Presentations from ICT 2015 in Lisbon

Building Apps Based on Open

(Spatial, Linked) Data

Tomáš Mildorf

[email protected]

University of West Bohemia in Pilsen

Programme

• Introduction - Tomas Mildorf

• SDI4Apps - Tor Gunar Overli

• Open Transport Net - Karel Charvat

• SmartOpenData - Jesus Estrada

• FOODIE - Karel Charvat

• Final discussion

DATA

APPS

INFORMATION

data

reinterpretable representation of

information in a formalized manner

suitable for communication,

interpretation, or processing

[ISO/IEC 2382-1:1993]

application

manipulation and processing of data in

support of user requirements

[ISO 19101:2002]

information

knowledge concerning objects, such as

facts, events, things, processes, or ideas,

including concepts, that within a certain

context has a particular meaning

[ISO/IEC 2382-1:1993]

Apps based on DATA

Open DATA

Spatial DATA

Linked DATA

Open Spatial Linked DATA

Smart DATA

DATA >>> APPS >>> INFORMATION

Different Communities

• Linked Data communities

• Open Data communities

• Spatial (Geographic) Data communities

Networking Session Supported by

The LO1506 project of the

Czech Ministry of Education,

Youth and Sports

Programme

• Introduction - Tomas Mildorf (UWB)

• SDI4Apps - Tor Gunar Overli (AVINET)

• Open Transport Net - Karel Charvat (HSRS)

• SmartOpenData - Jesus Estrada (TRAGSA)

• FOODIE - Karel Charvat (CCSS)

• Final discussion

Building Apps Based on Open (Spatial) Data – ICT 2015

Tor Gunnar Øverli, Asplan Viak Internet AS (Norway)

The project has received funding from the EU ICT Policy Support Programme as part of the Competitiveness and Innovation Framework Programme.

QUICK FACTS

Project title Uptake of Open Geographic Information Through Innovative Services Based on Linked Data

Short title SDI4Apps

Ref. number 621129

Funded under Competitiveness and Innovation Framework Programme - The Information and Communication Technologies - Policy Support Programme (CIP-ICT-PSP-2013-7)

Objective 2.2a Open Data experimentation and innovation building on geographic information

Total budget 4,070 Mil. EUR (2,035 Mil. EUR co-funded by the EU)

Duration April 2014 – March 2017

Coordinator University of West Bohemia, Czech Republic

Website http://sdi4apps.eu/

http://sdi4apps.eu/

SDI4APPS CONSORTIUM

Asplan Viak Internet as (NO) RTD Talos Limited (CY)

Baltic Open Solutions Center (LV) Scuola Superiore Sant’Anna (IT)

Czech Centre for Science and Society (CZ) Slovak Environmental Agency (SK)

e-Pro Group as (SK) Strategie Strutturali di Antonio Paterno’ & c. sas (IT)

European Regional Framework for Co-operation (GR)

The National Microelectronics ApplicationsCentre Ltd (IE)

Help Service Remote Sensing s.r.o. (CZ) Uhlava (CZ)

Hyperborea S.r.l. (IT) University of West Bohemia in Pilsen (CZ)

Masaryk University (CZ) Vidzeme Planning Region (LV)

Pronatur (SK) Zemgale Planning Region (LV)

18 partners8 European Countries

WHAT’S THE PROBLEM?

GENERAL IDEA OF SDI4APPS

SDI4APPS SOLUTION

A cloud platform for open data sharing through various interfaces including testing its viability through 6 pilots:

• PILOT I: Easy Data Access

• PILOT II: Open Smart Tourist Data

• PILOT III: Open Sensor Network

• PILOT IV: Open Land Use Map Through VGI

• PILOT V: Open INSPIRE4Youth

• PILOT VI: Ecosystem Services Evaluation

OPEN LAND USE MAP

• Harmonisation and integration ofheterogeneous land use and land cover data

• Re-using INSPIRE land use dataspecifications → transformation into a common data model

