ChronoZoom Data_World War I

ChronoZoom Data_World War I


API Documentation

ChronoZoom is an open source project that enables students, teachers and researchers to explore, create, and tell stories with timelines that span any period of time– from a single day to the beginning of the universe, 13.8 billion years ago.

In addition to the core data model of Timelines. Exhibits and ContentItems, ChronoZoom has a facility for adding RDF Triple’s which is used to capture ‘causality’ connections between objects (this is called out in the Triples.xlsx and TripleObjects.xlsx files). An example of causality is the ‘archduke Ferdinand assassination’ which lead to WWI. There is currently no user interface for adding such Triple’s in ChronoZoom, but a number of Triple’s have been administratively added to the WWI timeline for exploration.” You can also look at an example of how this is used in this JSFiddle:

Background Info:
When you visit ChronoZoom you will see the sample ‘Big History’ dataset. Students at UC Berkeley created this sample dataset where the project was originally conceived. The sample dataset also contains timelines created by students at University of Washington, University of Southern California, Brown University, Microsoft Research and the NAMES Foundation among others.

As of October, 2013 the ChronoZoom production database at has the following data:
• 1451 Timelines
• 1114 Exhibits
• 2603 Artifacts
For a total of 5168 objects.

The ChronoZoom test database (where the contest data is located) at has the following data:
• 198978 Timelines,
• 10203 Exhibits
• 34025 Artifacts
For a total of 243206 objects.

ChronoZoom does not store media itself, instead linking to the original media source on the web. Linked data can include videos, high-definition imagery, PDFs and other resources. The linked data includes basic bibliographic metadata such as source URL, author and descriptive text left by the timeline or event author. The default dataset also contains six climate data sets, spanning from the last 250 years of instrumental weather records back to 540 million years ago based on fossil records. Chart data can be visualized next to any timeline or event, and is stored using a simple CSV format.

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Alexandra Pappas's picture

@anditriendl – Thanks for your questions! Answers below.

Causality/Affinity: You may use other data in addition to what was provided. Make sure that all data used is properly attributed.

Styling: You may style the visualization as you like. It does not have to be WWI themed. It may complement the existing ChronoZoom design or can be an independent design.

Scope: The jsfiddle is only a suggestion of what may be done. If there is another way you would like to represent the data, which may or may not include a timeline, you can and should explore that.

anditriendl's picture

I would like to participate in the WWI/Chronozoom challenges and after studying the task and data I have a couple of questions:

Causality / Affinity: The task description states that the WWI entry should address causality and/or affinity. Causality is pretty clear – a couple of causal connections have been entered into the data as triples. However,there seems to be no explicit affinity tagging in the data set, nor any category tagging such as the mentioned “economic, cultural, military, religious, or other types”. In order to create an interactive HTML5 visualisation that shows these relations, the information would have to be in the data. So the question is: should the challenge entry use only the data provided? Or would it be a good idea to propose an extesion of the current data model?

Styling: Should the interactive visualisation for the WWI entry be visually WWI themed, i.e. should this visualisation be created for exclusive use with WWI data? Or should it sport a general visual approach so that it can be used for other timelines as well?

Scope: The WWI demonstration jsfiddle just shows one timeline. Should the visualisation should also be able to show the one timeline, right?



drizzt's picture

Thanks.'s picture

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