Big Data for Travel Demand Modelling (Registro nro. 6682)

000 -LEADER
fixed length control field 02672nam a22004097a 4500
001 - CONTROL NUMBER
control field 00006682
003 - CONTROL NUMBER IDENTIFIER
control field ES-MaONT
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20211006062654.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 210901s2021 fr db||f t|||i00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789282169155 (PDF)
024 ## - OTHER STANDARD IDENTIFIER
Source of number or code doi
Standard number or code 10.1787/08378837-en
040 ## - CATALOGING SOURCE
Original cataloging agency ES-MaONT
245 00 - TITLE STATEMENT
Title Big Data for Travel Demand Modelling
Remainder of title : summary and conclusions
Statement of responsibility, etc. / International Transport Forum
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. París :
Name of publisher, distributor, etc. OECD Publishing,
Date of publication, distribution, etc. 12 August 2021
300 ## - PHYSICAL DESCRIPTION
Extent p.
Dimensions ; 1 documento PDF
336 ## - CONTENT TYPE
Content type term texto (visual)
Source isbdcontent
337 ## - MEDIA TYPE
Media type term electrónico
Source isbdmedia
338 ## - CARRIER TYPE
Carrier type term recurso en línea
Source rdacarrier
490 ## - SERIES STATEMENT
Series statement ITF Roundtable Reports
Volume/sequential designation ; 186
520 ## - SUMMARY, ETC.
Summary, etc. This report examines how big data from mobile phones and other sources can help forecast travel demand. It identifies the strengths and potential use cases for big data in transport modelling and mobility analysis, presents ways to address potential biases, commercial sensitivities and privacy threats and offers recommendations for governance arrangements that make data sharing easier. Transport planners use big data from mobile network operators, smartphone apps and smart cards to complement traditional travel surveys. The new data sources help transport planners understand and forecast travel demand. The study recommend 1) Collect data only for defined purposes and only the minimum required 2) Develop guidelines for the use of big data in transport models 3) Enable the collection of location data through smartphone apps 4) Protect privacy through multiple solutions 5) Define a roadmap for household travel surveys 6) Design and test smartphone-assisted household travel surveys 7) Leverage artificial intelligence for data mining 8) Create and promote a recognised data steward function in the public and private sectors 9) Invest in the data-related training of the public-sector workforce
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Tecnologías habilitadoras digitales
9 (RLIN) 18
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term Big data
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term demanda viajes
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term gobernanza
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term intercambio datos
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term movilidad
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term pronóstico
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term teléfonos móviles
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term transporte
653 ## - INDEX TERM--UNCONTROLLED
Uncontrolled term viajes
710 ## - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element International Transport Forum
9 (RLIN) 3475
710 ## - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Organización de Cooperación y Desarrollo Económico
9 (RLIN) 2843
830 ## - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title ITF Roundtable Reports
9 (RLIN) 3476
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.itf-oecd.org/sites/default/files/docs/big-data-travel-demand-modelling.pdf
Nonpublic note Abierto
Link text Acceso al documento
Electronic format type pdf
856 42 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://www.oecd-ilibrary.org/transport/big-data-for-travel-demand-modelling_08378837-en
Nonpublic note Abierto
Link text Más información
Electronic format type pdf
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Koha item type Informes
Existencias
Withdrawn status Lost status Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type Public note
      Acceso libre online Colección digital CDO CDO   01/09/2021   1000020176875 01/09/2021 01/09/2021 Informes pdf
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