Main Page

From World Port Hackathon Api's
Jump to: navigation, search

Welcome!

Welcome on the wiki from the World Port Hackathon. This wiki contains information about the datasets, API's and references to the datasets. These datasets can only be used for World Port Hackathon purposes. For each data source a separate page is implemented into the wiki. Each page describes what the datasource offers and how you can use it. A division has been made between static and dynamic data. Furthermore, for dynamic data, historic and live feeds are provided. Of course, you probably find more data sources on the internet itself.

Good luck!

PS. Some of the datasets are in dutch, we are sorry for that. If there are any problems please contact us @ contact@worldporthackathon.com

The jury process

Downlaod the jury proces via this link https://worldporthackathon.com/wp-content/uploads/2017/09/Jury-selection-of-WPH2017.pdf

Data sources

Data sources per challenge

Challenge 1: Infrastructure & Assets: predicting the future

The amount of dredging in different harbours of Rotterdam between 1913 and 2017

Dredge data from January 2017 until July 2017, with location, amount and the time it took to dredge.

The by Rijkswaterstaat registered water levels in the Port of Rotterdam between 2006 and June 2017. Also data from the supply of water from the inland via the Rhine and the Maas in csv-format.

Challenge 2: Cascading effects in the network of networks: the weakest link

Data for this challenge is on a USB-drive during the Hackathon. Ask one of the World Port Hackathon crew members for more information.

Challenge 3: Energy: getting the picture

A document with all facts & figures about the petrochemical part of The Port of Rotterdam

Challenge 4: Logistics & Mobility: unlocking the optimal

For the WPH-Challenge Logistics & Mobility, De Verkeersonderneming (and her Partners Flitsmeister and Wegstatus.nl) have been able to provide some data that may be helpful. Furthermore we have made a list of some open data sources that may be of use.

Provided data sources:

Incidents with cars and trucks

A set of incident notification in Waze app for week 21 and 22 of 2017

These three datasets are available via World Port Hackathon crew:

  • A set of floating car data for the Rotterdam region (mainly freeways) provided by Flitsmeister app for week 21 and 22 of 2017
  • MTM logging of the systems above the roads
  • Some NDW-historical data for week 21 and 22 of 2017, including status reports

Open Data that may be of use:

Assetmanagement data:

  • Soil data (the height of the soil) from the Port of Rotterdam area
  • MARS data: test data (no real data) from the MARS system that is being used to monitor dredge and supplementation activities (where are the ships and what are the doing)
  • WAB-Info data: results of monsters taken from soil in Rotterdam area

Assetmanagement data

Challenge 5: Autonomous Shipping: on the move

File:Rr-ship-intel-aawa-8pg.pdf Autonomous Shipping - The Next Steps

Challenge 6: Data, Documents & Integrity: audit trail

Binnenbrengen


  • Containernumber
  • Container contents
  • Time of arrival




Transport by customs


  • MRN-number
  • Container number (sometimes license plate)
  • Container contents
  • Time of departure
  • Destination
  • Time of arrival

Uitgaan


  • MRN-number

  • Country of destination
  • Country of origin
  • Transport type
  • Container (y/n)
  • Chamber of export
  • Goods code
  • Container number

deepsea_hackathon_v3.csv contains data about incoming (import) vessels to the port

'Visit_Call_Reference_Number' - Unique reference of the vessel visit in the port
'Visit_ETA' - Expected Time of Arrival
'Visit_ATA' - Actual Time of Arrival
'Visit_ETD' - Estimated Time of Departure
'Visit_ATD' - Actual Time of Departure
'Vessel_Max_Draught' - Maximum draught of the vessel belonging to the visiting vessel
'Vessel_Full_Length' - Length of the vessel belonging to the visiting vessel
'Vessel_Max_Width' - Width of the vessel belonging to the visiting vessel
'Start_Port' - The previous port the vessel has visited
'Equipment_Number' - Number of the equipment (container)
'Container_Empty_Ind' - Is the container empty? Yes = Empty, No = Loaded
'Container_Discharge_Time' - Actual time of discharge of the equipment from the vessel
'Container_Type_Descr' - Description of container type
'Container_ISO_Code' - ISO code of container type
'Items_Gross_Weight' - gross weight of cargo
'Bill_of_Lading_Code' - Reference number of booking, multiple containers within single shipment can be identified (NOTE: numbers used are not actual numbers.)
'Dangerous_Goods_Ind' - Does the container contain goods registered as "dangerous goods"? Y= Dangerous goods, N=No dangerous goods
'Comodity_Types_Code' - Classification code of the cargo
'Transshipment_Ind' - is the equipment labeled as transshipment (will leave port through another deepsea vessel, not to hinterland)

hinterland_loading_hackathon_v3.csv contains data about hinterland processing of cargo entering the port through deepsea ships (=import)

'Container_Number' - unique identifier of the equipment
'Mode_of_Transport' - Mode of hinterland transport, i.e. Truck (road), train (rail), Barge
'ETA_Visit' - Expected time of arrival of the transporter (rail/road/barge) collecting the cargo
'Actual_Loading_Time' - Loading time of the equipment onto the hinterland transport
'Visit_ID_Number' - unique identifier of the voyage to the port
'Stevadore_Visit_ID_Number' - unique identifier of the visit to a specific pickup point (multiple visits per voyage possible)
'Voyage_Number' - unique identifier of the voyage to the port

======================================================================================================================

NOTE: please make sure date/time fields are processed correctly. All data should be within the timeframe of ~mid 2016 to ~mid 2017

DOWNLAOD LINK: https://drive.google.com/drive/folders/0BxRI5je2eSjxUERKLWlxLUdUNFk

Previous years datasources

Bridges

Dynamic data sources

Live feeds

Static Data Sources

Customs

Information Collections

Historical datasets

July 2015
July 2014
September 2013