Open serahkiburu opened 4 years ago
serahkiburu
commented
4 years ago Hi @lwinfree, thanks for agreeing to run your workshop remotely for CarpentryCon@Home. Please add details about your session to the sections with information pending above by editing the issue text.
lwinfree
commented
4 years ago Will do soon @serahrono!! So excited about this :-)
ousodaniel
commented
4 years ago @lwinfree there is still pending the possibility of multiple hosting? Kindly update, thanks
ousodaniel
commented
4 years ago @lwinfree thanks for your interest in regional hosting, check out the details here please. We'd love to see you sign up. Best
serahkiburu
commented
4 years ago Hi @lwinfree, the organising committee reviewed this session proposal and had this to say:
We are delighted to see the great mix of co-presenters. We recommend that the co-presenters think about how this session can provide opportunities for collaboration with attendees. It will help participants gain a great deal from attending this session.
Really excited for your session, and more details i.e. around scheduling will be shared with you in the coming days. Let me know if I can answer any questions or clarify anything for the time being.
lwinfree
commented
4 years ago Thanks @serahrono! That is helpful feedback :-)
lwinfree
commented
4 years ago Hi @serahrono or @ChristinaLK is there a recommended session length for the workshops? We (the co-presenters) are looking at our schedules right now to let you all know if the proposed time for this session will work for us all. Thanks!
serahkiburu
commented
4 years ago Hi @lwinfree 👋 the current recommendation is 1.5 - 2 hours, see https://github.com/carpentrycon/carpentryconhome-proposals#what-are-the-different-kinds-of-sessions-that-can-be-proposed
Title of the session: Frictionless data management for open and reproducible science
Session details
Session type: Workshop
Keywords: open science; reproducible research; open data; python; r; data management; metadata
Permission to record this session: Yes
Abstract
Generating insight and conclusions from scientific data is not always a straightforward process. Data is often hard to find, archived in difficult to use formats, poorly structured and/or incomplete. These issues create friction and make it difficult to use, publish and share data. The Frictionless Data initiative at Open Knowledge Foundation aims to reduce friction in working with data, with a goal to make it effortless to transport data among different tools and platforms for further analysis, and with an emphasis on reproducible research and open data. In this workshop, participants will learn about different sources of friction in working with scientific data and how to alleviate them using the open source Frictionless Data tools. Participants will learn where to find open scientific data, how to computationally prepare this data for further analysis and generate conclusions, and also best practices for sharing data and documenting metadata. This hands-on workshop is aimed for researchers interested in open science and reproducible research that are at a beginner programming level (for instance, some familiarity with Python or R and the command line), but more advanced programmers are also welcome.
Personal details
Name or pseudoname of the session lead: Lilly Winfree
Co-leads' names (we recommend involving 2 helpers/co-leads): Monica Granados (@monsauce), Daniel Ouso (@ousodaniel)
Email or other ways to contact the session leads/co-leads: lilly.winfree@okfn.org
Country of residence and/or compatible Time Zones (provide options): US Central/US Eastern
Would you like to present this multiple times, in other time zones: No
Would you like to volunteer to be listed as a wrangler/host for your time zone: Contact me with more details
Is there any help you would like to invite from the community? Please provide below in bullet points.
*N/A