I am very happy to announce that our new article "Enhancing Location-related Hydrogeological Knowledge" has been published in the ISPRS International Jounral of Geo-information.
Kmoch, A.; Uuemaa, E.; Klug, H.; Cameron, S.G. (2018) Enhancing Location-Related Hydrogeological Knowledge. ISPRS Int. J. Geo-Inf. , 7, 132, http://www.mdpi.com/2220-9964/7/4/132
In a joint study by the University of Tartu (Estonia), the Institute of Geological and Nuclear Sciences (New Zealand) and the University of Salzburg (Austria) more than 5,800 scientific articles from three environmental research journals were digitised and analysed. In addition, a geographical search method was developed to identify the location of a studied area.
We use Georeferencing of scientific journal articles and text-mining in order to provide spatial search capabilities for environmental research. Journal articles are made discoverable through spatial queries. We propose that journal publishers should provide these capabilities on their platforms. This would allow everyone to search for journal articles for their desired regions of interest and it would really well complement existing search functionalities with keywords etc.
The press release from Tartu University explains really nicely how our results enable geographic search for scientific papers through text mining and geocoding; and how to better find environmental research articles via location.
http://researchinestonia.eu/2018/04/17/enabling-geographic-search-for-scientific-papers-through-text-mining-and-geocoding-how-to-better-find-environmental-research-articles-via-location/
Estonian version of the press release: https://novaator.err.ee/821096/kuidas-otsida-teadustoid-geograafilise-piirkonna-jargi
(This article belongs to the Special Issue Place-Based Research in GIScience and Geoinformatics)
MDPI OpenAccess: http://www.mdpi.com/2220-9964/7/4/132
ResearchGate: https://www.researchgate.net/publication/323990934_Enhancing_Location-Related_Hydrogeological_Knowledge
Showing posts with label Data Science. Show all posts
Showing posts with label Data Science. Show all posts
Wednesday, 18 April 2018
Wednesday, 7 February 2018
Info Session for MSc programme in Geoinformatics for Urbanised Society
Today we broadcast a webinar info session about the new MSc programme in Geoinformatics for Urbanised Society at the University of Tartu.
One of the recurring core topics in this new MSc curriculum is Data and GIS use in Urban Planning.
Until just a decade ago spatial planning and analytics projects had problems with getting enough data. But nowadays there is so much data available, that it is increasingly hard to make sense of it – because of the 3 V’s of big data - volume, variety, velocity. The open data movement, government agencies, research institutes and citizen scientists alike make more and more data available publicly, mobile phones, sensor networks and satellites generate a multitude of datasets every day
In order solve the Interdisciplinary challenges of urban planning we want to empower you with skills and knowledge to analyse, visualise and understand processes and data. For that we teach the Full cycle of spatial data management, from the various methods of data acquisition, followed by efficient and practical processing techniques, to subsequent meaningful analysis and visualisation; in order to consequently make successful planning decisions for a sustainable future.
So what does it mean to study Geoinformatics for Urbanised Society with us in Tartu?
You will learn how to combine geography and IT in the age of BIG data. This is essentially what we believe modern Geoinformatics is representing. Mastering Geoinformatics will provide you with tools to analyse social and natural processes in space for interdisciplinary decision- and policy-making.
Watch the whole recorded session for more info:
Links:
One of the recurring core topics in this new MSc curriculum is Data and GIS use in Urban Planning.
Until just a decade ago spatial planning and analytics projects had problems with getting enough data. But nowadays there is so much data available, that it is increasingly hard to make sense of it – because of the 3 V’s of big data - volume, variety, velocity. The open data movement, government agencies, research institutes and citizen scientists alike make more and more data available publicly, mobile phones, sensor networks and satellites generate a multitude of datasets every day
In order solve the Interdisciplinary challenges of urban planning we want to empower you with skills and knowledge to analyse, visualise and understand processes and data. For that we teach the Full cycle of spatial data management, from the various methods of data acquisition, followed by efficient and practical processing techniques, to subsequent meaningful analysis and visualisation; in order to consequently make successful planning decisions for a sustainable future.
You will learn how to combine geography and IT in the age of BIG data. This is essentially what we believe modern Geoinformatics is representing. Mastering Geoinformatics will provide you with tools to analyse social and natural processes in space for interdisciplinary decision- and policy-making.
Links:
Tuesday, 17 October 2017
A Python Pandas Coding Meetup
On October, 12th, I organised a local meetup event at the Department of Geography. We had around 15 attendees, both from Tartu industry and university students.
In this meetup we played with the Jupyter Notebook (http://jupyter.org/) and did some data wrangling with Python, Pandas (http://pandas.pydata.org/) and co., some data analysis and visualisation.
In this meetup we played with the Jupyter Notebook (http://jupyter.org/) and did some data wrangling with Python, Pandas (http://pandas.pydata.org/) and co., some data analysis and visualisation.
I presented on how we can use Miniconda, an encapsulated versatile virtual python environment installer, that works under the hood of the big Anaconda python distribution. Miniconda is basically a mini version of Anaconda that includes only the conda package manager and its dependencies. We used a Python version 3.4 because some of the libraries/tools we wanted to work with supposedly only are supported up to Python 3.4. Here it becomes obvious how practical virtual environments can be. They help you to keep various Python versions around without messing up your system.
After we had set-up our local Python working environment, I introduced the Jupyter Notebook. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
I prepared a variety of resources that we worked through in the meetup. I shared the collated tutorials and course materials on my GitHub account, The repository contains a curated collection of Jupyter Notebooks of introductory materials about programming in Python in general, the Pandas data manipulation and visualisation toolkit, and the Geopandas geospatial library.
This repository aims at different degrees of experience with the Python programming language and Python data manipultation and visualisation libraries. Each folder contains a README.md (for the the online repository) and README.notebook.md (readme as readable Notebook) file that list the contents and some details for each of the 3 big modules here:
- 01 - Introduction to Python and the Jupyter Notebook
- 02 - Introduction to the Pandas library
- 03 - Introduction to the Geopandas library
In order to get started, download the full Meetup-Repositiry from https://github.com/allixender/meetup-notes/archive/master.zip and extract it to a LOCAL folder. Go back into the console/commandline prompt and change into that folder. There you should then start the Jupyter notebook.
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