32:T4bb,This hackathon is a shared activity between the **Project Management in Data Science** and the **Information Visualization** modules. The event is supported by the [ViT Foundation](https://www.fundaciovit.org/), the [Càtedra Lluís Santaló d'Aplicacions de la Matemàtica](https://www.udg.edu/ca/catedres/Lluis-Santalo), and [Eurecat](https://eurecat.org/home/). #### 🧑‍🎓 What you will learn to … - Apply data science techniques to a real-world scenario and under time pressure. - Utilize data visualization techniques to translate data insights into actionable decision-making tools. - Document your process for knowledge sharing and open-sourcing, ensuring transparency and reproducibility. - Develop collaborative skills in a team setting, including communication, planning, task delegation, and iterative problem-solving. #### 📅 Pre-hackathon preparations: Pre-hackathon prep is key to being efficient and effective during the main event. That involves understanding the theme, organizing the team, brainstorming ideas, and setting up the necessary tools and environment in advance. This way, you can focus on developing your project rather than dealing with logistical or technical issues.33:[{"id":"638166d39c314280b3d4cbd233a414a1db38a0e421d77c2ddfcb20589658e204632730e2644de0943d32a48461ad4b09efbedf39c2a2ec074ea71d845113bb46","href":"https://static.observableusercontent.com/files/638166d39c314280b3d4cbd233a414a1db38a0e421d77c2ddfcb20589658e204632730e2644de0943d32a48461ad4b09efbedf39c2a2ec074ea71d845113bb46","name":"raposos.png","type":"image/png","lastModified":1766432688586.354,"size":8148},{"id":"3acff95edb915b6277e463a3c35ced8d2ac3b59663faec2ef763cedb7f12fc47cdd4a5725fbde556aa5207cc7689b2c0b97e3bcea2352a91a04b2b1b2357b254","href":"https://static.observableusercontent.com/files/3acff95edb915b6277e463a3c35ced8d2ac3b59663faec2ef763cedb7f12fc47cdd4a5725fbde556aa5207cc7689b2c0b97e3bcea2352a91a04b2b1b2357b254","name":"xabarins.png","type":"image/png","lastModified":1766432688576.617,"size":6490},{"id":"f4d0f7a527e57f5b426dbf30d0ba8d87679eb2da7e382ceb4f59b1a1cc2c1d704864a77fbe404b1673566ebd0f4ef0b58db68a2327f41c6b9bba418a9618eefd","href":"https://static.observableusercontent.com/files/f4d0f7a527e57f5b426dbf30d0ba8d87679eb2da7e382ceb4f59b1a1cc2c1d704864a77fbe404b1673566ebd0f4ef0b58db68a2327f41c6b9bba418a9618eefd","name":"teixugos.png","type":"image/png","lastModified":1766432688582.106,"size":7729},{"id":"686809a63c07d2086a9059ab66d433acec6bffaa41dcd80dea782fe257bc98fef341a5811fe6322d7a47b1da25859b538ff4288a139e3c44f857e2ebc7bd472f","href":"https://static.observableusercontent.com/files/686809a63c07d2086a9059ab66d433acec6bffaa41dcd80dea782fe257bc98fef341a5811fe6322d7a47b1da25859b538ff4288a139e3c44f857e2ebc7bd472f","name":"donicelas.png","type":"image/png","lastModified":1766432688576.925,"size":6943}] 30:{"title":"Teams, Schedule, Awards, and Grading","cells":[{"id":0,"value":"

Teams, Schedule, Awards, and Grading

","pinned":false,"hidden":false,"mode":"md"},{"id":8,"value":"hackatoHero01","pinned":false,"hidden":false,"mode":"ojs"},{"id":22,"value":"$32","pinned":false,"hidden":false,"mode":"md"},{"id":86,"value":"---\nAlso in this collection:\n- [Brief](https://observablehq.com/@udg-master-data-science/5th-hackathon-brief?collection=@udg-master-data-science/5th-hackathon-affordable-housing)\n- [Datasets](https://observablehq.com/@udg-master-data-science/5th-hackathon-datasets?collection=@udg-master-data-science/5th-hackathon-affordable-housing)\n- [Tutorial on interactive maps](https://observablehq.com/@udg-master-data-science/5th-hackathon-map-tutorials?collection=@udg-master-data-science/5th-hackathon-affordable-housing)\n- [Tutorial on Mosaic and vgplot](https://observablehq.com/@udg-master-data-science/5th-hackathon-mosaic-tutorial?collection=@udg-master-data-science/5th-hackathon-affordable-housing)","pinned":false,"hidden":false,"mode":"md"},{"id":79,"value":"---\n## Teams","pinned":false,"hidden":false,"mode":"md"},{"id":126,"value":"\n \n \n ${groups.map(d => html``)}\n \n \n \n ${groups[0].names.map((_, i) => html`\n \n ${groups.map(d => html`\n \n `)}\n \n `)}\n \n

