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BEGIN:VEVENT
SUMMARY:HSF/IRIS-HEP Analysis Reproducibility  (Virtual)
DTSTART;VALUE=DATE:20260426
DTEND;VALUE=DATE:20260430
UID:208756393765
DESCRIPTION:Event from 2026-04-27 12:00:00+00:00 to 2026-04-30 22:00:00+00
 :00\n\nEvent URL: https://indico.cern.ch/event/1658598/\n\nSpeakers: Andre
 s Rios-Tascon (Princeton University)\, Alexander Moreno Briceño (Universi
 dad Antonio Nariño)\, Valeriia Lukashenko (University of Zurich (CH))\, R
 icha Sharma (University of Puerto Rico (US))\, Michel Hernandez Villanueva
  (Brookhaven National Laboratory (US))\n\n      \nWe are very excited t
 o announce a workshop on Analysis Reproducibility organised through the HE
 P Software Foundation and IRIS-HEP \nWhat is analysis reproducibility?\nN
 o one does a data analysis once. After the exploratory phase\, computation
 s that were found to be useful are formalized as reusable programs that co
 nvert input data into final results\, and these programs are run over and 
 over\, with updates\, as new corrections and considerations come to mind. 
 This is a data analysis pipeline.\nIt is very important for a data analysi
 s pipeline to be reproducible. After all\, you want to draw conclusions ab
 out your data by running the pipeline under different conditions and seein
 g how the results change\, but they would not be valid conclusions if runn
 ing it under the same conditions also yields different results! A clean wo
 rkbench is an essential part of the scientific method\, and your data anal
 ysis code is part of your scientific workbench.\nIn addition\, scientific 
 results need to be reproducible after your experiment is done. Ensuring re
 producibility during your analysis simplifies the process of preserving yo
 ur analysis for future research. (This training workshop was previously ca
 lled "Training on Analysis Pipelines.")\nReproducibility is a concern for 
 software developers as well\, and many of the tools that have been develop
 ed for the software industry can be applied to data analysis.\nThis traini
 ng event is for data analysts who are already familiar with analysis tools
  and concepts (e.g. C++\, Python\, event selection\, limit setting) who wa
 nt to learn how to make their analysis pipelines robust using continuous t
 esting (CI/CD) and containerization (Podman\, Docker\, and Apptainer). In 
 addition\, we will cover REANA\, the Reproducible Research Data Analysis P
 latform.\nIt will be taught by tutors expert in HEP software. Interactive 
 hands-on sessions led by the tutors will be supported by a number of helpe
 rs to ensure that all participants are able to follow and understand the m
 aterial.\nGiven the limited number of participants\, all participants are 
 expected to attend the whole workshop.\nThis is a virtual event and no pay
 ment or travel is required for attending.  Participants are required to h
 ave their own laptop for the workshop.\nAll sessions will take place in th
 e US Eastern Time zone.\nPlease contact the organizers (email us) in case 
 of any questions.\nWhat exactly will I learn?\nOver four half-days we will
  cover the fundamentals of: \n\nPodman (free work-alike of Docker): Podma
 n material\nApptainer (formerly known as Singularity): Singularity/Apptain
 er material\nGitHub and GitLab CI/CD: GitHub material\, GitLab material\nR
 EANA: material\nAdditional topics: lectures\n\nAre there any prerequisites
 ?\nYes! \n\nFamiliarity with git (very important!)\n\nKnow how to create 
 repositories\nKnow how to edit and push files\nYou should have an account 
 either with github.com\, gitlab.com\, or gitlab.cern.ch \n\n\nSome famili
 arity with the Linux command line\nSome familiarity with Python\n\nAlso\, 
 see Setup: do this first on the left sidebar.\nWho is supporting this?\nTh
 is event is supported by CERN and U.S. National Science Foundation Coopera
 tive Agreement PHY-2323298 (IRIS-HEP).\nWho is teaching this thing?\nThis 
 is a hands-on training and consists of live lectures by the instructors vi
 a Zoom.  Along with this\, there are mentors who will give individual att
 ention and to debug assistance to participants via chat tools.  The peopl
 e filling these roles are listed below.  \nInstructors: \n\nPodman (Doc
 ker):\n\nMichel Hernandez Villanueva (Brookhaven National Lab)/Alexander M
 oreno Briceño (Universidad Antonio Nariño)\n\n\nApptainer (Singularity):
 \n\nMarco Mambelli (Fermilab)\n\n\nGitHub CI/CD:\n\nAndres Rios-Tascon (Pr
 inceton Univ)\n\n\nGitLab CI/CD:\n\nLera Lukashenko (University of Zurich)
 \n\n\nREANA\n\nTibor Simko (CERN) \n\n\n\nMentors (on Slack): \n\nMarco 
 Mambelli (Fermilab)\nRicha Sharma (Univ of Puerto Rico Mayaguez) \nMichel
  Hernandez Villanueva (Brookhaven National Lab)\nAlexander Moreno Briceño
  ( Universidad Antonio Nariño) \nTibor Simko (CERN)\n\n\n\n \n\n\n \n\
 n \n \n\n\n\n\n\n\nhttps://indico.cern.ch/event/1658598/
LOCATION:Virtual
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