Note: This has been used, the video is produced. Data analysis We will use Buster Keaton public domain videos (one week, …) Flow Data analysis and results are a thrill when collecting data, different formats are often possible data format modification is costly, the later it comes the more costly making sure the data collected will be 1 stored, 2 analysed in its format is a time saver. In doubt, make the data computer readable does reduce that cost ideas Before the data collection starts, it is useful to know what format it will have.
While previous video were online for some time, I have worked the concept a bit and end up with 4 videos so far. The first one is about open data and features superman. The second one is about using RDM to be sure to be able to retrieve one’s data and work more efficiently. It features Popeye. The third one is a general introduction about the main pitfalls RDM aims at avoiding, ending with a positive thinking: “we want better research in less time, while producing open FAIR data”.
Here are notes about what stories we will use to design cartoons. 1 Your first collaborator is yourself, and your past self does not answer emails Documentation is key if you want others (i.e. you in two years) to understand what you did. S1: I have a collaborator that will analyse the data and write the paper, but he is not allowed to ask me any question. S1: Can you check if my explanations will be sufficient for her to do his job.
Please send your feedback about the current video (now: v.3)! script Open FAIR data is the new standard (actual srt file available on github) Research data shall be free, digital, shared and re-usable. Only while open it will reach its true potential. Fostering collaboration, open data accelerates research, and even years after its production, by allowing easy preliminary and meta-analyses, open data can bring research on the right track.
Background I have recently completed a project that involved curating, researching and staging three performances of live electronic music compositions by the English composer Hugh Davies (1943-2005). Staging these concerts has, in many cases, involved building the equipment required to perform them from scratch, based on incomplete or ambiguous information gleaned from archival documents. In addition, these are experimental pieces, with scores that comprise text-based instructions and descriptions rather than standard notation, as well as other inherently unpredictable elements that mean that the pieces turn out differently every time they are performed.