• Mapping different classifications → HILUCS

• Using linked data

• Uniform visualisation

• Corine Land Cover 2006

• Urban Atlas

• Czech cadastre

• Land Parcel Identification System – LPIS

• Spatial plans

• Other sources

Differentlevel ofdetail

Differentgeometry

OPEN LAND USE MAP

SPOI – Spatial Point of Interests

• Open and seamless SPOI data set, which is based on Linked data principles, contains over 4 million Points of Interest important for tourism from Europe, Africa and South East Asia

11

12



Danube Hackathon Bratislava 15. 10. 201513

OpenTransportNet

Karel Charvat

Help Service Remote Sensing

ICT2015

Lisbon 20.10.2015

2

Organisation Kick-off Representative

1. CORVE (Flemish

eGovernment

Agency)

Geert Mareels

Lieven Raes

2. IS-PracticeHugo Kerschot

Jiri Bouchal

3. IntrasoftAntonis Ramfos

Bapis Ipektsidis

4. 21c ConsultancySusie Ruston

Raluca Ionescu

5. Birmingham City

CouncilPhilip Edwards

6. iMinds

Shenja van der Graaf

Pieter Colpaert

Carina Veeckman

7. CEN GroupSteve Cross

Megan Cross

Organisation Kick-off Representative

8. Help Service –

Remote Sensing

Karel Charvát

Karel Charvát jr.

9. Issy MediaEric Legale

Laetitia Vaysse

10. EDIP

Luděk Bartoš

Jana Bartošová

Jan Martolos

11. University of West

Bohemia

Tomáš Mildorf

Karel Jedlička

Jan Ježek

12. ExigenAgris Snepts

Indulis Makens

13. AntwerpGerrie Smits

Steven Sterkx

14. Athens Technology

Centre

Eva Jaho

Sofia Vasilliou

3

CREATING SMART TRANSPORT SERVICES

BY FACILITATING THE RE-USE OF OPEN

GIS DATA

4

Data Hub

5

Data Hub

6

Data Hub

7

Data Hub

8

Data Hub

9

Data Hub

Thank you

More information:

[email protected]

Jesús Estrada

Grupo TRAGSA

[email protected]

• SmartOpenData has created a Linked Open Data set of tools

•to make public & voluntary GeoSpatial data resources on

rural areas - such as national parks.

•available to SMEs in a way that will enable them to create

new services & products.

• Based on the practical needs & experience of 5 Demonstration

Pilots

• SmartOpenData aims to help bridge the gap between

1.GeoSpatial Data - from the SDI/INSPIRE “world”•OGC (Open Geospatial Consortium) – standards setting

2.Linked Open Data (LOD) - from the Semantic Web “world”•W3C (World Wide Web Consortium) – collaborative movement

Project Overview

The Consortium

Industry

Academia

Public

Bodies

Duration: 24 meses

Started: End 2013

EU Contribution: 2.4 M €

SMEs

• Involves 16 partners from 9 countries 1.Public Bodies,2.Academic Researchers, 3.Industry4.SMEs

• Project started in November 2013 &

will be completed in two weeks.

• See www.smartopendata.eu21

1

3

1

3

3

1

1

The Consortium - II

• Environmental Conservation – Ireland

•Focused on biodiversity & habitats data for researchers & decision makers in management & conservation of the Burren & other National Parks.

• Water monitoring – Italy

•Will explore the role of aggregating information from different Open Data sources to provide up to date monitoring of water quality in Sicily.

• Forest sustainability – Czech Republic

•Forest site classification, sustainable management & utilisation of forest roads using the National Forest Inventory & Regional Plans for Development datasets.

• Environmental data reuse – Slovakia

•Will deploy two types of web applications to achieve reuse of environmental data & information in line with the European Open Data Strategy.

• Agroforestry Management – Spain & Portugal

•Will focus on building a web based collaborative Spatial Data Infrastructure to promote sustainable agroforestry management, environment protection, rural economic development, water management & drinking water protection.

