2020

GeoSPARQL queries on OSM Data in GraphDB

Or, Querying geospatial data with SPARQL Part 2

Over a year ago, in Querying geospatial data with SPARQL: Part 1, I described my dream of pulling geospatial data down from Open Street Map, loading it into a local triplestore, and then querying it with queries that conformed to the GeoSPARQL standard. At the time, I tried several triplestores and data sources and never quite got there. When I tried it recently with Ontotext’s free version of GraphDB, it all turned out to be quite easy.

Generating MODS XML from RDF with Go templates

Using a built-in Go(lang) feature to drive an RDF application.

I had heard that Go (also known as “golang”) was an increasingly popular newish programming language before I migrated my blog from being generated by handmade XSLT scripts on snee.com to using the Hugo platform to generate it on bobdc.com. Hugo is written in Go, which was invented at Google (get it?) by three people, two of whom had contributed to the development of C, Unix, and important related technology at Bell Labs. Go provides an excellent basis for a website generation…

Converting CSV to RDF with Tarql

Quick and easy and, if you like, streaming.

I have seen several tools for converting spreadsheets to RDF over the years. They typically try to cover so many different cases that learning how to use them has taken more effort than just writing a short perl script that uses the split() command, so that’s what I usually ended up doing. (Several years ago I did come up with another way that was more of a cute trick with Turtle syntax.)

SPARQL in a Jupyter Notebook

For real this time.

A few years ago I wrote a blog post titled SPARQL in a Jupyter (a.k.a. IPython) notebook: With just a bit of Python to frame it all. It described how Jupyter notebooks, which have become increasingly popular in the data science world, are an excellent way to share executable code and the results and documentation of that code. Not only do these notebooks make it easy to package all of this in a very presentable way; they also make it easy for your reader to tweak the code in a local copy of your…

Last month in Populating a Schema.org dataset from Wikidata I talked about pulling data out of Wikidata and using it to create Schema.org triples, and I hinted about the possibility of updating Wikidata data directly. The SPARQL fun of this is to then perform queries against Wikidata and to see your data edits reflected within a few minutes. I was pleasantly surprised at how quickly edits showed up in query results, so I thought I would demo it with a little video.