${d.img} ${d.g}
${d.names[i] \|\| ''}

","pinned":false,"hidden":false,"mode":"html"},{"id":30,"value":"---\n## Activities and schedule\nA **preparatory session** will be held during our **regular session on Monday, February 2, 2026, at 16:30**.\n\nThe **full-day Hackathon** will be held in the **P-IV building, EPS UdG, on Saturday, February 7, 2026, at 08:30**. We will provide breakfast 🥐, lunch 🍕, snacks 🍊, coffee ☕, and emotional support 🫶. \n\n> 👋 **08:30** Welcome, breakfast ☕ 🥐, and set up by groups \n> 🙋‍♀️ **09:00** Standup meeting: objectives, processes, and what you want to achieve in the hackathon. \n> 👩‍💻 **09:15** Start of work day! \n> 🙋‍♀️ **13:45** Short standup \n> 🍕 **14:00** Lunch \n> 👩‍💻 **15:00** Back to work \n> 🧑‍🏫 **19:00** Wrap-up presentation: About 10 minutes per team. \n> 🏆 **19:45** Awards \n> 🍻 **20:00** End!!!\n","pinned":false,"hidden":false,"mode":"md"},{"id":52,"value":"---\n## The awards\nAs we all know, [the professional jury and the popular vote don't always match](https://www.youtube.com/watch?v=4uGN9efcACw), so we're offering two awards: y’all decide one via an open vote, we decide the other —which may or may not be the same, and we won't know until we reveal them simultaneously.\n\n> 🏆 **Jury fav**: A €500 gift card for the team (sponsored by the Càtedra Informació i Computació via Eurecat)\n> \n> 🏆 **Popular vote**: [_Dear Data: A Friendship in 52 Weeks of Postcards_](https://www.dear-data.com/theproject) by Giorgia Lupi and Stefanie Posavec (one copy of the book per team member, sponsored by the ViT Foundation)\n","pinned":false,"hidden":false,"mode":"md"},{"id":61,"value":"---\n## Our evaluation criteria\n### For the Project Management subject\nThe hackathon accounts for 25% of the final mark for the subject.\n\n- ~~35%~~ 50%: Active participation and engagement with the given roles.\n- ~~15%: Colleague evaluation within the teams. You'll judge your teammates’ engagement with their roles.~~\n- 25%: Persuasiveness and confidence in the presentation of the results.\n- 25%: Creativity, feasibility, and accuracy of the deliverables.\n\n### For the Information Visualization subject:\nThe hackathon accounts for 10% of the final mark for the subject —i.e. one full point.\n\nAll attending students get 0.4 for actively participating. All students in the winning groups get 0.6 (if the popular vote coincides with the jury favorite, they'll get an extra 0.2)\n\nWe will take into account:\n- How clearly the visualization displays the results,\n- the strategies used to highlight patterns,\n- the integration of the visuals with the documentation or the text in the Observable notebook.","pinned":false,"hidden":false,"mode":"md"},{"id":18,"value":"---\n#### Addendum","pinned":false,"hidden":false,"mode":"md"},{"id":83,"value":"import { hackatoHero01 } from \"@udg-master-data-science/5th-hackathon-datasets\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":114,"value":"groups = [\n {\n g: \"Xabaríns\",\n img: xabarins,\n names: [\"Christian\", \"Narcís\", \"Pau\", \"Juan\"]\n },\n {\n g: \"Teixugos\",\n img: teixugos,\n names: [\"David\", \"Àlex\", \"Fabricio\", \"Iu\"]\n },\n {\n g: \"Raposos\",\n img: raposos,\n names: [\"Marco\", \"Jordi\", \"Joan\", \"Natalia\"]\n },\n {\n g: \"Donicelas\",\n img: donicelas,\n names: [\"Albert\", \"Josep\", \"Karina\", \"Louis\"]\n }\n]","pinned":false,"hidden":false,"mode":"ojs"},{"id":118,"value":"donicelas = FileAttachment(\"donicelas.png\").image({width:120})","pinned":false,"hidden":false,"mode":"ojs"},{"id":119,"value":"raposos = FileAttachment(\"raposos.png\").image({width:120})","pinned":false,"hidden":false,"mode":"ojs"},{"id":120,"value":"teixugos = FileAttachment(\"teixugos.png\").image({width:120})","pinned":false,"hidden":false,"mode":"ojs"},{"id":121,"value":"xabarins = FileAttachment(\"xabarins.png\").image({ width: 120 })","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}