Demonstration Pilots

... ... ...

Data Sources

Harmonisat ion of data Sources

Open Data Source Layer SmartOpenData System

Distributed Semantic Indexing

Administration and Notification

Distributed Data Access

Scenario for researchers Scenario for companies Scenario for end-users

ETL/Indexi

ng

Pipeline

Entity

Extraction

Pipeline

Semantic

Server

SirenDB

SPARQL-ED

Sefarad

Faceted Search

Notification Admin

Fro

nt-E

nd

Implemented Technical Architecture

SmartOpenData Services

• SmartOpenData

•is an integration of previously developed & available open components, •has been improved based on user operational feedback, •provides the following services:

• Discovery

•Metadata harvesting & Publishing.• Data services

•Distributed open data services•Registry services•GeoSPARQL tools •KML/KMZ

• Transformation

•Workflow management• Monitoring

• Access to External services

• Applications

• Semantic queries

• Social Networks & Media

text ... ...

External data Sources Local data Sources

text

Open Data Source Layer

Entity

Extraction

Pipeline

ETL/Indexi

ng

Pipeline

Semantic

Server

SirenDB

Internal Interfaces to be

documented

Front-End

Internal Interface to be

documented

Real or conceptual DB store to

be documented

SmartOpenData Data Flow

Thank You

Questions?

Jesús Estrada

[email protected]

+34 91 322 6693

1www.foodie-project.eu

FOODIE Farm-Oriented Open Data in EuropeCIP-ICT-PSP-2013-7 Pilot Type B

Karel Charvat

2

FOODIE Core Data Model class Foodie Core Data Model v 4.1 proposal

«featureType»

Agricultural and

Aquaculture Facilities

Model::Holding

«featureType»

Agricultural and Aquaculture Facilities Model::

Site

+ code :Identifier

+ geometry :GM_Object

+ activity :EconomicActivityNACEValue [1..*]

+ validFrom :DateTime

+ validTo :DateTime [0..1]

+ beginLifespanVersion :DateTime

+ endLifeSpanVersion :DateTime [0..1]

«voidable»

+ includesAnimal :FarmAnimalSpecies [0..*]

«dataType»


FarmAnimalSpecies

«voidable»

+ livestock :LivestockSpeciesValue [0..*]

+ aquaculture :AquacultureSpeciesValue [0..*]

«featureType»

Activ ity Complex::Activ ityComplex

+ inspireId :Identifier

+ thematicId :ThematicIdentifier [0..*]


+ function :Function [1..*]

+ userId :CharacterString

«voidable»

+ name :CharacterString [0..1]



«voidable, l ifeCycleInfo»


+ endLifespanVersion :DateTime [0..1]

«featureType»

Plot

+ code :Identifier



+ beginLifeSpanVersion :DateTime


+ geometry :GM_Object [1..*]

+ description :CharacterString [0..1]

+ originType :OriginTypeValue

«featureType»

Treatment

+ quantity :Measure [1..*]

+ tractorId :CharacterString [0..*]

+ machineId :CharacterString [0..*]

+ motionSpeed :Measure [0..1]

+ pressure :Measure [0..1]

+ flowAdjustment :Measure [0..1]

+ applicationWidth :Measure [0..1]

+ areaDose :DoseUnit [0..1]

+ formOfTreatment :FormOfTreatmentValue [1..*]

+ treatmentPurpose :TreatmentPurposeValue [0..*]

+ treatmentDescription :CharacterString [0..1]

«dataType»

NutrientsType

+ N :Measure [0..1]

+ P2O5 :Measure [0..1]

+ K2O :Measure [0..1]

+ MgO :Measure [0..1]

+ CaO :Measure [0..1]

+ S :Measure [0..1]

+ Zn :Measure [0..1]

+ Cu :Measure [0..1]

+ Fe :Measure [0..1]

+ B :Measure [0..1]

+ Mn :Measure [0..1]

