
We are pleased to announce the first public beta of Weaving History!
Weaving History lets you create ‘factlets‘, containing basic information about historical events, persons, and so on, which you can string together to create historical ‘threads‘. These threads can then be visually represented on maps and timelines.
There’s a function that lets you automatically pull information from Wikipedia, including images, dates, locations and brief descriptions.
For example, you can see a thread of the Napoleonic wars showing the dates and locations of major battles, or a thread showing Shakespeare’s works.

Each factlet can be used in a multiplicity of different threads. For example, a factlet giving the birth and death dates for Leonardo Da Vinci might be included in a thread on renaissance painting, a thread on the history of famous inventors and a thread on the history of anatomy.
The project is very much a work in progress – and we’d love to hear what you think on our discuss list or as a comment below!
If you’d like to try it out, you can get stuck in and create a new factlet or thread! Also if you’d like to contribute – we’d warmly welcome help with developing the graphical interface, the code, or with curating the site!
Related posts:
- British History Online: Why the Restrictions? British History Online is a site created and run by Institute for Historical Research (part of the University of London I believe) and the History of Parliament Trust and located at: http://www.british-history.ac.uk/ (note the ‘ac.uk’ domain name signifying the official...
- Open Data Commons Release v1.0 Release Candidate for Open Database License Open Data Commons, a project we help host, has put out a v1.0 “Release Candidate” for their Open Database License (ODbL). As it states in the announcement: This updated version of the license incorporates a whole set of changes arising...
- Some Agricultural History via Open Economics One of the active Open Knowledge Foundation projects is Open Economics. A substantial part of that effort ends up being data acquisition and ‘cleaning’: getting hold of economic data, parsing it into (computer) usable form and adding it to the...

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