Visual and numerical data in timelines

This is a meta page about timelines. View all meta pages about timelines

We include a variety of visual and numerical data in several timelines. Some of this visual and numerical data is standard and included in many timelines. Other visual and numerical data is specific to the topic of the timeline and does not easily generalize.

The selection of visual and numerical data to show for a given timeline depends on a variety of factors, that we plan to articulate more on this page.

Standard visual and numerical data

Information source	Time period	Granularity of data	Existence and relevance to timeline topic
Google Trends	2004 to present	Granularity adjusts to time range selected; finest granularity is hourly	For most topics that are well-defined entities with unambiguous names, Google Trends does a good job as it's possible to pick appropriate search terms or topics. However, in some cases, such as timeline of nonprofit evaluation, the term/topic "nonprofit evaluation" is not a Schelling point for searchers, so the Google Trends in this case are not informative. In other cases, such as timeline of AI safety, there are many variants of the term "AI safety" and so it may be necessary to look at several search terms.
Wikipedia views	July 2015 to present; some pages have data going as far back as December 2007; limited to after the page creation date	Monthly, but underlying data available at daily granularity	For topics that have Wikipedia pages over a long enough time duration, this is relevant.
Google Ngram Viewer	Ever since we started having books	Annual	For topics that have relatively well-defined and unambiguous names that have been in use for a long enough time period, this is useful. For instance, something like malaria. On the other hand, for very new topics, or topics with no standard name, this is not useful.
Google Scholar	Ever since we have recorded publication; often very recent data (last 3-5 years) is incomplete	Annual, but underlying data may have finer granularity	For topics that have relatively well-defined and unambiguous names and that are covered in the scholarly literature, this is useful.