+ Mo :Measure [0..1]

«codeList»

TreatmentPurposeValue

+ weed

+ pest

+ disease

«featureType»

CropSpecies

+ beginDate :Date

+ endDate :Date [0..1]

+ cropArea :GM_Object

+ cropSpecies :CropType [1..*]

+ production :ProductionType [0..*]

«featureType»

Product

+ productCode :CharacterString [0..*]

+ productName :CharacterString [1..*]

+ productType :CharacterString

+ productSubType :CharacterString [0..*]

+ productKind :ProductKindValue


+ manufacturer :CI_ResponsibleParty [1..*]

+ nutrients :NutrientsType [0..*]

+ safetyInstructions :CharacterString [0..1]

+ storageHandling :CharacterString [0..1]

+ registrationCode :CharacterString [0..*]

+ registerUrl :URL [0..*]

«featureType»

SoilNutrients

+ nutrientName :GenericName

+ nutrientAmount :Measure

+ nutrientMeasure :CharacterString

«codeList»

ProductKindValue

+ organic

+ mineral

«dataType»

SoilTextureType

+ clay :Percent

+ silt :Percent

+ sand :Percent

«dataType»

ProductionType

+ productionDate :Date

+ variety :CharacterString

+ productionAmount :Measure

+ productionAnalysis :ProductionAnalysisType [0..*]

«dataType»

ProductionAnalysisType

+ productionAnalysisDate :Date

+ property :Measure

«codeList»

OriginTypeValue

+ manual

+ system

«featureType»

Alert

+ code :Identifier

+ type :CharacterString [1..*]


+ checkedByUser :Boolean

+ alertDate :Date

+ alertGeometry :GM_Object

«featureType»

Interv ention

+ type :CharacterString

+ description :CharacterString

+ notes :CharacterString [0..1]

+ status :CharacterString

+ creationDateTime :DateTime

+ interventionStart :DateTime

+ interventionEnd :DateTime [0..1]

+ interventionGeometry :GM_Object [1..*]

+ supervisor :CI_ResponsibleParty [0..1]

+ operator :CI_ResponsibleParty [0..*]

+ evidenceParty :CI_ResponsibleParty [1..*]

«featureType»

TreatmentPlan

+ treatmentPlanCode :CharacterString [0..*]

+ description :CharacterString [1..*]


+ campaign :TM_Period [1..*]

+ treatmentPlanCreation :DateTime


«featureType»

ProductPreparation

+ productQuantity :Measure

+ solventQuantity :Measure [0..*]

+ safetyPeriod :TM_Period

«dataType»

Activ eIngredients

+ code :CharacterString [0..1]

+ ingredientName :CharacterString

+ ingredientAmount :Measure

«codeList»

DoseUnit

+ minimumDose :Measure

+ maximumDose :Measure

«codeList»

FormOfTreatmentValue

+ manual

+ applicationMachine

+ aerial

«featureType»

ManagementZone

+ code :Identifier

+ validFrom :DateTime [0..1]





+ notes :CharacterString

+ dateOfAnalysis :DateTime [0..*]

«featureType»

SoilType

+ soilType :CharacterString [1..*]

«featureType»

SoilTexture

+ soilTexture :SoilTextureType [1..*]

«featureType»

pH

+ pH :Measure [1..*]

«featureType»

OrganicMatter

+ organicMatter :Percent

«featureType»

ElectricConductiv ity

+ electricConductivity :Measure [1..*]

«featureType»

ZonePolygon

+ area :Measure

«dataType»

CropType

+ name :CharacterString

+ scientificName :CharacterString



+ seedingAdvice :CharacterString

+ harvestingAdvice :CharacterString

0..*

1..*

+contains

1..*HoldingSites

1..*

0..*

+containsZone

0..*

+HoldingPlot

0..*

+containsPlot 1..*

HoldingPlots

0..*

0..1 0..1

0..*

0..*

+crop 0..*

• Data Model compliant to:• Directive 2007/2/EC (INSPIRE)

