Lens supports eight main data visualisation “types.” Each type can display a variety of data in a variety of ways, so understanding when to use which one will help you get the clearest possible view of your data. Below is an overview of each type, when to use it, and the charting styles available within each visualisation type.
Basic
The Basic visualisation type shows a simple aggregation of a single facet for a single metric — in other words, a ranked or grouped breakdown of one thing by one measure. A typical example is “Top 100 Institutions by Scholar Citations.”
Basic visualisations can be presented as any of the following:
Historical
The Historical visualisation type is a date histogram — data binned by a date field on the x-axis — optionally split by a facet, for a single metric. Use it to track how something changes over time, with or without a breakdown by category. Examples include “Top 10 Applicants per Filing Date” (split by facet) or “All Patents per Expiry Date” (no facet).
Historical visualisations can be presented as any of the following:
Nested (X-by-Y)
The Nested, or “x-by-y,” visualisation type allows a nested aggregation of two facets for a single metric. Use it when you want to compare a metric across two categorical dimensions at once — for example, “Top Applicants by Jurisdiction” or “Top Institutions by Country.”
Nested visualisations can be presented as any of the following:
Scatter Plot
The Scatter Plot visualisation type — sometimes called the “patent” or “article” scatter plot — plots individual scholarly works or patents on arbitrary axes. Colour and size can be encoded to any given fields, letting you compare several dimensions of the same dataset at once.
Examples include “Show most cited scholarly works by publication date and number of citations, coloured by Open Access status,” or “Show most cited patents by filing date and number of patent citations, coloured by Applicant.”
The Scatter Plot visualisation type is available as:
Histogram
The Histogram visualisation type takes a given facet representing a count and bins it into arbitrary bucket sizes. Use it to understand the distribution of a value across your dataset, rather than to compare it against a date or another facet.
The Histogram visualisation type is available as:
Top Hits
The Top Hits visualisation type displays a short, specifically sorted list of patents or scholarly works. Use it to surface individual standout records rather than aggregate trends — for example, “Top Cited Patent” or “Most Recently Published Scholarly Work.”
The Top Hits visualisation type is available as:
Multi Date Histogram
The Multi Date Histogram is similar to a standard date histogram (see Historical, above), but instead of each series representing a sub-aggregation of a facet, each series represents a different date field. This lets you display more than one date-based event — for example, publication date and filing date — on the same timeline.
The Multi Date Histogram visualisation type is available as:
Metrics
A Metric is a single, standard measure of one specific piece of data, displayed on its own rather than broken down by facet or date. Examples include the sum of patent citations or the average author count.
The Metrics visualisation type is available as:
Choosing the right type
As a quick rule of thumb use:
- Basic to rank or group by one facet,
- Historical or Multi Date Histogram to track change over time,
- Nested to compare across two facets at once,
- Histogram to see the distribution of a count,
- Scatter Plot to compare individual records across two or more encoded dimensions,
- Top Hits to spotlight specific standout records, and
- Metrics for a single summary number.