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tags: OpenDreamKit
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# ODK Web site
[TOC]
## Keywords
For each item we need:
- one or two word link
- short heading
- one sentence summary
- brief description (one paragraph or more)
- links to more details / videos / ...
### About
Short heading: What is OpenDreamKit?
One sentence summary: OpenDreamKit supports better science through better e-infrastructure for computational science.
OpenDreamKit is a project that brings together a range of projects and associate software to create and strengthen virtual research environments. The most widely used research environment is the Jupyter Notebook from which computational research and data processing can be directed. The OpenDreamKit project provides interfaces to well established research codes and tools so that they can be used seamlessly and combined from within a Jupyter Notebook.
OpenDreamKit also supports open source research codes directly by investing into structural improvements and new features to not only connect all of these tools but also enrich them, and make them more sustainable.
More concretely, the tools brought together in the OpenDreamKit project include mathematical software packages such as SageMath, GAP, [add more] but also simulation tools from materials science such as OOMMF [add link to full list].
OpenDreamKit has also advanced the Jupyter Notebook Ecosystem, for example through providing tools to support reproducibility in computational science [add link to reproducibility/nbval], effectively comparing and merging notebooks [nbdime link], and providing interactive 3D visualisation [link to summary] within the notebook.
### Use cases (and success stories)
- use cases: what can ODK do?
- success stories: what has been done
Current paragraphs on the web page; please proofread!
This (in-the-works) page collects a range of typical use cases that the OpenDreamKit project aims at tackling. It targets end-users,
reviewers, and followers. For each use case, a document:
- describes a typical scenario;
- suggests operational solutions (or upcoming solutions) and best
practices, with a rough assessment of the technical difficulty to
set it up;
- describes the progress during the OpenDreamKit project;
- links to exemplary instances;
- showcases OpenDreamKit contributions.
Second attempt:
The links below lead to a series of use cases - examples of work that have been made possible through the OpenDreamKit project.
The general structure is to describe a work requirements what is required - for example [need an example here] - followed by a solution using OpenDreamKit supported tools. Where appropriate, we provide links to related examples, and provide more details.
### Events
Short: Training and developers events
One line: Training, developer workshops, project meetings and dissemination
Training and community building is dear to the heart of our team mates. The OpenDreamKit funding has enabled us to multiply our actions. We (co)organize dozens of training events and summer schools in Europe and all over the world where we train the new generation in mathematics (and beyond!) to better use computational software. We run coding sprints where developpers from various horizons gather for a couple of days to tackle common needs together (TODO: a few words about about the impact). Finally, we meet regularly to coordinate our actions, and go around the world to advocate for our software ecosystem, and raise awareness of open science and best practices.
### Reproducibility
Long title: Open Science and Reproducibility
One line summary: OpenDreamKit support reproducibility in computational science
A key concept in science is that of reproducibility: Imagine a researcher or research group carries out a study, comes to a conclusion and publishes this. We call the work reproducible, if the publication describes the study in such way that another research group can follow the description, repeat the study and come to the same conclusion.
The issue of reproducibility is particularly acute when computer based work is involved, for example to generate data or analyse data. For full reproducibility, it is required to archive the software, to record exactly which processing steps where carried on which order on what data and how figures, tables and other results were obtained from that. Ideally, any software that is used should be open source so that there are no 'hidden steps' in processing.
Reproducibility raises a number of challenges, including a technical and social one.
One the technical side, the OpenDreamKit project enables and improves more reproducible research by allowing to drive computational science inside the Jupyter Notebook, which provides a full and detailed record of computational steps taken, together with the results obtained. It also allows to annotate the results, thus capturing the key elements of a scientific study: experiment, processing and interpretation. This makes in easier for the scientists to log their actions, and share this with others - for example an as appendix to a publication. Further technical work includes the creation of the NBVAL package [add use case link] and support of the Binder project [add use case link] that archives the computational environment in which such a notebook can execute successfully.
On the social side, it is important to convince scientists, but more so journal editors and policy makers that reproducibility is important for better science and more effective use of taxpayers money. OpenDreamKit runs a wide range of workshops to spread this message and train scientists in use of the relevant tools [add link / use case and workshops?].
### engagement -> promoting diversity
keyword: Diversity
Short title: Promoting diversity
blurb: Engaging toward an inclusive science community
At OpenDreamKit, we care about creating an inclusive and diverse science community. Our experience in open-source development tells us we are not there yet: many groups, like women and minorities, are largely under-represented. We have been organizing events to reach a wider, more diverse crowd.
### software we contribute to
keyword: software
short title: software we contribute to
blurb: OpenDreamKit supports the development of several several open source software projects
first paragraph:
OpenDreamKit is built on the principle of supporting, improving, and integrating various software components already in use by the mathematical research and education communities. We contribute to software involved in mathematical research and education at all levels, which can be assembled as components in different combinations to serve a variety of use cases. See below a collection of software OpenDreamKit has contributed to and details about our contributions. These contributions mostly fit in two broad categories: mathematical research software and general purpose e-infrastructure software such as user interfaces.
### jupyter notebook
keyword: Jupyter
short title: Jupyter and OpenDreamKit
blurb: The Jupyter notebook is a common interface for OpenDreamKit projects.
The Jupyter notebook is a web-based notebook interface for interactive computing, used widely in research and education in numerous fields. Mathematical researchers use many different languages for their work and OpenDreamKit's goal is to support researchers where they are already working. The fact that Jupyter can be used in any language makes it a good fit for OpenDreamKit.
Much of our Jupyter-related contributions are in two broad categories: making mathematical tools work or work better in Jupyter, and contributions to the general Jupyter ecosystem that are particularly useful for research and education.
- jupyter compatibility
- kernels
- joommf
- general jupyter
- nbdime
- nbval
- thebelab
- visualisation
- K3D-jupyter
- pythreejs
- ipydatawidgets
- unray
### mathematical software