The Future of GIS, a Study of Conferences — Part Two — Second Verse
So this blog picks up where this blog ended, putting together the text analysis for the Workshops at FOSS4G. I referred to FOSS4G as thick, and the 54 workshops that are taking place the two days before the conference are substantial as well. Before we dive into this analysis, lets look at what is happening the two days before FOSS4G:
Monday, August 14th — Workshops ($$)
Tuesday, August 15th — More Workshops ($$)
Tuesday, August 15th — JSgeo ($$)
Tuesday, August 15th — Fulcrum Live(Free, if you sign up before 31 July)
Tuesday, August 15th — Me singing either Nickleback or Patsy Cline at Hong Kong Boston(Fire Drinks)(Freeish)
Okay, now that that’s out of the way let’s dive in-
Like I said in the first blog post of this series, the analysis is evolving, as I work with the data more it will improve. With FOSS4G tech lacking a “standard” platform a number of the Workshops are mishmashes of technology and if something is like Node, PostGIS and Geoserver, where would it go? Okay, bare with me through this explanation — If major technology within a Workshop does not make the top ten cut *cough* geoserver *cough*, and if the supporting technology is in the top ten, then the technology in the top ten gets the point. Like if something is Perl with GeoMesa, and Perl didn’t make the top ten, but GeoMesa did, GeoMesa would get the point, not Perl.
Also, since Workshops can be four hours, or eight hours, if the workshop is eight hours its counted twice.
ITS THE SUMMER OF POSTGIS, SUCK IT Q
Eight workshops out of the 54, about 15 percent of the total number of Workshops. Everything from getting up to speed on Spatial SQL in PostGres, to temporal analysis , all the way to Advanced Spatial Analysis.
With QGIS, there isn’t a surprise here, it’s a popular desktop technology within the FOSS4G community and its growing.
Python in the fourth slot is surprising, I expected there to be more Python presentations with the number of spatially related libraries are being released.
Coming in at number five are drones and sensors. This is interesting because drones and sensors did not break the top 20 in the sessions analysis of FOSS4G. Obviously people are using them, but there does not seem to be a direct call out within the sessions, opposed to the workshops.
Rounding out the top ten, all with two sessions each, are 3D, R, Solr/Search, Big Data, Cloud Computing, GDAL, and GeoNode.
3D, which had the most sessions in the conference, only has two workshops. A SWAG about this is that 3D technology lends itself better to shorter sessions, and less to a 4 hours workshop. Full disclosure, I’m not sure how I’m going to fill up a four hour workshop.
<Narrator> Expect puppets
Its nice to see R on the list, and with expansion in R spatial libraries, and with its growing popularity within the Non Brand X/Non Classically Trained Spatial Analysts, it’s going to be around for a while. I mean, check out the trend in R libraries.
Solr/Search, specifically Geoblacklight are technologies that we all need to pay attention too, but never seem to have to time, or want to do. One of the hardest things to do is to find spatial data. Especially now, when open data portals and data sets being removed.
Big Data, and Cloud Computing are both on this list, but I think that goes back to people being comfortable with these technologies to give a four hour presentation on the subject. I mean, if you aren’t in AWS by now, whats the hold up?
GDAL, the workhorse of the Spatial industry, really needs to be common knowledge among anyone working in GIS. Also, it deserves a damn award from us for being the awesome backbone that allows us to work the magic we do. I mean if FME can give a Shapefile an award, we can give GDAL, the first shapefile slayer, an award. A statue in Redlands would be better though.
Last in the study, but not in mentions is GeoNode. GeoNode is an open spatial platform for managing spatial data services, and allowing a place to collaborate and share data. Between the GeoNode and Solr results show there is a need/nitch within the Spatial Industry to share and discover our data.
As far as up and comers I see three technologies to watch/to learn. R, which is enjoying a a great deal of support from the open data science community, and as geographers we can benefit from that. Serverless/Container technology, the ability to create and share services without concerning yourself with the whole similar environment thing is pretty much magic.
Third, is the rise of Spark within the Spatial Industry. Spark is a core technology for Big Data, which allows for the search and processing of large datasets. As our datasets grow in size and the need to integrate with large non spatial data, you will see more Spark sessions.
As far as those technologies that maybe withering is Geoserver. While it has provided a sturdy platform to push spatial data to the web, with the rise of the Serverless technology geoserver may begin to be utilized less.
This should be an amazing conference. If you are going, I’m teaching the Spatial SQL for Rookies Workshop, or just find me and say hi. I might be overloaded with stickers and need to give you some.
Next up, plowing through the ESRI UC schedule (The website doesn’t lend itself for quick keyword search) and getting that analysis up, and then fusing everything together.
I might have to do a full blog entry on Bias. How I’m dealing with Bias in the data, Bias in the conference selection process as well as my own personal Bias.
After writing my entry on being a “Full Stack Single Dad”, the good folks over at the GEOINT Symposium reached out to me and offered to assist me with finding care for my daughter if I was planning on attending their conference. I unfortunately had to decline their offer due to, well the kid being excited about lacrosse camp. I wanted to thank them publicly for being awesome.