READ ME ======================== General information ======================== Author: Christopher Harrison / James Trayford Contact: christopher.harrison@newcastle.ac.uk / james.trayford@port.ac.uk DOI: To Be Confirmed License: CC-BY Last updated: 10/03/2023 Related article: J. Trayford & C. Harrison, ICAD Proceedings (2023), details to be confirmed after publication. ======================== Introductory information ======================== Files included in the data deposit (include a short description of what data are contained): Each of these video files were produced as example applications of the STRAUSS code (https://github.com/james-trayford/strauss) for the introductory paper on this code, which is to appear in the ICAD conference proceedings 2023. Each file is a movie file containing an audio representation of the data (i.e., a 'sonification') as well as a visual representation of the data. 1. spectrum_realisation_a.mp4 The data for the basis of this comes from a galaxy spectrum (flux density, or brightness, versus wavelength) provided by the Sloan Digital Sky Survey (SDSS; sdss.org). The galaxy has spectra ID: 54139-2582-125. This example focusses on a small region of the spectra from 535nm to 575nm. This can be seen visually in the video file. The sound is generated by STRAUSS, treating each data point as an Event, and representing each data point as a sampled sound of mallets. The pitch of the sound is mapped onto the brightness (i.e., flux density) of the spectrum, such that higher brightness corresponds to a higher pitch. In the video we hear sequentially these data points (lowest wavelengths first). The moving dashed line in the video highlights which data point is being heard at that particular time. 2. spectrum_realisation_b.mp4 The same data as in spectrum_realisation_a.mp4. However, this time the whole spectrum is used (i.e., wavelengths from around 380nm to 920nm) which can be seen to be represented visually in the video file. The sound is generated by STRAUSS, treating the spectrum as an evolving `Object'. The sound is generated using an A5 chord as a carrier signal and then the pitch is mapped to brightness (flux density). The moving dashed line in the video highlights which data is being used to map to the sound at each time. 3. spectrum_realisation_c.mp4 Same as spectrum_realisation_b.mp4, but this time the flux density is mapped to the cut-off frequency of low pass filter applied to a A5 (tonal) carrier in STRAUSS. 4. spectrum_realisation_d.mp4 Same as spectrum_realisation_c.mp4, but this time using white noise as a carrier (textual) in STRAUSS. 5. spectrum_realisation_e.mp4 The same data as in spectrum_realisation_a.mp4. This time the whole spectrum is used for an 'Event' in STRAUSS, using the spectraliser generator. Therefore the entire spectrum is heard at once (non evolving in time). 6. multivariate_realisation_a.mp4 This is a sonification of galaxy data from the EAGLE simulations (https://icc.dur.ac.uk/Eagle/). In these simulations the properties of the galaxies are recorded over time. The visualisation in the video shows two properties of one particular galaxy: star formation rate (blue curve) and metallicity (orange curve) as a function of time over most of the age of the Universe (~13 Gyrs). STRAUSS was used to turn these data into sound (heard in the video). Star formation rate is mapped to pitch and metallicity is mapped to a cut-off frequency of a low pass filter (with an A5 carrier). In the video a moving dashed line shows you which part of the data are being used to control the properties of the sound at that particular time. 7. multivariate_realisation_b.mp4 Same as multivariate_realisation_a.mp4, but this time the star formation is mapped to a (sinusoidal) low frequency oscillator so the volume pulse rate increases with star formation rate. 8. stars.mp4 This video is a screen-grab recording of a Virtual Reality playback of the 'Stars Appearing' sequence. The data and sonification approach (made using STRAUSS) are described in more detail in Harrison et al. 2022, Astronomy & Geophysics, Volume 63, Issue 2, pp.2.38-2.40. Briefly, there is a visual and sonification representation of data for star brightness (V-band magnitude), colour and position of stars located above the Very Large Telescope in Chile on 13th September 2019. Each star is represented by a single sound produced by a sample of glockenspiel notes. The stars are heard in order of brightness (brightest first). When a star is heard it also flashes briefly in the visualisation. The colour of the star (difference in B-band and V-band magnitude) determines which note is played, from one of five pitches: Db3, Gb3, Ab3, Eb4 or F4. The reddest stars are assigned the lowest notes and the bluest stars the highest notes. The stars position on the sky are used to place the sound in the correct location in 'sound' space for the VR experience (using full ambisonics); however the sound in this playback recording is in mono. For the full surround sound (ambisonics) use the Virtual Reality file listed below, or for a stereo and 5.1 version visit: https://data.ncl.ac.uk/account/projects/123730/articles/16988107 9. stars_appearing_mw_ambiX3_360_FB360.mkv The same as stars.mp4 but this is the full file required for Virtual Reality playback (including the visualisation and full ambisonic sound). Explain the relationship between multiple data sets, if required: N/A ========================== Methodological information ========================== A brief method description of what the data is, how and why it was collected or created, and how it was processed: The methods for each individual file are described above. Instruments, hardware and software used: + STRAUSS Python package: https://github.com/james-trayford/strauss + Other python packages: matplotlib, astropy, numpy + ffmpeg (command link package to make the movies) Date(s) of data collection: Files generated in March 2023 Geographic coverage of data: N/A Data validation (how was the data checked, proofed and cleaned): N/A Overview of secondary data, if used: N/A ========================= Data-specific information ========================= Definitions of names, labels, acronyms or specialist terminology uses for variables, records and their values: N/A Explanation of weighting and grossing variables: N/A Outline any missing data: None