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    --- 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 ## Demos ### WP2: Open Science paper @defeo https://github.com/fdslrm/EBLUP-NE 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. ### WP4 #### 3d visualisation @minrk, Marcin 3D visualisation with k3d, ideally include micromagnetics example #### Jupyter collaboration (2-3 minutes) @minrk - 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) - Statistics - 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 - HPCGAP - Meataxe64 (9 minutes) - SyntaxTree Suggestions: - MeatAxe: Tell the story on one use case (e.g. around the Monster), with comparison before / after - HPCGap: - 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 - Semigroups - libsemigroups example - francy package example - Packages ecosystem - Other demos (Alex) - Memoisation (WP6) - PackageManager (WP3) - Use for lecturing (with RISE extension) - unipoly (on Binder!) ### Singular - 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 Demonstrates: - 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 Requirements: - 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 - 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! Suggestions: - 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

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