List your projects!

[RaoOfPhysics]

CERN Study Group Projects

List your public projects (with link to GitHub / Bitbucket / GitLab) below so we have a list for contributors. Format:

- Name: 
- Description: [one not-too-long sentence] 
- Link to repo(s): 
- Skills needed / sought: 
- Additional info: 

(N.B.: Do not use this issue for 👍 / +1 and similar comments. Use it exclusively to list your open-science projects.)

[seneubert]

• Name: ANA-Docker
• Description: tutorial to setup Gitlab-CI at CERN, including a Dockerfile to create a useful container for analysis
• Link: https://gitlab.cern.ch/sneubert/ANA-Docker
• Skills sought: Docker foo
• Additional info: The tutorial needs some feedback from people trying it out. The Container could be modularised.

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• Name: Continuous Analysis Template
• Description: template to setup CERN analysis repositories with CI (using ANA-Docker)
• Link: https://gitlab.cern.ch/sneubert/ContinuousAnalysisTemplate
• Skills sought: feedback, jupyter
• Additional info: The template and instructions need feedback and polishing. If someone wants to add a jupyter notebook example, this would be welcome

[suenjedt]

• Name: CERN Open Data Portal
• Description: An open platform to publish open data from CERN experiments
• Link to repo(s): https://github.com/cernopendata/opendata.cern.ch
• Skills needed / sought: feedback, input, ideas, data?
• Additional info:
  • this is a collaborative effort and we are eager to get feedback from others (i.e. potential users and contributors): what else to integrate? how to improve text, design/IA, tutorials?
  • who is "we": a mixed team from CERN IT, Scientific Information Sevice and the LHC collaborations

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• Name: CERN Analysis Preservation
• Description: A prototype service to preserve the insider knowledge about an analysis (data, software, docs), with easy open publishing options. Demo of latest prototype, concept and how it integrates with existing tools at CERN
• Link to repo(s): https://github.com/cernanalysispreservation/analysis-preservation.cern.ch
• Skills needed / sought: feedback, input
• Additional info:
  • this is a collaborative effort and we are eager to get feedback from others (i.e. potential users and contributors)
  • who is "we": a mixed team from CERN IT, Scientific Information Sevice and the LHC collaborations

[jacquerie]

• Name: senato.py
• Description: A scraper for the data made available by the Italian Senate, and a cluster analysis to detect similar amendments.
• Link to repo(s): https://github.com/jacquerie/senato.py
• Skills needed / sought: Some coaching on text similarity (I'm just using Jaccard similarity).
• Additional info:
  • The Italian Senate is clogged by computer-generated amendments. This project aims to cluster similar amendments so that specific Senate procedures can be used to get rid of them in one sweep.
  • This is more of an open-politics project rather than open-science, but here it goes : )

[betatim]

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• Name: Everpub
• Description: 🔭 Everpub - Making reusability a first class citizen in the scientific workflow.
• Link to repo(s): https://github.com/everpub
• Skills needed / sought: docker, JS, python

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• Name: Everware
• Description: Reproducible and reusable science powered by jupyterhub and docker. Like nbviewer, but executable.
• Link to repo(s): https://github.com/everware
• Skills needed / sought: python, unit testing, docker

[tpmccauley]

• Name: iSpy WebGL
• Description: A browser-based event display for the CMS experiment using WebGL
• Links: https://github.com/cms-outreach/ispy-webgl, http://cern.ch/ispy-webgl
• Skills needed/sought: feedback (is that a skill?), testing

[pseyfert]

• Name: FlavourTransfer (working title)
• Description: Apply arXiv:1409.7495 (transfer learning / domain adaptation) to LHC(b) data
• Link to repo(s): pseyfert/transfer-learning
• Skills sought: experience with BVLC/caffe or will to reimplement 1409.7495 in a different framework
• Additional Info:
  • Machine learning classifiers are often trained on simulated events and applied to real data. The authors of 1409.7495 deal with image recognition, trained with professional photos to be applied to low quality smartphone pictures. So … what they came up with should be applicable in physics.
  • As alternative to porting the physics data to caffe, one could as well port the method by 1409.7495 to theano/sklearn/tmva/whatever-works

[rochaporto]

• Name: CERN Container Service
• Description: Scalable container clusters on the CERN cloud (docker swarm or kubernetes)
• Link to repo(s): https://github.com/openstack/magnum
• Skills needed / sought: python, docker, docker swarm, docker compose, kubernetes
• Additional Info:
  • cern specific documentation

[spMohanty]

• Name: CrowdAI Knowledge Base
• Description: An open access and community driven collection of resources to help everyone get started on state of art Machine Learning Resources on open problems in Science !!
• Link to repo(s): https://github.com/crowdAI/Knowledge-Base
• Skills Sought: Experience with Data Science and/or desire to teach and learn and/or knowledge about a bucket load of interesting open problems from your domain of expertise
• Additional Info:
  • http://crowdai.github.io/Knowledge-Base/

[riga]

• Name: tfdeploy
• Description: Tool to deploy tensorflow DNN graphs for fast evaluation and export to tensorflow-less environments running numpy
• Link to repo(s): https://github.com/riga/tfdeploy
• Skills needed / sought: Experience with Deep learning techniques and performant numpy/scipy.

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• Name: luigi analysis workflow
• Description: High-level extension layer for spotify's Luigi to enable advanced analysis workflows over distributes resources, so a WMS for end-user analysis =)
• Link to repo(s): https://github.com/riga/law
• Skills needed / sought: Experience with Python, Docker, GFAL & distributed computing
• Additional Info: CHEP16 talk

[JoeriHermans]

• Name: Distributed Keras (dist-keras)
• Description: Employing Distributed Optimization algorithms and Apache Spark to train neural networks (Keras models).
• Link to repo(s): https://github.com/cerndb/dist-keras
• Skills needed / sought: Use-cases, "big" (physics) datasets, and models.