Physics

Background

Physics is the natural science concerned with understanding the fundamental properties of matter, energy, space, and time. It spans an enormous range of scales — from subatomic particles studied in high-energy colliders to the large-scale structure of the universe mapped by telescopes — and its methods underpin nearly every other natural science and engineering discipline. Modern physics is broadly organized around several major domains: classical mechanics, thermodynamics, electromagnetism, quantum mechanics, and relativity, alongside active research frontiers such as particle physics, condensed matter physics, and cosmology.

A distinctive feature of contemporary physics research is the scale and complexity of its experimental infrastructure. Facilities such as CERN's Large Hadron Collider (LHC), gravitational wave observatories like LIGO and Virgo, and neutrino detectors buried deep underground generate enormous volumes of data that are increasingly made available to the public. The open data movement in physics is well established: CERN, for example, began releasing LHC collision data through its Open Data Portal in 2014, with the explicit goal of enabling education and independent research (Lassila-Perini et al., 2022). Beyond particle physics, open data is available in areas including seismology, materials science, nuclear physics, and space physics, giving students and researchers access to real experimental datasets that were previously available only to specialists.

References:

Lassila-Perini, K., Šimko, T., Åkesson, T. P. A., Cranmer, K., & Dallmeier-Tiessen, S. (2022). Open data from the large hadron collider. Annual Review of Nuclear and Particle Science, 72, 80–106. https://doi.org/10.1146/annurev-nucl-111119-013650

Data Sources

Particle Physics

1. CERN Open Data Portal https://opendata.cern.ch/

• Official open data repository from CERN, the European Organization for Nuclear Research

• Contains data from the CMS and ATLAS detectors at the Large Hadron Collider (LHC), including proton-proton collision data

• Includes educational datasets specifically designed for students and teachers

• Tools and virtual machine environments provided for working with the data

• Good for: Understanding particle collisions, studying fundamental particles, educational particle physics research

2. CMS Public Data (via CERN Open Data) https://opendata.cern.ch/search?experiment=CMS

• Data from the Compact Muon Solenoid (CMS) experiment at CERN

• Includes simplified datasets designed for educational use (e.g., dimuon mass spectra, which can be used to identify known particles like the Z boson)

• Accompanying tutorials and Jupyter notebooks available

• Good for: Hands-on particle physics analysis; identifying resonances in collision data; histogram analysis of particle masses

3. Particle Data Group – Review of Particle Physics https://pdg.lbl.gov/

• Authoritative summary of known properties of all confirmed subatomic particles

• Data tables on particle masses, lifetimes, decay modes, and interaction cross-sections

• Freely downloadable in multiple formats

• Good for: Reference data on particle properties; comparing theoretical predictions to experimental measurements

Gravitational Waves

4. LIGO Open Science Center (GWOSC) https://gwosc.org/

• Open data from the LIGO (Laser Interferometer Gravitational-Wave Observatory) and Virgo detectors

• Includes strain data from all confirmed gravitational wave events, including the first detection (GW150914) from two merging black holes

• Tutorials and Jupyter notebooks provided for data analysis

• Good for: Studying gravitational wave signals from black hole and neutron star mergers; signal processing; introduction to time-series analysis

Nuclear and Atomic Physics

5. National Nuclear Data Center (NNDC) https://www.nndc.bnl.gov/

• Operated by Brookhaven National Laboratory

• Comprehensive data on nuclear structure, decay, and reactions for all known isotopes

• Includes half-lives, decay modes, energy levels, and reaction cross-sections

• Good for: Research on radioactive decay, nuclear stability, isotope properties

6. NIST Atomic Spectra Database https://physics.nist.gov/PhysRefData/ASD/lines_form.html

• Data on spectral lines and energy levels of atoms and ions

• Maintained by the US National Institute of Standards and Technology

• Used in fields from astrophysics to analytical chemistry

• Good for: Studying atomic structure; identifying elements from spectral data; astrophysical spectroscopy

7. NIST Physical Measurement Laboratory – Fundamental Constants https://physics.nist.gov/cuu/Constants/

• Official values of fundamental physical constants (speed of light, Planck's constant, electron mass, etc.)

• Updated following each review by the Committee on Data of the International Science Council (CODATA)

• Good for: Reference values for calculations; studying how measurement precision of fundamental constants has improved over time

Condensed Matter and Materials

8. Materials Project https://next-gen.materialsproject.org/

• Open database of the properties of tens of thousands of known and predicted materials

• Data calculated using quantum mechanical simulations (density functional theory)

• Properties include crystal structure, band gap, magnetic properties, and stability

• Good for: Comparing material properties; research on semiconductors, batteries, or superconductors

9. ICSD – Inorganic Crystal Structure Database (free subset) https://icsd.fiz-karlsruhe.de/

• Database of inorganic crystal structures; a limited free subset is accessible

• Good for: Researching the atomic structure of materials

10. AFLOW – Automatic FLOW for Materials Discovery https://www.aflowlib.org/

• Large open database of computed material properties from high-throughput quantum mechanical calculations

• Covers over 3 million material compounds

• Good for: Large-scale comparisons of material properties; data-driven materials science research

Space Physics and Geophysics

11. NASA Space Physics Data Facility (SPDF) https://spdf.gsfc.nasa.gov/

• Archive of data from NASA missions studying Earth's magnetosphere, solar wind, and space plasma

