Comparing Data Quality and Cost from Three Modes of On-Board Transit Passenger Surveys

This report presents the findings from a research project investigating the relative data quality and administration costs for three different modes of surveying bus passengers that produce results generalizable to the full passenger population. The three modes, all of which used survey methods distributed or administered onboard the transit vehicle, were: self-complete paper surveys, self-complete online surveys, and interviewer-assisted tablet-based surveys. Results from this study indicate several implications for practitioners choosing a survey mode. First, and most importantly, the analysis reinforces the point that there is no single, best survey mode. The choice of mode must depend on an agency’s priorities for what questions most need to be answered, what population groups are most important to represent, and exactly how the agency chooses to define concepts like a “complete” survey or a “usable” address. Findings suggest several general recommendations for current survey practice: (1) online surveys administered via an invitation distributed on the transit vehicle are not a good option; (2) old-fashioned, low-tech paper survey may still be the best option for many bus passenger surveys; (3) changes in survey results that accompany changes in survey methods should be interpreted with caution; and (4) using a new survey method, especially one relying on more complex technologies, may create unexpected glitches

Comparing data quality and cost from three modes of on-board transit surveys

Many transit agencies invest substantial resources in surveying their passengers to generate data used for planning, marketing, and equity analyses. Within the industry, there is considerable interest in replacing traditional paper-based self-complete surveys with new approaches that might lower costs or generate better quality data. However, very limited research has been done to identify the relative performance of different transit passenger survey modes. This paper begins to fill that gap. The research investigates the relative data quality for three different bus passenger survey methods distributed or administered on the transit vehicle: self-complete paper surveys, interviewer-assisted tablet-based surveys, and self-complete online surveys. The research used an experimental design, with the same survey questionnaire distributed via the three survey modes. All factors about the survey and distribution process were kept identical to the extent feasible, so that the only variation would be the survey mode itself. The findings by survey mode are compared in terms of the overall response and completion rates, the completion rate for individual questions, respondent demographics, and labor costs per complete. The study results suggest that many agencies may still find the old-fashioned, low-tech paper survey to be the best option for bus passenger surveys. The paper mode required less labor per complete, and for many of the metrics discussed it generated data that was as good as—or better than—the tablet survey. In addition, the findings suggest that online survey invitations distributed on the transit vehicle are not a good option because they were labor intensive and had very low response rates

DUNE Offline Computing Conceptual Design Report

International audienceThis document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment

Reconstruction of interactions in the ProtoDUNE-SP detector with Pandora

International audienceThe Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/$c$ charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1$\pm0.6$% and 84.1$\pm0.6$%, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation