The fifth module of this course deals with access to web services from gvSIG. At this first part we will introduce you to a fundamental concept when we talk about the efficient management of geographic information: Spatial Data Infrastructures (SDI). SDI are very important, and countries and regions of the world are legislating them more and more to make effective their implementation in all the administrations that generate digital geographic information.
The SDI is considered the ideal system to manage the geographic information of an organization and, of course, of a municipality completely. In future modules of this course we will speak about gvSIG Online, the free solution to start them up. In the current module we will see how to work with the web map services that SDI can generate from the desktop GIS.
Currently, a large number of administrations offer their cartography in a public way to be loaded through web services. Thanks to the use of this device it is possible to access these services from gvSIG Desktop, which allows us to load the cartography in our project without having to download anything on disk.
In order to understand this part in gvSIG in a better way we will start with a video about the introduction to the Spatial Data Infrastructures, where we will explain what a web service is, and some links where these available services are collected.
In this module it is not necessary to download any cartography, since it is a totally theoretical video.
Here you have the first videotutorial of this fifth module:
Ya está disponible la grabación del taller de Geoestadística con gvSIG impartido durante la Jornada realizada en la Universidad Miguel Hernández de Elche, España, el día 13 de diciembre de 2017, englobada dentro de la Cátedra gvSIG.
En esta jornada, aparte de los talleres sobre la aplicación y la ponencia sobre la Suite gvSIG se hizo entrega de los premios a los proyectos ganadores de la Cátedra gvSIG 2017.
En el vídeo se explica una breve introducción de cómo ejecutar código de R desde el Módulo de Scripting de gvSIG. El lenguaje de programación R orientado a la estadística y el análisis de datos permite un amplío abanico de posibilidades para el tratamiento de datos espaciales que complementan los ya existentes en gvSIG o los desarrollados también desde Scripting con Python.
El ejemplo mostrado realiza una lectura masiva de ficheros csv correspondientes a crímenes en la ciudad de Londres, sacados del portal de open data UK Data Police, los cuales transformamos a una capa shapefile para poder ser explorados desde gvSIG.
Cualquier duda puedes preguntar aquí o en las Listas de Correo.
At this second video of the fourth module we will continue speaking about the attribute tables, where we will show how to join the the alphanumeric information of a vector layer and an external table.
In our city council we can have external information in a table, and it would be interesting to georeference it, that means, to join the information of that table with the alphanumeric information of a vector layer.
For example, if we have a table with the population of each neighbourhood in our municipality, and we also have a vector layer with the neighbourhoods in our GIS, we can add the population of the first table to the graphic layer. For that we would need a field in both tables with common values. If we use the name of the neighbourhoods there can be different names (with or without the article…), so we can get an error. Then it will be recommendable to use a numeric field, where the numbers will be the same in both tables (we can use the neighbourhood code).
Here you have the second videotutorial of this fourth module:
Diciamo subito che nel 2016 ho letto poco e male, e diamo la responsabilità al fatto che nella prima parte dell’anno invece ho scritto un po’ (abbastanza da concludere la mia tesi di dottorato, tanto per capirci), mentre nella seconda parte dell’anno ho dedicato del tempo allo studio per un concorso (che poi è andato bene).
Aggiungiamo che poco dopo la fine del 2016, come alcune delle letture suggeriscono, sono diventato papà, e ho aiutato come potevo la mamma con il suo pancione, invece che leggere (tranne un caso in cui ho letto per loro molte volte lo stesso libro ad alta voce).
- James Ellroy, Perfidia è il mio preferito e mi ha fatto trovare vecchie mappe di Los Angeles (il massimo)
- Wu Ming, L’invisibile ovunque
- Joe R. Lansdale, Rumble Tumble che mi ha passato Andrea Bellotti e non glielo ho ancora reso
- Roberto Negro, Bocca di rosa
- Loredana Lipperini, Ancora dalla parte della bambine
- Julien Blanc-Gras, Padri in attesa. Il giornale di bordo di un padre nella Terra della gravidanza
- Chiara Cecilia Santamaria, Quello che le mamme non dicono
- Emma Mora, L’orsacchiotto Gedeone (qualche dozzina di volte)
Update: Barcelona is going all-open. Sounds extreme, but some times you’ve got to…
“You’ve got to spend money to make money”, I once confidently told a business associate, on the occasion of paying him a thousand dollars to manually clean some terrible data for me. In the event, I was right: that cleaned data paid for itself 10 times over in the following years.
