{"id":4187,"date":"2025-01-28T09:22:23","date_gmt":"2025-01-28T09:22:23","guid":{"rendered":"https:\/\/libraryblogs.is.ed.ac.uk\/datablog\/?p=4187"},"modified":"2025-01-28T09:28:48","modified_gmt":"2025-01-28T09:28:48","slug":"datashare-spotlight-human-motionless-dataset-humols-and-the-creative-potential-of-research-data","status":"publish","type":"post","link":"https:\/\/libraryblogs.is.ed.ac.uk\/datablog\/2025\/01\/28\/datashare-spotlight-human-motionless-dataset-humols-and-the-creative-potential-of-research-data\/","title":{"rendered":"DataShare spotlight: Human MotionLess Dataset (HuMoLs) and the creative potential of research data"},"content":{"rendered":"

For the second installment of the spotlight on DataShare blog posts, I would like to showcase a fascinating item containing videos of people not doing anything!<\/p>\n

The dataset in question is titled \u201cHuman MotionLess Dataset (HuMoLs)<\/em>\u201d and was created by researchers Longfei Chan, Muhammad Ahmed Raza and Robert Fisher, who are based in the School of Informatics\u2019 Institute of Perception Action and Behaviour. While on the face of it, people being still might not seem very dynamic, the research behind this dataset is trying to solve a difficult problem with a very useful outcome. Simply put, how do you tell when someone is lying still because they are doing something like sleeping, or if it is because they are unwell or have fallen? The videos in this dataset aim to try and train healthcare monitoring systems to help determine whether it is the former or the latter of these possibilities, with the priority being to uncover any critical medical conditions or to analyse chronic conditions.<\/p>\n

\"A<\/p>\n

What struck me while reviewing the videos for submission was that beyond the usefulness of these videos to the research project, there was the potential for them to be adapted creatively. The videos have a deliberately \u201cuncanny valley\u201d aspect, due to using AI to deepfake participant\u2019s faces in order to preserve their anonymity. The amusingly odd character to the videos made me imagine them being used in an Adam Curtis documentary, or in an Aphex Twin music video. Possibly even in an Adam Curtis documentary with Aphex Twin music over the top of it.<\/p>\n

This raises the fascinating idea that there are rich sources of research data stored in open access repositories that could have a life beyond being reproducible, but could also be reused, repurposed and remixed into creative new pieces, adding value to both the research itself, and to the repositories where the affiliated data is stored. To demonstrate this possibility, I have edited some of the videos together, see below, and set them to music. The piece of music, \u201cRedolescence<\/em>\u201d by Other Lands, has a dreamlike quality to it which both complements and recontextualises the videos into something beyond their originally intended use.<\/p>\n