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Category: Data visualisations

Data visualisations are graphical representations of scientific data, using tools like axes, scales, and colour gradients to quantify and display information. Through charts, graphs, and plots, they help users spot patterns, trends, and insights, making complex data easier to interpret, understand, and communicate effectively.

Discovery of the Periodic Table of Elements

Periodic Table of Elements showing the years of discovery of each element.

Years of discovery of each element in the Periodic Table of Elements including atomic numbers, element symbols and names, atomic mass, and period and group. Lanthanoids and Actinoids are shown. Accessibly coloured are the year of discovery or, alternatively, different element flavours, phases of individual elements at room temperature, element numbers, and year of discovery. See the original s-ink periodic table of elements for a more detailed version.

Data are based on the NIST Atomic Spectra Database and the Royal Society of Chemistry’s periodic table, which compile experimentally verified and theoretically predicted ground-state configurations.

The Scientific colour map ‘lipari‘ is used to represent individual groups of elements to all, including colour-blind, readers.

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Simple Periodic Table of Elements

Simple Periodic Table of Elements including atomic numbers, element symbols and names, and period and group.

A simple version of the colour-vision deficiency friendly Periodic Table of Elements including atomic numbers, element symbols and names, and period and group. Lanthanoids and Actinoids are shown. Coloured are the phases of individual elements at room temperature or, alternatively, different element flavours, element numbers, and year of discovery. See the original s-ink periodic table of elements for a more detailed version.

Data are based on the NIST Atomic Spectra Database and the Royal Society of Chemistry’s periodic table, which compile experimentally verified and theoretically predicted ground-state configurations.

The typeface ‘Elle‘ and the Scientific colour map ‘hawaii‘ are used to represent individual groups of elements to all, including colour-blind, readers.

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Selam Moonlet Formation

Simulated formation of Dinkinesh’s moon Selam, identified as the first confirmed “contact binary” moon.


Animated model of the formation of the asteroid Dinkinesh’s moon Selam. Dinkinesh’s tiny moon was likely built from multiple low-speed collisions between small moonlets, making it the first confirmed “contact binary” moon. The current understanding is that Selam formed not from two, but at least four separate bodies. This simulation shows the Moonlet merger forming the characteristic ridge on the inner lobe of Selam (Selam A), which matches the observations obtained from NASA’s Lucy mission.

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Consistency of of Hubble Constant Measurements

The measurement of the Hubble Constant, highlighting variations from different methods and the consistency of these measurements across galaxies with differing redshifts.

The consistency of different methods to measure the Hubble Constant. Shown are differences in the measured Hubble constant for galaxies at various redshifts, compared to the combined best estimate (“everything” solution). Each panel shows results from one measurement method, where points represent individual galaxies, with error bars showing the expected variation within that method. The shaded bars on the right indicate the average value and overall spread for each method. As such, the figure shows how consistently different techniques measure the expansion rate of the Universe.


Data are drawn from published Hubble-flow measurements compiled in the Hubble Constant “everything” solution, including distances derived from Cepheids, TRGB, SBF, and Type Ia supernovae, as assembled by the H₀DN Collaboration (2025).

The graphic was developed within the framework of the ISSI Workshop ‘What’s under the H0od? Towards Consensus on the local value of the Hubble Constant‘ at the International Space Science Institute (ISSI) in Bern, Switzerland.

The Scientific colour map ‘batlow‘ is used to represent data accurately and to all readers.

  • Creator: Fabio Crameri
  • This version: 20.10.2025
  • License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
  • Specific citation: This graphic by Fabio Crameri (ISSI Bern) from H₀DN Collaboration (2025) is available via the open-access s-ink.org repository.
  • Related reference:
    H₀DN Collaboration, Casertano, S., Anand, G., Anderson, R. I., et al. (2025). The Local Distance Network: A community consensus report on the measurement of the Hubble constant at 1% precision. arXiv preprint arXiv:2510.23823. https://doi.org/10.48550/arXiv.2510.23823 
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Consistency of Distance Network Measurements

The consistency of distance network measurements used in calibrating the Hubble constant, showing how various methods align with each other.

Consistency of Distance Network Measurements for Hubble Constant Calibration. Shown are residuals (differences) between measured host galaxy distances and the values from the full distance network. Each panel groups measurements made with the same method, reference, and research team. Points show individual distance estimates with their uncertainties, and shaded bands show the shared uncertainty for each group. The figure illustrates how well different measurement methods agree within the overall distance ladder, or now termed more fittingly distance network, used to determine the Hubble constant.

The data was taken from various distance-ladder studies using different methods. These methods include Cepheids, Tip of the Red Giant Branch (TRGB), Surface Brightness Fluctuations (SBF), with each measurement retaining its original calibration (anchor), such as to the Large Magellanic Cloud (LMC), NGC 4258 maser distance, or Milky Way parallaxes. The “Baseline solution” refers to the combined, self-consistent solution obtained by linking all these methods into a single global network.

The illustration was developed within the framework of the ISSI Workshop ‘What’s under the H0od? Towards Consensus on the local value of the Hubble Constant‘ at the International Space Science Institute (ISSI) in Bern, Switzerland.

