tags: OpenDreamKit, Final Review
# OpenDreamKit final review (rehearsal day 1)
This pad is for taking notes during the first day of rehearsal for
OpenDreamKit's [Final review](https://opendreamkit.org/meetings/2019-10-30-Luxembourg/).
- [Notes for rehearsal day 2](/lGEmzaiWTq2ZBrZ_GuGkug)
- [Notes for the review day](/TpyMyvlzTPmajWX3TtwfHw)
Having a glossary seems useful to reviewers. At both previous reviews we (Vincent) made one, see
[the Glossary folder on github](https://github.com/OpenDreamKit/OpenDreamKit/tree/master/Glossary).
## Agenda Brainstorm
Agenda brainstorm was copied into the pad for Day 2 and is edited there.
## WP presentations
Suggestions from our reviewers:
We need to understand not only the achievements of the project as a whole, but also to know whether this kind of project is viable in the future. Here are three suggestions:
- Stick to high level presentations on work packages, without going too much into the details
- Focuse the presentations more on problems encountered
- explain what the future generation of project can learn from our experience
One of the reviewers further suggested:
The project was funded on the idea of creating a collaborative environment. Therefore, the success of the project should be measured against this objective. He therefore suggests to make a special focus on:
- How to evaluate Jupyter Notebooks as system by which one can collaborate internally
- Same question for external collaboration
### WP2: Open Science paper
Binder-powered GitHub repo associated to a research paper
- uses Sage, CVXPY, Scipy and R
- external to OpenDreamKit!
Hančová, M., Vozáriková, G., Gajdoš, A., Hanč, J. (2019). Estimating variance components in time series linear regression models using empirical BLUPs and convex optimization, https://arxiv.org/abs/1905.07771, 2019.
#### 3d visualisation
3D visualisation with k3d, ideally include micromagnetics example
#### Jupyter collaboration (2-3 minutes)
- nbdime diff
- live collaboration in JupyterLab
Give a few words of context:
- feature been there in cocalc for years
- use the analogy with google docs / ...
- big deal: impact
- big deal: required structural changes in the core design of JupyterLab
### WP6 Data.MathHub.info (5 min; Katja & Michael)
- Demonstrate F. A. I. R.
- citability? permanent URI
- Discussion about options for long term preservation
Software heritage for metadata / small data sets that can be put in version control
??? from EOSC??? for raw data preservation
### Persistent Memoization (GAP/Sage; Alex/Steve)
NT: How long a demo would be proper fit here?
NT: If just a short one, maybe I could fit this in "Balthazar's use case; need to find a nice example"
both best after the WP6 talk.
### High Performance Mathematical Computing with GAP (Steve Linton)
All rather technical, designed for "drop in" rather than presentation
- Meataxe64 (9 minutes)
- MeatAxe: Tell the story on one use case (e.g. around the Monster), with comparison before / after
- Draw a picture for block multiplication?
- Explain Before ODK / After ODK
- Good news: lots of intricate code, many users: high impact
- Bad news: lots of intricate code, many users: hard to maintain backward compatibility
### GAP usability
- WP4 stuff (Alex) -- demonstration of usability of GAP Jupyter notebooks. Maybe pick up one, leave the rest for the "drop in"?
- Homophonic quotients
- libsemigroups example
- francy package example
- Packages ecosystem
- Other demos (Alex)
- Memoisation (WP6)
- PackageManager (WP3)
- Use for lecturing (with RISE extension)
- unipoly (on Binder!)
- Benchmarks of old Singular vs new Singular
- Possibly rational functions?
### WP3/WP5 integration Linbox in Sage
### Balthazar wants to do modular rep theory of semigroups (Nicolas)
Cross WP demo
- low and high level interfaces
- Sage, GAP, Semigroups, ...
- widgets / explorer (hopefuly)
- Sharing via binder, "deploying on a VRE" (thanks to packaging)
### Use Case: Jupyter for Enterprise Training at Logilab (Olivier, 4 minutes?)
Scenario: Logilab trains 500 scientists yearly on scientific computing, with highly heterogeneous groups
- Maintain a large collection of exercises
- Foster autonomy of students, engaging them to explore at their own pace, with automatic feedback
Previous solution: slides + python in the console
Current solution: Deploye a Jupyter-based Virtual Environmnent:
- JupyterHub server
- Jupyter-training: open source home-grown solution to solve our needs, now shared with the world
Outcome: people are more engaged, autonomous, ... They keep using the server after their session! We need to cut them!
- more impressive example
- show an answer
- show the author's perspective: what do the sources look like
- demonstrate how this could be used for teaching mathematics