L. Bauerdick, M. Ritter, O. Gutsche, M. Sokoloff, N. Castro, M. Girone, T. Sakuma, P. Elmer, B. Bockelman, E. Sexton-Kennedy, G. Watts, J. Letts, F. Würthwein, C. Vuosalo, J. Pivarski, D. Katz, R. Bianchi, K. Cranmer, R. Gardner, S. McKee, B. Hegner, E. Rodrigues, D. Lange, C. Paus, J. Hernández, K. Pedro, B. Jayatilaka, L. Kreczko
{"title":"arXiv : HEP Software Foundation Community White Paper Working Group - Data Analysis and Interpretation","authors":"L. Bauerdick, M. Ritter, O. Gutsche, M. Sokoloff, N. Castro, M. Girone, T. Sakuma, P. Elmer, B. Bockelman, E. Sexton-Kennedy, G. Watts, J. Letts, F. Würthwein, C. Vuosalo, J. Pivarski, D. Katz, R. Bianchi, K. Cranmer, R. Gardner, S. McKee, B. Hegner, E. Rodrigues, D. Lange, C. Paus, J. Hernández, K. Pedro, B. Jayatilaka, L. Kreczko","doi":"10.2172/1436702","DOIUrl":null,"url":null,"abstract":"At the heart of experimental high energy physics (HEP) is the development of facilities and instrumentation that provide sensitivity to new phenomena. Our understanding of nature at its most fundamental level is advanced through the analysis and interpretation of data from sophisticated detectors in HEP experiments. The goal of data analysis systems is to realize the maximum possible scientific potential of the data within the constraints of computing and human resources in the least time. To achieve this goal, future analysis systems should empower physicists to access the data with a high level of interactivity, reproducibility and throughput capability. As part of the HEP Software Foundation Community White Paper process, a working group on Data Analysis and Interpretation was formed to assess the challenges and opportunities in HEP data analysis and develop a roadmap for activities in this area over the next decade. In this report, the key findings and recommendations of the Data Analysis and Interpretation Working Group are presented.","PeriodicalId":8424,"journal":{"name":"arXiv: Computational Physics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv: Computational Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2172/1436702","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
At the heart of experimental high energy physics (HEP) is the development of facilities and instrumentation that provide sensitivity to new phenomena. Our understanding of nature at its most fundamental level is advanced through the analysis and interpretation of data from sophisticated detectors in HEP experiments. The goal of data analysis systems is to realize the maximum possible scientific potential of the data within the constraints of computing and human resources in the least time. To achieve this goal, future analysis systems should empower physicists to access the data with a high level of interactivity, reproducibility and throughput capability. As part of the HEP Software Foundation Community White Paper process, a working group on Data Analysis and Interpretation was formed to assess the challenges and opportunities in HEP data analysis and develop a roadmap for activities in this area over the next decade. In this report, the key findings and recommendations of the Data Analysis and Interpretation Working Group are presented.