This readme.txt file was generated on <2022-21-06> by Recommended citation for the data: Dunne, Lucy; Dahunsi, Bolanle; Woelfle, Heidi; Holm, Allison; Mack, Isidora; Mochoge, Neema; Philemon, Paith. (2022). Numerical RGB and LAB values of skin colors for Cabinet members of 32 countries extracted using Photoshop. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/tvtg-fk90. ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Numerical RGB and LAB values of the skin colors extracted using Photoshop from Facial images used for skin color variation analysis 2. Author Information Principal Investigator Contact Information Name: Lucy Dunne Institution: University of Minnesota Address: Wearable Technology Lab, 1985 Buford Ave. St. Paul, MN 55108 Email: ldunne@umn.edu ORCID: 0000-0002-8889-2087 Associate or Co-investigator Contact Information Name: Bolanle Dahunsi Institution: University of Minnesota Address: Wearable Technology Lab, 1985 Buford Ave. St. Paul, MN 55108 Email: dahun002@umn.edu ORCID: 0000-0002-8481-5535 Associate or Co-investigator Contact Information Name: Heidi Woelfle Institution: University of Minnesota Address: Wearable Technology Lab, 1985 Buford Ave. St. Paul, MN 55108 Email: woel0055@umn.edu ORCID: 0000-0002-1096-6111 Associate or Co-investigator Contact Information Name: Allison Holm Institution: University of Minnesota Address: Wearable Technology Lab, 1985 Buford Ave. St. Paul, MN 55108 Email: holm0812@umn.edu ORCID: Associate or Co-investigator Contact Information Name: Isidora Mack Institution: University of Minnesota Address: Wearable Technology Lab, 1985 Buford Ave. St. Paul, MN 55108 Email: mack0596@umn.edu ORCID: 0000-0003-0130-5626 Associate or Co-investigator Contact Information Name: Neema Mochoge Institution: University of Minnesota Address: Wearable Technology Lab, 1985 Buford Ave. St. Paul, MN 55108 Email: mocho008@umn.edu ORCID: Associate or Co-investigator Contact Information Name: Paith Philemon Institution: University of Minnesota Address: Wearable Technology Lab, 1985 Buford Ave. St. Paul, MN 55108 Email: phile001@umn.edu ORCID: 3. Date published or finalized for release: 2022-03-24 4. Date of data collection (single date, range, approximate date) 2021-06-22 to 2021-10-22 5. Geographic location of data collection (where was data collected?): Minnesota, USA 6. Information about funding sources that supported the collection of the data: National Science Foundation (#1715200), University of Minnesota 7. Overview of the data (abstract): Skin color values in RGB and LAB formats for a global population sample gathered from photographs of parliament members of 32 countries. Countries from which photographs were collected were purposefully selected to be representative of the diversity of skin colors across the world. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: Attribution 3.0 United States 2. Links to publications that cite or use the data: Paper not published yet but will be presented at the ITAA conference in September 2022. 3. Was data derived from another source? Data was downloaded from public images on various government webpages and numerical values extracted manually in photoshop. If yes, list source(s): 4. Terms of Use: Data Repository for the U of Minnesota (DRUM) By using these files, users agree to the Terms of Use. https://conservancy.umn.edu/pages/drum/policies/#terms-of-use --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: AllRGBAndLAB.csv Short description: A .csv file containing the numerical average values for visible sections of skin extracted from Photoshop. B. Filename: Number_of_images_by_country.png Short description: A .png image map showing countries where data was collected C. Filename: Readme.txt Short description: Current documentation file 2. Relationship between files: The csv file is the numerical RGB and LAB values for the skin color of each image downloaded. The map shows the number of images from each country. -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: The top five (5) countries in each continent with the highest percentage of female representation in parliament was obtained from https://data.ipu.org/women-ranking?month=4&year=2021 on 2021-22-06. Two other countries were then added to this list as they were found to have a wider spectrum of the darker ends of skin tones (South Sudan) or a large variation in skin tones (India). The final list has 32 countries. A search was conducted for the parliamentary website of the country and the images of the parliament members were downloaded. The URLS for each country were: Australia https://www.aph.gov.au/Senators_and_Members/Parliamentarian_Search_Results?q= Fiji https://www.parliament.gov.fj/members-of-parliament/ Guyana https://parliament.gov.gy/about-parliament/parliamentarian Micronesia https://www.cfsm.gov.fm/index.php/members/21st-congress Mozambique https://www.portaldogoverno.gov.mz/por/Governo/Conselho-de-Ministros Namibia https://www.parliament.na/1903-2/ New Zealand https://www.parliament.nz/en/mps-and-electorates/members-of-parliament/ Norway https://www.stortinget.no/no/Stortinget-og-demokratiet/Galleri/Stortingsrepresentantene/?acrid=A#primaryfilter Peru https://www.congreso.gob.pe/pleno/congresistas/ Singapore Removed 2 images that came as .thumb files and were too small with reddish tint https://www.parliament.gov.sg/mps/list-of-current-mps South Africa https://www.parliament.gov.za/group-details?keyword= Suriname https://www.dna.sr/het-politiek-college/leden-2020-2025/ Tonga https://www.parliament.gov.to/members-of-parliament/24-members-of-parliament/peoples/current-members/ Uzbekhistan https://parliament.gov.uz/ru/structure/deputy/?abs=%D0%90 Rwanda – Africa: 32 Ministers https://www.gov.rw/cabinet UAE – Asia 40 member of the Federal National Council: https://www.almajles.gov.ae/AboutTheFNC/UndertheFNC/Pages/Previous-Members-aspx.aspx# Timor-Leste https://www.parlamento.tl/Legislatura%202020%20-%202023 Sweden https://www.riksdagen.se/en/members-and-parties/ Senegal http://www.assemblee-nationale.sn/deputes-de-l-hemicycle-1-all.xml?p=active7 Andorra http://www.consellgeneral.ad/ca/composicio-actual/consellers-generals Finland https://www.parliament.fi/SV/kansanedustajat/nykyiset_kansanedustajat/Sidor/default.aspx Spain https://www.senado.es/web/composicionorganizacion/senadores/composicionsenado/senadoresdesde1977/consultaorden/index.html?legis=14 India https://www.india.gov.in/my-government/whos-who/council-ministers Bolivia https://web.senado.gob.bo/legislativa/brigadas Argentina https://www.hcdn.gob.ar/diputados/listadip.html Cuba Used provincial government and got the pictures of council members from each province website: Pinewood: https://www.redpinar.gob.cu/es/politica-y-gobierno/consejo-provincial-de-gobierno Sagebrush: https://www.artemisa.gob.cu/es/politica-y-gobierno/consejo-provincial-de-gobierno Mayabeque: https://www.mayaweb.gob.cu/es/politica-y-gobierno/consejo-municipal-de-gobierno Images are all black and white photographs so not used Havana: https://www.lahabana.gob.cu/category_detalles/es/33/estructura?page=1 Ciego De Havila: https://www.ciegodeavila.gob.cu/es/gobierno-provincial-menu-derecho-politica-y-gobierno/consejo-de-gobierno-provincial-menu-derecho-politica-y-gobierno Camaguey: https://camaguey.gob.cu/es/politica-y-gobierno/diputados-a-la-asamblea-nacional-2 Sancti spiritus: https://www.espirituano.gob.cu/gobierno-abierto - No images, just names Villa Clara: https://www.soyvillaclara.gob.cu/es/ Kilings/Matancenos: https://www.matanceros.gob.cu/es/politica-y-gobierno/gobierno-provincial-del-poder-popular No images, just names Isla de la Juventud: https://www.redisla.gob.cu/es/politica-y-gobierno/consejo-municipal-de-gobierno Guantanamo: http://www.guantanamo.gob.cu/es/politica-y-gobierno/consejo-provincial-de-gobierno Mostly names, just 2 images Santiago de Cuba: https://www.santiago.gob.cu/es/politica-y-gobierno/gobierno-provincial batched in poster on webpage De Granma: https://www.degranma.gob.cu/es/politica-y-gobierno/consejo-municipal-de-gobierno Holguin: https://www.holguin.gob.cu/es/politica-y-gobierno/consejo-municipal-de-gobierno No images Las Tunas: https://www.lastunas.gob.cu/es/politica-y-gobierno/composicion-de-la-ampp Mostly names, just 2 images Nicaragua http://legislacion.asamblea.gob.ni/Tablas%20Generales.nsf/Main.xsp Grenada https://gov.gd/whos-who-ministers Costa Rica http://www.asamblea.go.cr/Diputados/SitePages/Inicio.aspx Mexico Male: https://www.senado.gob.mx/64/senadores Female: https://www.senado.gob.mx/64/senadoras Timor Leste https://www.parlamento.tl/data-tables Nepal https://na.parliament.gov.np/np/members South Sudan Paith did a manual search for images of cabinet members from multiple pages and reconfirmed identities with friends back in South Sudan. Peter Marcello Nasir excluded as we could only find a black and white picture of him online. 2. Methods for processing the data: Images were merged into batches of nine(9) photos to simplify ease of import into Photoshop for color value extraction. The average RGB and LAB values for visible sections of skin with no shadows were extracted using the Magicwand tool in Photoshop and recorded for each image in the csv file. 3. Instrument- or software-specific information needed to interpret the data: None 4. Standards and calibration information, if appropriate: N/A 5. Environmental/experimental conditions: N/A 6. Describe any quality-assurance procedures performed on the data: Confirmation was done in excel to ensure that none of the values were outside the expected range of numbers within which numerical color values would fall in both the RGB and LAB color scale. 100 images were selected at random from the complete dataset for numerical values recollection in a different system from the ones initially used. Difference in average values for each image were within a range of +/-5, which was the initial tolerance value set as acceptable for the data. 7. People involved with sample collection, processing, analysis and/or submission: Bolanle Dahunsi, Heidi Woelfle, Allison Holm, Isidora Mack, Neema Mochoge, Paith Philemon, Lucy Dunne. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: AllRGBAndLAB.csv ----------------------------------------- 1. Number of variables: 7 2. Number of cases/rows: 3566 3. Missing data codes: N/A 4. Variable List A. Name: Image Description: This is the label for each image collected. Text B. Name: R Description: An integer value corresponding to the R component of the average skin section's RGB color Integer: 0 to 255 C. Name: G Description: An integer value corresponding to the G component of the average skin section's RGB color Integer: 0 to 255 D. Name: rgbB Description: An integer value corresponding to the G component of the average skin section's RGB color Integer: 0 to 255 E. Name: L Description: An integer value corresponding to the L component of the average skin section's LAB color Integer: 0 to 100 F. Name: A Description: An integer value corresponding to the A component of the average skin section's LAB color Integer: -128 to 127 G. Name: labB Description: An integer value corresponding to the B component of the average skin section's LAB color Integer: -128 to 127