Big Data Training and Research Suggestions for Joint Degree Program

1. BigDAPHNE … take 2  C.Roda Universita` e INFN Pisa

2. List of things to do • Work on draft according to next slide • revise your ESR projects • revise table of your institution • letter for joint degree • letters from partners • New draft ready by: December 5th C.Roda Universita` e INFN Pisa

3. Work sharing • Section 1 and WP description Chiara, Stefania Section 2 Chara, Rosy Section 3 Nikos, Tim • Letters for Double Degree – Status • UNIPI, UCL – Done • UNILE – Phd schoold meeting done, expected next week • Saclay – letter requested need to wait • AUTH – should arrive this week C.Roda Universita` e INFN Pisa

4. Asked letter and project C.Roda Universita` e INFN Pisa

5. Partners – not giving secondments Request from Nik to add University of Parma C.Roda Universita` e INFN Pisa

6. Training focus: BigData technology and tools • Event 1: Establishing the foundation (M. Morandin, F.Giacomini) • based on Bertinoro school – 2016 edition • https://agenda.infn.it/conferenceOtherViews.py?view=standard&confId=11680 • program mostly on Good programming practices in C++ / Architectures / Parallel Computing / GPU programming • will add more seminars on BigData analytic aspects • Event 2: Introduction to BigData techniques for science and society (?) • SAS (C.Gianfiori): introduction to SAS programming and statistics, DataMiner tool from SAS (7days) • Ophidia (D.Salomoni): a tool for BigData analytics • Introduction to BigData aspects in science • Event 3: Summer schools on Big Data techniques in Particle Physics and Cosmology (A.Di Meglio, …) • tools for Data Analytics in particle physics and cosmology • can we try to have a list of possible course subjects ? C.Roda Universita` e INFN Pisa

7. Work packages Suggestion from Nikos/Tim/Chiara: Merge WP1/WP2  Research in fundamental physics - CEA Merge WP3/WP4  BigData tools in fundamental physics and private sectors – UCL Training – UNILE Outreach and dissemination - AUTH Management and coordination - UNIPI C.Roda Universita` e INFN Pisa

8. Suggestions C.Roda Universita` e INFN Pisa

9. NCP – D’Agostino • General positive feedback – he thinks that in the evaluation report there are not strong objections • Suggestions to improve the project: • add a table with the list of institutions and list of needed expertise and show who has which expertise • describe also in document 1 the thesis that we have supervised and mention if we have students that have won prizes or that have found very good jobs • documentary check if we have described in the correct way what we wanted to do, he thinks the idea is good • Improve the description of the impact on the career: have two sections short term impact on long term impact:. short term: profit of the Marie Curie fellow to learn … . . long term: they will be able to submit ERC … • He is available to read the new version of the document to give feedback  beginning of Monday 5th December the document should be ready for review. C.Roda Universita` e INFN Pisa

10. G.Chiarelli – My colleague EU evaluator • - need to better evidentiate the connections and role of the different institutions and it is better to have more than a single role for the various institutions • - Dissemination should be done: • . be more precise on the actions for example if we mention we want to publish mention to which Journals • . companies: we could propose to build a boot of the project to send around to company meetings to disseminate results of the project • . "success story board" is not clear what it means, mention that for the movie we have a company that will do this and that we have a precise plan and mention successful experiences in similar actions • . it seems that one very fancy thing to propose in the dissemination are actions related to the citizen science (from wikipedia since I did not know what it meant): • Citizen science (CS) (also known as crowd science, crowd-sourced science, civic science, volunteer monitoring or networked science) is scientific research conducted, in whole or in part, by amateur or nonprofessional scientists. • we could ask our CMCC colleagues to make a weather forecast contests for public :-) ... any other ideas ? • - in Pisa we could have "sabato in Virgo" and enroll the students (from any experiment) as guides C.Roda Universita` e INFN Pisa

11. Tom Kitching – school content 1/2 In terms of Event 3 for Big Data aspects in PP and Cosmology, I think a good list of broad things to include from the cosmology side would be * Some basic stats and training in particular codes * Practical aspects in particular using public machine learning data sets from here https://www.kaggle.com/c/galaxy-zoo-the-galaxy-challenge , and also from the public supernovae and weak lensing cosmology data sets A list of topics could be: * Basic Stats: - What is probability? - The Laws of Probability and Bayes’ Theorem - Priors - Parameter inference - Marginalization - Confidence intervals, credibility intervals * Parameter Estimation: - Bayesian Computation: Parameter Estimation and Sampling - Grid-based methods - Markov Chain Monte Carlo - Metropolis-Hastings algorithm - Convergence tests – Rubin-Gelman - Hands on: MCMC code from scratch. Cosmology from the Supernova Hubble Diagram. C.Roda Universita` e INFN Pisa

12. Tom Kitching – school content 2/2 * Machine learning - Unsupervised and supervised ML methods - Random forests - Neural networks - Feature extraction - Hands on: Applying TensorFlow to image recognition. Galaxy shapes from Galaxy Zoo. * Cosmology codes - Public and Widely used cosmology codes - CosmoMC tutorial - Cosmosis tutorial - MontePython tutorial C.Roda Universita` e INFN Pisa

13. Similar project – Stefania, Nik • Asterics-Obelix project: https://www.asterics2020.eu/obelics CTA, SKA, KM3NeT, EUCLID, LSST, EGO-Virgo, E-ELT C.Roda Universita` e INFN Pisa