I’m still the only person with a GIS file for 1996 BC elections results by voting area, and the jealousy is killing you.
Governments can play the game too, but it seems like they all end up tilling the same landscape. There’s no shortage of governments trying to create their own Silicon Valley clusters, usually through the mechanisms of subsidizing venture capital funding (via tax breaks or directly) and increased spending on R&D grants to academia. Spending money to “hopefully” make money.
There’s an under-recognized niche available, for a government willing to go after it.
@nayafia Thanks for Roads & Bridges and the rest of your oeuvre! I'm currently researching the question of gov funding of OSS from a Mazzucato / Porter cluster development / Tire Tracks point of view; may I ask for advice? I'm looking for success stories, preferably quantified.— Meng Weng Wong (@mengwong) January 2, 2018
Venture capitalists are (understandably) interested in having their investments create “intellectual property”, that can be patented and monopolized for outsized profits. By following the VC model of focussing on IP formation, governments are missing out on another investment avenue: the formation of “intellectual capital” in their jurisdictions.
VCs don’t like intellectual capital because it’s too mobile. It lives between the ears of employees, who can change employers too easily, and require expensive golden handcuffs to lock into place. They can monetize intellectual property in an acquisition or public offering, but they cannot monetize intellectual capital.
Governments, on the other hand, understand that by investing in universities and colleges, they are creating intellectual capital that will tend to stick around in their jurisdictions (for all the public wailing about “brain drain”, the fact is that people don’t move around all that much).
Investment in open source technology is a potential gold mine for creating intellectual capital, but governments have been steadfastly ignoring it for years. There is also a big first mover advantage waiting for the first governments to get into the game:
- Instead of “buying off-the-shelf” for government information systems, build on existing OSS, or start OSS from scratch, using local talent (in-house or private sector).
- Deliberately build with enough generality to allow use in other jurisdictions.
- Become the first reference customer for the project. Send your local talent out to evangelize it. Encourage them to commercialize their support and services.
- Wash, rinse, repeat.
Is this risky? Yes. Will it result in some failed projects? Yes. Will it be more expensive than the “safe” alternative? Sometimes yes, sometimes no. Will it result in increased revenues flowing into your jurisdiction? Almost certainly, if committed to and carried out across a number of projects.
When the first library in BC adopted the Evergreen open source library software, they probably weren’t envisioning a Canada-wide open source cooperative, bringing support and consulting dollars into the province, but that’s what they did, by accident. When the Atlanta Public Library started the project, they probably weren’t thinking a local company would end up selling support and expertise on the software around the country.
There is no IP moat around open source projects, but there is a first mover advantage to having a critical mass of developers and professionals who have amassed intellectual and social capital around the project.
Intellectual capital isn’t just built in universities, and the private sector shouldn’t only be looked to for intellectual property. Let’s mix it up a little.
The BC government spends $9M/year on Oracle “maintenance”, basically the right to access bug fixes and updates from Oracle for the software we’re running. It’s not a lot of money, but it’s money being shipped straight over the border. Affilias, the “.org” top level DNS provider built their infrastructure on PostgreSQL – they spend a couple hundred thousand a year having some PostgreSQL core developers on staff. Same effect, different path.
gvSIG Team: GIS applied to Municipality Management: Module 4.1 ‘Attribute tables (alphanumeric information)’
At this first video of the fourth module we will speak about the attribute tables of a GIS, and we will show how to manage the alphanumeric information of a vector layer.
As we told at the first module, about differences between GIS and CAD, at the Geographic Information Systems we can manage different types of alphanumeric information. For example, for a parcel we can add information about the owner, area, coordinates, date of the buildings… And we can make a query to get the elements with a concrete values (for example the parcels with an area higer than X squared meters).
That information will be very useful for our city council, to manage the information in an easy way.
At this module we will see hot to manage that information.
At the first module of the course you can find a frequent questions section about the course, and if you have any doubt or error using gvSIG you can consult this post: https://blog.gvsig.org/2015/06/17/what-to-do-when-we-get-an-error-in-gvsig/
Here you have the first videotutorial of this fourth module: