OpenEarth

components in Data Science

some examples

Gerrit Hendriksen

Willem Stolte, Frank Keppel, Maarten Pronk, Dave de Koning,

Matthijs Schaap, Joan Sala, Anna van Gils, Kees den Heijer, Fedor

Baart, Johan Beekhuizen, Giorgio Santinelli, Almar Joling, Rens van

de Bergh, Amrit Cado van der Lelij, André Speelmans, Arthur van

Rooij, ….

A small survey to start with

Go to Kahoot.it with your smartphone!

What is OpenEarth?

OpenEarth consists of Open Source tools to transform and

store your data in a standardized format. This enables you to

easily:

• Show the data in online viewers

• Help others find your data in online catalogues

• Share the data through an online download

• Store the changes in the data (version control)

Benefits of OpenEarth Data management tools

Data Stages

tailored

data

> WCS

> WFS

> SOS

> SOAP > netCDF-CF-

OPeNDAP

> ISO SQL–

PostGIS > SVN

> GIT

> http

> ftp

> KML

> WMS

> WFS

> CSW graphics

of data

standard

data

raw

data

catalogue

of data

work done

on server

work done

on client

what

where

when

who

why

how

…

data URLs

smart phone & tablet users scientists professionals

Techniques - Basics

Techniques - Basics

• OpenEarth:

• Open standards (OGC WxS)

• Open data

• Open source

• Web technology:

• Dissemination

• Interface between users and data

• Geoserver (OGC WxS)

• WPS

• Geonetwork (data discovery)

storage

(geo)database

OGC WxS services

dissemination

THREDDS netCDF

Some examples

Where:

- Data management is unified

- Reuse of information

- Reuse of tools

Side information:

- Target audience

- Which data is used

- Which protocols

FAST

FAST

Description:

- Assessment tool

Stakeholders:

- Decision makers

- Education

Techniques:

- WMS

- WCS

- WPS

- XBeach modelling

Data: Global, Regional

Expert version with regional data

OET-WIS

Description:

Data management system for data intensive projects with:

- Time series (models, loggers, …)

- Geo data in various kinds

Stakeholders:

- Researchers, Clients

Data:

- Global, regional, local

Techniques:

- OGC services, FEWS, statistics, Mobile Apps

OET-WIS

storage

(geo)database

OGC WxS services

dissemination

THREDDS netCDF

FEW

S functions

Models

(Inter)national (I)WRM projects

WIS animated results

Waterviewer + NO3-app

Hydrological Statistical Functions

Description:

- Hydrological statistical functions enabled by WPS builder

Stakeholders:

- Researchers, end users

Data

- Timeseries, geospatial

Techniques:

- WPS, OGC-WxS, Statistics

Hydrological Statistical Functions

Hydrological Statistical Functions

Subsurface data handling

storage

(geo)database

OGC WxS services

THREDDS netCDF

dissemination

OGC WxS services

OGC WxS services (WPS)

Subsurface Data Handling

Description:

- Central place for national (ground) water modelling data

Stakeholders:

- Researchers, Modellers, Waterboards, National government

Data

- National data for groundwater modelling and model results

Techniques:

- WPS, OGC-WxS

Subsurface data handling

Subsurface Examples - Infoline

Subsurface Examples - Infoline

Subsurface Examples - Infoline

dissemination

TNO - REGIS

THREDDS netCDF

OGC WxS services

OGC WxS services (WPS)

LHM/NHI

(GMDB)

THREDDS netCDF

OGC WxS services

Subsurface Examples - Watersoils

Description:

- Risk assessment tool for water infrastructure

- Quick access to sub surface data

Stakeholders:

- Governmental researchers/engineers

Techniques:

- OPeNDAP

- WPS

Data:

- national, regional data

Subsurface Examples - Watersoils

Subsurface Examples - Watersoils

Dynamic Reporting

Description:

- Quick access to high level information on trends in …

Stakeholders:

- End users at governmental level

Techniques:

- (spatial)database

- R-shiny

Data:

- National, regional data

Reporting made dynamic

Reporting made dynamic

Future work

Extensions:

- Reporting functions

- Statistical functions

- Running models

- Data entry modules

Attention to:

- User management

- security

Message

Data acquisition

• Standardisation of data and metadata

• Standardised Processes to ‘create’/reuse data

• 3 clicks …

• Easy information dissemination

Main components of OpenEarth data systems:

• Central storage

• Knowledge exchange (i.e. statistical tools, Infoline)

• Highly standardised data formats

• Meta data

• Information and viewing services