{"id":14297,"date":"2024-10-31T23:59:39","date_gmt":"2024-11-01T05:59:39","guid":{"rendered":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/?p=14297"},"modified":"2024-11-01T00:03:40","modified_gmt":"2024-11-01T06:03:40","slug":"final-project-proposal-jyrus-cadman","status":"publish","type":"post","link":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/2024\/10\/31\/final-project-proposal-jyrus-cadman\/","title":{"rendered":"Final Project Proposal &#8211; Jyrus Cadman"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">For my final project, I aim to create <strong>a tangible data visualization that reflects the most frequently played keys on a piano<\/strong>. Specifically, I will produce individual keys with varying depths based on how often each key is played. The depth of each key will resemble a &#8220;crater&#8221; effect, symbolizing frequency intensity\u2014keys that are more frequently played will have deeper craters, while less frequently played keys will be shallower.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Once each key is printed, I will assemble them into a unified piano model, creating a tactile and visually striking representation of note usage. This project will combine my skills in Rhino, Grasshopper, and Python to accomplish a meaningful data physicalization, transforming abstract musical data into an engaging and interpretable 3D object.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Deliverables<\/h2>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Data-Driven 3D-Printed Piano Keys<\/strong>: Each key will have a unique depth based on play frequency, reflecting the data-driven concept.<\/li>\n\n\n\n<li><strong>Assembled Piano Model<\/strong>: The keys will be assembled into a single, cohesive model, offering a holistic view of the frequency distribution.<\/li>\n\n\n\n<li><strong>Digital Documentation<\/strong>: A supplementary digital model in Grasshopper or Rhino showcasing the frequency dataset and how it correlates to each key\u2019s depth, for reference and comparison.<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Project Timeline and Milestones (Tentative)<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Week 1: Data Collection and Preparation<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Goal<\/strong>: Obtain relevant data on piano key frequencies, focusing on MIDI files from popular music genres and classical compositions.<\/li>\n\n\n\n<li><strong>Tasks<\/strong>:\n<ul class=\"wp-block-list\">\n<li>Download the MAESTRO dataset from Google\u2019s Magenta project, focusing on a subset of compositions for efficiency.<\/li>\n\n\n\n<li>Process the data in Python using <code>pretty_midi<\/code> to calculate the frequency of each note across selected compositions.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Milestone<\/strong>: Generate a note frequency dataset that can be mapped to individual piano keys.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Week 2: Modeling and Test Prints<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Goal<\/strong>: Begin translating data into 3D form.<\/li>\n\n\n\n<li><strong>Tasks<\/strong>:\n<ul class=\"wp-block-list\">\n<li>Use Rhino and Grasshopper to create parametric designs for each piano key, assigning depth values to each based on the data from Week 1.<\/li>\n\n\n\n<li>Run a series of test prints to evaluate the depth representation, ensuring that the cratering effect accurately reflects frequency differences and remains structurally sound.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Milestone<\/strong>: Complete and approve test prints with desired depth precision.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Week 3: Final Prints, Assembly, and Documentation<\/strong><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Goal<\/strong>: Print, assemble, and document the final model.<\/li>\n\n\n\n<li><strong>Tasks<\/strong>:\n<ul class=\"wp-block-list\">\n<li>Print all keys, ensuring consistency in depth variations.<\/li>\n\n\n\n<li>Assemble the printed keys into a single model and document the outcome.<\/li>\n\n\n\n<li>Prepare digital documentation that illustrates the frequency dataset and maps it to the physical keys.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Milestone<\/strong>: Submit the assembled model and digital documentation for grading and display.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Related Work<\/h2>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Data Physicalization: A New Frontier for Data Science<\/strong> by Yvonne Jansen, Pierre Dragicevic, and Sheelagh Carpendale<br>This paper explores methods for transforming abstract data into tangible, physical forms, offering insights into the field of data physicalization. Jansen\u2019s work emphasizes how physical properties, like depth, can encode information, which is directly applicable to my project. This concept will inform how I use \u201ccratering\u201d to signify frequency, making the piano keys not just functional parts but interpretable data artifacts.<\/li>\n\n\n\n<li><strong>Tangible Bits: Towards Seamless Interfaces between People, Bits and Atoms<\/strong> by Hiroshi Ishii and Brygg Ullmer<br>Ishii\u2019s work on \u201ctangible bits\u201d emphasizes creating seamless, interactive interfaces between the digital and physical. By designing objects that communicate data through touch and sight, I hope to create a similar interaction in my final project, where each piano key\u2019s depth will visually and tactilely express musical frequency. This approach directly inspires the project&#8217;s interactive design, adding depth both conceptually and literally to the visualization.<br><a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/258549.258715\">Link to paper on ACM Digital Library<\/a><\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Summary<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">My goal with this project is to blend music, data science, and computational fabrication to create an insightful and interactive representation of piano key frequency. By focusing on creating a model with meaningful tactile qualities, I hope to convey musical data in an innovative, physically engaging way. This project will certainly challenge my skills in parametric design, data handling, and 3D printing, ultimately producing a unique visualization of sound.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>For my final project, I aim to create a tangible data visualization that reflects the most frequently played keys on a piano. Specifically, I will produce individual keys with varying depths based on how often each key is played. The depth of each key will resemble a &#8220;crater&#8221; effect, symbolizing frequency intensity\u2014keys that are more frequently played will have deeper [&hellip;]<\/p>\n","protected":false},"author":42,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[59],"tags":[],"class_list":["post-14297","post","type-post","status-publish","format-standard","hentry","category-final-project-proposal"],"_links":{"self":[{"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/posts\/14297","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/users\/42"}],"replies":[{"embeddable":true,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/comments?post=14297"}],"version-history":[{"count":2,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/posts\/14297\/revisions"}],"predecessor-version":[{"id":14398,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/posts\/14297\/revisions\/14398"}],"wp:attachment":[{"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/media?parent=14297"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/categories?post=14297"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/handandmachine.org\/classes\/computational_fabrication\/wp-json\/wp\/v2\/tags?post=14297"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}