• ISO standards 19100 series

• Open and scalable

3


«featureType»

Agricultural and


Model::Holding

«featureType»


Site

+ code :Identifier







«voidable»


«dataType»


FarmAnimalSpecies

«voidable»



«featureType»







«voidable»







«featureType»

Plot

+ code :Identifier








«featureType»

Treatment












«dataType»

NutrientsType

+ N :Measure [0..1]





+ S :Measure [0..1]




+ B :Measure [0..1]



«codeList»


+ weed

+ pest

+ disease

«featureType»

CropSpecies

+ beginDate :Date





«featureType»

Product













«featureType»

SoilNutrients




«codeList»

ProductKindValue

+ organic

+ mineral

«dataType»

SoilTextureType

+ clay :Percent

+ silt :Percent

+ sand :Percent

«dataType»

ProductionType





«dataType»



+ property :Measure

«codeList»

OriginTypeValue

+ manual

+ system

«featureType»

Alert

+ code :Identifier




+ alertDate :Date


«featureType»

Interv ention












«featureType»

TreatmentPlan







«featureType»

ProductPreparation




«dataType»

Activ eIngredients




«codeList»

DoseUnit



«codeList»


+ manual


+ aerial

«featureType»

ManagementZone

+ code :Identifier








«featureType»

SoilType


«featureType»

SoilTexture


«featureType»

pH


«featureType»

OrganicMatter


«featureType»



«featureType»

ZonePolygon

+ area :Measure

«dataType»

CropType







0..*

1..*

+contains

1..*HoldingSites

1..*

0..*

+containsZone

0..*

+HoldingPlot

0..*

+containsPlot 1..*

HoldingPlots

0..*

0..1 0..1

0..*

0..*

+crop 0..*

Intervention attribute Value

Type tillage

Status ongoing

Intervention start 2015-04-22

Supervisor John First, senior manager, phone 7435

… …

4


«featureType»

Agricultural and


Model::Holding

«featureType»


Site

+ code :Identifier







«voidable»


«dataType»


FarmAnimalSpecies

«voidable»



«featureType»







«voidable»







«featureType»

Plot

+ code :Identifier








«featureType»

Treatment












«dataType»

NutrientsType

+ N :Measure [0..1]





+ S :Measure [0..1]




+ B :Measure [0..1]



«codeList»


+ weed

+ pest

+ disease

«featureType»

CropSpecies

+ beginDate :Date





«featureType»

Product













«featureType»

SoilNutrients




«codeList»

ProductKindValue

+ organic

+ mineral

«dataType»

SoilTextureType

+ clay :Percent

+ silt :Percent

+ sand :Percent

«dataType»

ProductionType





«dataType»



+ property :Measure

«codeList»

OriginTypeValue

+ manual

+ system

«featureType»

Alert

+ code :Identifier




+ alertDate :Date


«featureType»

Interv ention












«featureType»

TreatmentPlan







«featureType»

ProductPreparation




«dataType»

Activ eIngredients




«codeList»

DoseUnit



«codeList»


+ manual


+ aerial

«featureType»

ManagementZone

+ code :Identifier








«featureType»

SoilType


«featureType»

SoilTexture


«featureType»

pH


«featureType»

OrganicMatter


«featureType»



«featureType»

ZonePolygon

+ area :Measure

«dataType»

CropType







0..*

1..*

+contains

1..*HoldingSites

1..*

0..*

+containsZone

0..*

+HoldingPlot

0..*

+containsPlot 1..*

HoldingPlots

0..*

0..1 0..1

0..*

0..*

+crop 0..*

Treatment attribute Value

Intervention type herbicide application

Status ongoing

Intervention start 2015-04-22

Supervisor John First, senior manager, phone 7435

Treatment quantity 70 litres

Application width 25 meters

Form of treatment Application machine

Product Roundup®

… …

5

• Core Data Model• Management zones

• Interventions

• Treatments

• …

• Sensor Data Model• ISO 19156 O&M

• also VGI

SENSOR Data Models

<swe:encoding>

<swe:TextEncoding decimalSeparator="." tokenSeparator="," blockSeparator="@@"/>

</swe:encoding>

<swe:values>2014-10-

28T18:47:07+0100,urn:ogc:object:feature:tom:foi0792,24.61,49.2241229,16.5398454@@2014-10-

