Open source data tools

Blender

Blender is a free and open source 3D creation suite which supports the entirety of the 3D pipeline — modeling, rigging, animation, simulation, rendering, compositing and motion tracking, in the context of research data in particular.

Access

The suite is free to download from the Blender website.

Training

ITLC offers:

See also an overview course on 3D modelling, taught by ITLC using SketchUp, Blender and image manipulation software.

Geospatial Analysis online

A free online resource, based on the book Geospatial Analysis: a comprehensive guide (5th Edition, 2015 - de Smith, Goodchild, Longley) introduces concepts, methods and tools, provides many examples using a variety of software tools such as ArcGIS, etc. to clarify the concepts discussed. It aims to be comprehensive (but not necessarily exhaustive) in terms of concepts and techniques, representative and independent in terms of software tools, and above all practical in terms of application and implementation.

KNIME

Knime is an open resource platform for data analysis, a toolbox containing over two thousand modules, hundreds of ready-to-run examples, a comprehensive range of integrated tools, and a choice of advanced algorithms.

Training

Training resources are available on the Knime website.

OpenRefine (formerly Google Refine)

OpenRefine is a tool for working with messy data: cleaning it; transforming it from one format into another; and extending it with web services and external data. Currently Google is not actively supporting this project; project development, documentation and promotion is now fully supported by volunteers.

Training

User documentation is available on the OpenRefine website.

Orange

Orange is an open source machine learning and data visualization for novice and expert. Interactive data analysis workflows with a large toolbox.

Training

Documentation and tutorials.

R

R is an open source, freely available language and environment for statistical computing and graphics. It provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification and clustering. It is a major rival of SPSS and Stata.

Training