The Scientific colour map ‘batlow‘ is used to represent data accurately and to all readers.

  • Creator: Fabio Crameri
  • This version: 20.10.2025
  • License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
  • Specific citation: This graphic by Fabio Crameri (ISSI Bern) from H₀DN Collaboration (2025) is available via the open-access s-ink.org repository.
  • Related reference:
    H₀DN Collaboration, Casertano, S., Anand, G., Anderson, R. I., et al. (2025). The Local Distance Network: A community consensus report on the measurement of the Hubble constant at 1% precision. arXiv preprint arXiv:2510.23823. https://doi.org/10.48550/arXiv.2510.23823 
  • ‘Baseline’ and ‘all’ dataset versions
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  • Readable in black&white
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Known Exoplanets

The collection of known Exoplanets represented based on their date of detection and their relative size to scale.

The collection of known Exoplanets represented based on their date of detection and their relative size to scale. Exoplanets are planets outside our solar system with known radii. The largest planetary bodies are annotated with their names. Note that there is some uncertainty in classifying and measuring “exoplanets”. The current figure includes objects (such as some Brown Dwarfs) that do not necessarily fulfil the true definition of an “exoplanet”. This definition would limit the collection to planetary bodies with true masses below the limiting mass for thermonuclear fusion of deuterium, which is currently calculated to be 13 Jupiter masses for objects of solar metallicity, that orbit stars or stellar remnants are (see e.g., https://www.iau.org/static/resolutions/IAU2003_WGESP.pdf for a discussion thereof).

The first confirmed discovery of an exoplanet occurred in 1992 by Aleksander Wolszczan and Dale Frail, who detected two Earth-mass planets orbiting the pulsar PSR B1257+12. These were the first exoplanets ever confirmed, but because they orbit a neutron star rather than a Sun-like star, they were a very unusual find.

First discovery 30 years ago

In 1995, Swiss astronomers Michel Mayor and Didier Queloz discovered the first confirmed exoplanet around a main-sequence star (a more Sun-like star), named 51 Pegasi b and shown in the very centre of the graphic. This discovery marked a major milestone and is often considered the true beginning of modern exoplanet astronomy. Mayor and Queloz were awarded the 2019 Nobel Prize in Physics for this work.

The Scientific colour map ‘devon‘ is used to represent data accurately and to all readers.

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Biomass on Earth

The total biomass on the Earth, the combined weight of all living organisms.



The total biomass on the Earth, the combined weight of all living organisms, is estimated at around 550 Billion tons of carbon (Gt C). This mass is primarily made up of plants, particularly land plants such as trees, which account for roughly 450 Gt C. Bacteria and fungi also contribute significantly, together with about 80 Gt C. Animals, including humans, represent a smaller fraction, around 2 Gt C. Understanding the distribution and composition of biomass is crucial for studying ecological processes, biodiversity, and the impact of human activities on the environment. The data are from Bar-On et al. (2018) and the Scientific colour map ‘navia‘ is used to represent data accurately and to all readers.

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Plate tectonic Earth map

Visually accessible and scientifically accurate global map of key plate tectonics characteristics on the Earth.

Visually accessible and scientifically accurate global map of key plate tectonics characteristics on the Earth. Superposed on the Earth’s surface topography (from s-ink.org/surface-topography-relief) are the seafloor age (from s-ink.org/oceanic-plate-age), plate boundaries (from s-ink.org/subduction-zones-map) and tectonic plate names (from s-ink.org/tectonic-plates-simple), active volcanoes (from s-ink.org/global-volcano-distribution), largest earthquakes (from s-ink.org/historic-earthquake-distribution), major rivers, and the outlines of the world map. 

Data sets shown are from Amante and Eakins (2009), Müller et al. (1997), Argus et al. (2011), Bird (2003), Deep Sea Drilling Project (1989), NCEI Volcano Location Database, and Hayes (2018). The Scientific colour map ‘lipari‘ is used to represent data accurately and to all readers.

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Magnetic Seafloor Anomalies

Global map of magnetic anomalies imprinted onto the seafloor of the Earth in form of characteristic stripes and other patterns.


Global map of magnetic anomalies imprinted onto the seafloor of the Earth in form of characteristic magnetic stripes and other patterns. The magnetic anomalies are not only observable on the seafloor, but also provide insight into the subsurface structure and composition of the Earth’s crust. Anomalies trending parallel to the isochrons (lines of equal plate age) in the oceans reveal the temporal growth of oceanic plate and crust: seafloor spreading.

Ever so often the Earth’s magnetic field flips its polarity in an occurrence called a geomagnetic reversal. These reversals throughout Earth’s history are recorded in solidifying rocks, such as in the ones making up the growing oceanic crust at mid-oceanic ridges. The successive bands of ocean floor representing alternating magnetic polarity parallel with mid-ocean ridges was important evidence for seafloor spreading, the concept central to the acceptance of the early theory of plate tectonics.

The data plotted is from the global Earth Magnetic Anomaly Grid (EMAG2) and was compiled from satellite, ship and airborne magnetic measurements.

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