>{
      opencage
        .geocode({ q: this.state.input, key: OCD_API_KEY})
        .then(data => {
          // Found at least one result
          if (data.results.length > 0){
              console.log("Found: " + data.results[0].formatted);
              const latlng = data.results[0].geometry;
              const {markers} = this.state
              markers.push(latlng)
              console.log(latlng);
              this.setState({markers})
              let mapInst =  this.refs.map.leafletElement;
              mapInst.flyTo(latlng, 12);
          } else alert("No results found!!");

        })
        .catch(error => {
          console.log('error', error.message);
        });


    }

In order to do this, you need to sign up for a free API key first, and store it within a secrets file (.env).

The application allows the user to type any address, and it will fly to it with an animation, adding a marker on the map.

You can check out the final result at https://leaflet-react.herokuapp.com/

marianella_watercolor

 

 

FindMeACoin: a Platform to Support Offline Trading of Cryptocurrencies

Trading crypto currency offline1, in person, is the quickest way of acquiring/selling crypto coins. It is also the only way of not exposing any identity information.

This post presents a platform for finding buyers/sellers for crypto currencies in a certain geographic location. Registered users can find other users on a map, and get in touch with them to arrange a meeting.

findmeacoin

The collected information about the users is kept at the bare minimum.

The platform only puts users in touch. It does not participate or interfere in the trading process, and thus it does not take any liability for what may happen. However, if the transaction is successful it does collect a fee, based on a smart contract.

The platform uses a gamification approach, with the use of avatars, associated to reputation. It aims to be kept simple and user friendly.

At this stage we are looking forward to collecting expressions of interest, and feedback in general. If you want to be the first to try FindMeACoin, please register now!

FindMeACoin is a platform which enables users to trade cryptocurrencies, in a private, reliable, easy and fun way.

Let’s make transactions private again!

1In this context, trading currencies “offline” means trading currencies in person, converting from cash to a cryptocurrency, or vice versa.