If you’ve always wondered how this whole blockchain thing works, but didn’t dare to ask: Here’s an excellent high-level introduction that explains the basic principles.
GeoNotebook is an application that provides client/server environment with interactive visualization and analysis capabilities using Jupyter, GeoJS and other open source tools.
I use Jupyter notebooks all the time when I write Python code, so I definitely need to give GeoNotebook a shot.
- Carsten Keßler (2017) Extracting Central Places from the Link Structure in Wikipedia. Transactions in GIS 21(3):488–502.
Abstract: Explicit information about places is captured in an increasing number of geospatial datasets. This article presents evidence that relationships between places can also be captured implicitly. It demonstrates that the hierarchy of central places in Germany is reflected in the link structure of the German language edition of Wikipedia. The official upper and middle centers declared, based on German spatial laws, are used as a reference dataset. The characteristics of the link structure around their Wikipedia pages, which link to each other or mention each other, and how often, are used to develop a bottom-up method for extracting central places from Wikipedia. The method relies solely on the structure and number of links and mentions between the corresponding Wikipedia pages; no spatial information is used in the extraction process. The output of this method shows significant overlap with the official central place structure, especially for the upper centers. The results indicate that real-world relationships are in fact reflected in the link structure on the web in the case of Wikipedia.
While we’re at it: IJGIS has also published a brief book review online that I wrote about Glen Hart and Catherine Dolbear’s Linked data: a geographic perspective.
The results of our our evaluation of the RG Score were rather discouraging: while there are some innovative ideas in the way ResearchGate approached the measure, we also found that the RG Score ignores a number of fundamental bibliometric guidelines and that ResearchGate makes basic mistakes in the way the score is calculated. We deem these shortcomings to be so problematic that the RG Score should not be considered as a measure of scientific reputation in its current form.
Interesting read about reverse engineering the blackbox ResearchGate score. I have considered that score useless for a long time and think about closing my account every time they send me one of those annoying emails. But unfortunately RG has become so widely used that they drive a considerable number of readers to my papers, so I guess I’ll just keep on putting up with these annoyances. I just hope people don’t start taking that score seriously.
Handy tool if you want to cite a book, but are too lazy to put together the BibTex entry yourself. To comply with the Amazon API that it uses to generate the BibTex code, the entry includes the link to the book on Amazon, but that’s easy enough to remove.
I almost forgot to mention that our group finally has a proper website.
- Carsten Keßler and Peter J. Marcotullio (2017) A Geosimulation for the Future Spatial Distribution of the Global Population. Short paper, AGILE 2017, Wageningen, The Netherlands.
The presentation is scheduled for Wednesday at 12:00PM in the SOCIETAL-1 session in room 4.
This should be a fun workshop:
Knowledge graphs, i.e., making semantically annotated and interlinked raw data available on the Web, has taken information technologies by storm. Today such knowledge graphs power search engines, intelligent personal assistants, and cyber-infrastructures. For instance, the publicly available part of the Semantic Web-based Linked Data cloud contains more than 150 billion triples distributed over 10000 datasets and connected to another by millions of links. Geographic data play a significant role in this cloud and knowledge graphs in general as places function as central nexuses that connect people, events, and physical objects. Consequently, geo-data sources are among the most central and densely interlinked hubs. Beyond their sheer size, the diversity of these data and their inter-linkage are of major value as they enable a more holistic perspective on complex scientific and social questions that cannot be answered from a single domain’s perspective. Hence, knowledge graphs such as those implemented using the Linked Data paradigm bear potential to address many fundamental challenges of geoinformatics.
In this workshop we will discuss various aspects of geo-knowledge graphs ranging from their extraction and construction from unstructured or semi-structured data, issues of data fusion, conflation, and summarization, geo-ontologies, to query paradigms and user interfaces. By focusing explicitly on geo-knowledge graphs in general, we aim at broadening the focus beyond the Semantic Web technology stack and thus also beyond RDF-based Linked Data.
I am currently working a lot with large GeoTIFFs in Python and use Pillow to read them in, then convert them to NumPy arrays for processing. Every now and then, Pillow throws the following error, that I’ve seen on several computers running OS X now:
python TIFFReadDirectory: Warning, Unknown field with tag 42113 (0xa481) encountered. Segmentation fault: 11
Since it always takes me a while to figure out how to fix this, here’s a short note to self, maybe also useful to someone else out there:
- Uninstall Pillow:
- Install dependencies for building Pillow from source:
- Download Pillow source from PyPI
- Unpack and change into the folder with the source code, then build an install via:
python setup.py install
$ pip uninstall pillow
$ brew install libtiff libjpeg webp little-cms2
This has always fixed the problem for me so far. I don’t know whether building from source rather than simply running
pip install pillow
will also fix this problem on other operating systems, but it’s worth a shot if you hit that error.
The world is awash in bullshit. Politicians are unconstrained by facts. Science is conducted by press release. So-called higher education often rewards bullshit over analytic thought. Startup culture has elevated bullshit to high art. Advertisers wink conspiratorially and invite us to join them in seeing through all the bullshit, then take advantage of our lowered guard to bombard us with second-order bullshit. The majority of administrative activity, whether in private business or the public sphere, often seems to be little more than a sophisticated exercise in the combinatorial reassembly of bullshit.
We’re sick of it. It’s time to do something, and as educators, one constructive thing we know how to do is to teach people. So, the aim of this course is to help students navigate the bullshit-rich modern environment by identifying bullshit, seeing through it, and combatting it with effective analysis and argument.
I would definitely have taken a course that has Harry G. Frankfurt’s On Bullshit as its first reading. Let’s hope they get the university administration to approve it.