• Includes data from missions such as Van Allen Probes, Wind, and ACE

• Good for: Studying solar-terrestrial interactions, space weather, and the physics of the near-Earth environment

12. IRIS – Incorporated Research Institutions for Seismology https://www.iris.edu/hq/

• Open archive of seismic waveform data from global seismograph networks

• Data from thousands of stations worldwide, accessible via web tools

• Good for: Studying seismic wave propagation, Earth's interior structure, and earthquake physics (complements the Earthquakes data page)

13. NOAA National Centers for Environmental Information – Geomagnetic Datahttps://www.ngdc.noaa.gov/geomag/

• Historical and real-time data on Earth's magnetic field

• Includes measurements from ground stations and satellite missions

• Good for: Studying geomagnetic variation over time, magnetic pole movement, and space weather effects on Earth

Historical and Educational Physics Data

14. The Feynman Lectures on Physics – Online Edition https://www.feynmanlectures.caltech.edu/

• Freely available text of Richard Feynman's landmark physics lectures (Caltech, 1961–63)

• Not a dataset, but a foundational open educational resource for understanding physics concepts

• Good for: Background reading on physical principles underlying any of the datasets above

15. PhysNet / European Physical Society Data Resources https://www.eps.org/?page=links_physnet

• Directory of physics data resources and archives across Europe

• Good for: Finding specialized physics datasets not covered by the major archives above

Example Research Questions

Some of these questions require background reading in physics before the data can be meaningfully interpreted. Combining physics data with historical, policy, or materials science context can also open up interesting research directions.

• What does the dimuon mass spectrum from LHC collision data reveal, and can known particles (such as the Z boson) be identified from the data?

• How have measurements of fundamental physical constants (such as the speed of light or Planck's constant) become more precise over time?

• How do the electronic or structural properties of materials in the Materials Project database vary by element or compound type?

• What patterns can be found in the properties of known subatomic particles (mass, charge, lifetime), and how do these reflect the structure of the Standard Model?

• How does gravitational wave signal data from a confirmed black hole merger event compare to the theoretical predictions made before detection?

• How has the precision of measurements of fundamental constants improved since systematic international measurement began?

• What is the relationship between a material's crystal structure and its predicted electronic properties (e.g., whether it is a conductor, semiconductor, or insulator)?

Tips for Using Physics Data

Getting Started:

1. For particle physics, start with CERN's educational CMS datasets — they come with tutorials and require no specialist software beyond a web browser or basic Python

2. For materials science, the Materials Project has an excellent web interface and does not require programming to explore

3. LIGO's open data comes with Jupyter notebook tutorials that walk through signal analysis step by step

4. Physics data is often more technical than social science or environmental data — read the documentation carefully before downloading

Understanding the Data:

• Invariant mass: In particle physics, a quantity calculated from collision products that identifies which particle was produced; peaks in the invariant mass spectrum correspond to known particles

• Strain: In gravitational wave data, the fractional change in the length of the detector arms caused by a passing gravitational wave

• Half-life: The time for half of a sample of a radioactive isotope to decay; a key property in nuclear data

• Band gap: In materials science, the energy gap between the valence and conduction bands of a material; determines whether a material is a conductor, semiconductor, or insulator

• Cross-section: In nuclear and particle physics, a measure of the probability of a particular interaction occurring

Data Quality Considerations:

• Particle physics data from CERN is extremely high quality but requires understanding of how detectors work and their limitations

• Materials Project data is computed (not measured), so values are theoretical predictions that may differ from experimental results

• Seismic waveform data quality varies by station location, instrument type, and recording conditions

• Historical measurements of physical constants reflect the technology of their time and have large uncertainties compared to modern values

Making Comparisons:

• When comparing particle properties, ensure you are using consistent units (MeV/c² for mass, seconds for lifetime, etc.)

• Materials property comparisons should specify whether data is computed or experimentally measured

• Time-series comparisons of constants or measurements should account for changes in measurement methodology

Combining Datasets:

• CMS dimuon data + Particle Data Group reference values (to identify peaks)

• Materials Project properties + element periodic table data (to study trends)

• NIST fundamental constants historical values + measurement technology timelines

• Seismic waveform data + earthquake catalog data (from USGS or NOAA)

Useful Additional Data Sources

When studying physics topics, you may also want to use:

• NASA Astrophysics Data System (ADS): Literature database for physics and astronomy research (https://ui.adsabs.harvard.edu/)

• Zenodo: General open research data repository used by physicists to share experimental datasets (https://zenodo.org/)

• PhysicsForums and Stack Exchange – Physics: Community Q&A useful for interpreting unfamiliar data (https://physics.stackexchange.com/)

• ROOT (CERN analysis framework): Software used to analyze CERN data; tutorials available on the CERN Open Data Portal (https://root.cern/)

• Astropy: Python library useful for working with space physics and astronomical physics data (https://www.astropy.org/)

Questions? Need Help?

• The CERN Open Data Portal's educational CMS datasets are the most accessible entry point for particle physics

• For materials science, the Materials Project web interface requires no programming and is a good starting point

• LIGO's tutorials are among the best-documented open physics datasets for students

• Physics data often requires more domain knowledge to interpret than other data types — budget extra time for reading documentation and background material

• The Particle Data Group is the authoritative reference for particle properties and is freely available online

• Don't hesitate to combine physics data with historical or policy context — for example, studying how international collaboration shaped particle physics, or how materials data informs energy technology

Site created by Nigel Robb and maintained by the ALESS Program