28T19:00:00+0100,urn:ogc:object:feature:tom:foi0792,24.06,49.2241229,16.5398454@@2014-10-

28T20:00:00+0100,urn:ogc:object:feature:tom:foi0792,22.87,49.2350641

16.5770019@@</swe:values>

</swe:DataArray>

</om:result>

<om:result>

<swe:DataArray>

<swe:elementCount>

<swe:Count>

<swe:value>5</swe:value>

</swe:Count>

</swe:elementCount>

<swe:elementType name="Components">

<swe:DataRecord>

<swe:field name="Time">

<swe:Time

definition="http://www.opengis.net/def/property/OGC/0/Samplin

gTime">

<swe:uom xlink:href="http://www.opengis.net/def/uom/ISO-

8601/0/Gregorian"/>

</swe:Time>

</swe:field>

<swe:field name="feature">

<swe:Text definition="urn:ogc:data:feature"/>

</swe:field>

<swe:field name="temperature">

<swe:Quantity

definition="urn:ogc:def:phenomenon:tom:temperature">

<swe:uom code="°C"/>

</swe:Quantity>

</swe:field>

<swe:field name="latitude">

<swe:Quantity definition="urn:ogc:def:latitude">

<swe:uom code="decimalDegrees"/>

</swe:Quantity>

</swe:field>

<swe:field name="longitude">

<swe:Quantity definition="urn:ogc:def:longitude">

<swe:uom code="decimalDegrees"/>

</swe:Quantity>

</swe:field>

</swe:DataRecord>

</swe:elementType>

6

• Core Data Model• Management zones

• Interventions

• Treatments

• …

• Sensor Data Model• ISO 19156 O&M

• also VGI

• Transport Data Model• OSM for navigation

TRANSPORT Data Models

edge

edge

vertex

vertexvertex

edge

edge edge

edge

Road segment attributes

Identifier, e.g. http://foodie-project.eu/dat/tn/654787

National code, e.g. 43

Road width, e.g. 5 meters

Maximum height, e.g. 2.1 meters

Maximum weight, e.g. 2 tons

Speed limit, e.g. 20 km·h-1

Surface category, e.g. asphalt, unpaved,…

HAZMAT limitation, i.e. flammable/explosive/corrosive/toxic/oxidizing

Fuel consumption: tillage (l/h)

Fuel consumption: detail (l/h)

9

FOODIE available open data – currently covering the Czech Republic

10

Site Specific Crop Management

Periodic satellite remote sensing• for identification of spatial variability and capturing the

dynamics of vegetation growth, both at medium level of spatial resolution

• Suggested satellite survey is based on the free available data of Landsat 8 or in 2015 launched Sentinel-2.

• The main information are vegetation indices NDVI and EVI• The absolute values of VI, their relative to mean value of the

field and change detection will be implemented for assessment of crop stands and delineating of management zones.

11

Example of L8 dataset for the Czech pilot farm

LC81900262015127LGN00LC81890262015200LGN00

LC81900262015143LGN00= not reliable for planning of VRA

Cloud coverageover farm area

12

Coverage of all of the Czech Republic

13

Pilot

Estimation of field cropvariability based on the recentyears Landsat images and EVI2 index

FOODIE Czech pilot farm

14

Landsat 8 OLI images

crop development within 68-ha (spring barley) and 62-ha (winter wheat) fields in 2014 represented by NDVI

Presentations from ICT 2015 in Lisbon

Data & Analytics

Transcript of Presentations from ICT 2015 in Lisbon