User:RailML Coord Governance: Difference between revisions
No edit summary |
(Pattern for railML 3 use cases for timetable added) |
||
Line 1: | Line 1: | ||
== Vasco Paul Kolmorgen == | |||
railML-Koordinator | railML-Koordinator | ||
Tel. +49 351 46676939 | |||
01069 Dresden | |||
Germany / {{Deu|Deutschland}} / {{Fra|Allemagne}} | |||
== Vorlage für railML<sup>®</sup> 3 use cases im timetable-Schema == | |||
'''Use case / {{Deu|Anwendungsfall}} / {{Fra|Scénario d’utilisation}}:''' | |||
''An expressive name in English; {{Deu|Ein aussagekräftiger Name in Deutsch}}; {{Fra|nom descriptif en Francais}}'' | |||
'''Description / {{Deu|Beschreibung}} / {{Fra|Description}}''' | |||
''What is the application behind the use case? Which data are required? Who or which tool/application provides these data? Which data are not included (if not obvious)? Define the boundaries of the use case and the relevant data. (max. 200 words, English)'' | |||
'''Data Flows and Interfaces / {{Deu|Datenflüsse und Schnittstellen}} / {{Fra|Flux de données et interfaces}}''' | |||
''Which data flows (from/to the use case application) exist? Which data and process interfaces exist?'' | |||
'''Interference with other railML<sup>®</sup> schemas / {{Deu|Interferenz mit anderen railML<sup>®</sup>-Schemen}} / {{Fra|Interaction avec autres schemas railML<sup>®</sup>}}''' | |||
* ''infrastructure'' | |||
* ''rolling stock'' | |||
* ''interlocking'' | |||
* ''other ..............'' | |||
'''Characterizing Data / {{Deu|Charakterisierung der Daten}} / {{Fra|Caractérisation des données}}''' | |||
This section serves to specify the required data regarding certain aspects. | |||
<u>How often do the data change (update)?</u> | |||
*''static (not changing)'' | |||
*''yearly'' | |||
*''regular changes'' | |||
*''monthly'' | |||
*''weekly'' | |||
*''daily'' | |||
* ''realtime (seconds)'' | |||
<u>How big are the data fragments to be exchanged (complexity)?</u> | |||
*''tiny (attribute)'' | |||
*''very small (element)'' | |||
*''small (operational point)'' | |||
*''big (station/ yard)'' | |||
*''huge (region)'' | |||
*''whole data set (network)'' | |||
<u>Which views are represented by the data (focus)?</u> | |||
*''Long term planning (eg. for infrastructure dimensioning)'' | |||
*''Mid term planning (eg. for yearly timetable disposition)'' | |||
*''Short term planning (eg. for trackworks)'' | |||
*''Real term planning (eg. for dispatching)'' | |||
*''Statistics'' | |||
*''Fare collection'' | |||
*''Passenger information'' | |||
*''...'' | |||
<u>Which specific infrastructure data do you expect to receive/send (elements)?</u> | |||
''Fill in your application-specific data structure elements, which you want to see modelled in railML 3.''<br> | |||
''Please define them as detailed as possible, the length isn't limited here.'' |
Revision as of 10:59, 26 January 2015
Vasco Paul Kolmorgen
railML-Koordinator
Tel. +49 351 46676939
01069 Dresden
Germany / Deutschland /
Vorlage für railML® 3 use cases im timetable-Schema
Use case / Anwendungsfall / :
An expressive name in English; Ein aussagekräftiger Name in Deutsch;
Description / Beschreibung /
What is the application behind the use case? Which data are required? Who or which tool/application provides these data? Which data are not included (if not obvious)? Define the boundaries of the use case and the relevant data. (max. 200 words, English)
Data Flows and Interfaces / Datenflüsse und Schnittstellen /
Which data flows (from/to the use case application) exist? Which data and process interfaces exist?
Interference with other railML® schemas / Interferenz mit anderen railML®-Schemen /
- infrastructure
- rolling stock
- interlocking
- other ..............
Characterizing Data / Charakterisierung der Daten /
This section serves to specify the required data regarding certain aspects.
How often do the data change (update)?
- static (not changing)
- yearly
- regular changes
- monthly
- weekly
- daily
- realtime (seconds)
How big are the data fragments to be exchanged (complexity)?
- tiny (attribute)
- very small (element)
- small (operational point)
- big (station/ yard)
- huge (region)
- whole data set (network)
Which views are represented by the data (focus)?
- Long term planning (eg. for infrastructure dimensioning)
- Mid term planning (eg. for yearly timetable disposition)
- Short term planning (eg. for trackworks)
- Real term planning (eg. for dispatching)
- Statistics
- Fare collection
- Passenger information
- ...
Which specific infrastructure data do you expect to receive/send (elements)?
Fill in your application-specific data structure elements, which you want to see modelled in railML 3.
Please define them as detailed as possible, the length isn't limited here.