emerging semantic web technologies for eo value- chains...
TRANSCRIPT
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Emerging Semantic Web Technologies for EO Value-chains; Enabling Downstream Service Providers using Linked-Open Data (LOD)
15.11.2018 phi-week 2018
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Copernicus App Lab
The vision of linked data is to go from a Web of documents to aWeb of data:
• Unlock data dormant in their silos• Make it available on the Web• Interlink it with other data
This is especially useful for Earth Observation data.
Why Linked Data?
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Copernicus App Lab
Semantic Web
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Copernicus App Lab
Linked Open Data Cloud
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Copernicus App Lab
Innovation
• Provision of Copernicus linked-open data (LOD) via onlineservices
• Improved data access via a streaming data library (SDL)• Tools for semantic linkage of Copernicus data with other
societal or business information
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The designation “Greenest capital” is a sought-after trophy, but how to establish
and validate such a claim?
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Use case: “What is Europe's greenest capital?”
Being ‘green’ brings many benefits for city marketing. Some of those benefits are listed below:● Increase in tourism● Positive international media coverage worth millions of euro● Increase in international profile, networking and new alliances● New jobs – green capitals have successfully exported their green products, processes and services● More emphasis on environmental projects through sponsorship and grants● Momentum to continue improving environmental sustainability● Boost in local pride and feeling of belonging● Enhancement of culture and the arts● Green vegetation reduces heat island-effects
The designation of being the “Greenest capital” is therefore a sought-after ‘trophy’, but how to validate such a claim?
(e.g. a Google search for “What is Europe's greenest city?” shows a variety of claims)
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Use case: “What is Europe's greenest capital?”
The designation “Greenest capital” may be seen from Space, e.g. using Copernicus Land Monitoring, provided the question is rephrased as follows:
But: what defines the city boundary of a captial, and what defines its greenness?
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Use case: “What is Europe's greenest capital?”
Definition:
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Use case: “What is Europe’s greenest captial?”
before AppLab:approximate city boundaries by drawing a buffer
around a city centre (lat,lon)
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Use case: “What is Europe’s greenest captial?”
before AppLab:City boundaries by on-screen digitization
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Use case: “What is Europe’s greenest capital?”
after AppLab:Obtain actual city boundaries from LOD (WP4), e.g. sourced from OSM offered as GeoTriples:
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Exploring data, Adding value, Publishing info
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Exploring and Discovering Data
Combine and Visualize(e.g., Mobile and Web)
Ramani Cloud Analytics
Discover Complementary Linked Open Data Sources
Earth Observation Linked Data Cycle
Streaming Data Library (SDL) Web-interface
OPeNDAPInstalled at EEs
(Geo)SPARQL-Endpoints
Subsetting and Derived Products
Accessing EO data
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Exploring and Discovering Data
Combine and Visualize(e.g., Mobile and Web)
Ramani Cloud Analytics
Discover Complementary Linked Open Data Sources
Earth Observation Linked Data Cycle
Streaming Data Library (SDL) Web-interface
OPeNDAPInstalled at EEs
(Geo)SPARQL-Endpoints
Subsetting and Derived Products
Accessing EO data
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Results task 3.3: Web-interface
Web interface has been expanded to support aone-stop-shop:● Supports discovery (text search)and
exploration of datasets (map view)● Provides basic filtering options● Provides UI for SDK (scripting with functions,
documentation) with illustrative example to facilitate downstream service provider
to builld their own add-ons (workflows).
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Text-based search
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Graphical data discovery
Live view
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Web interface for visual discovery and exploration
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Data by Source (Link)
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Exploring and Discovering Data
Combine and Visualize(e.g. Mobile and Web)
RAMANI Cloud Analytics
Discover Complementary Linked Open Data Sources
Earth Observation Linked Data Cycle
Streaming Data Library (SDL) Web-interface
OPeNDAPInstalled at EEs
(Geo)SPARQL-Endpoints
Subsetting and Derived Products
Accessing EO data
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Get Metadata (getMetadata) from Ramani (click for an example)
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Subsetting by time and space
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Server-side Analytics• App Lab Analytics (SDK for downstream service providers)
• Broad range of analytics available• SDK for downstream service providers• Fiunctions for supporting the use case:
■ Monthly average■ Yearly anomalies■ Spatial average■ Temporal filter
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SDL scripting language (SDLS)
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Server-side Analytics
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Server-side Analytics
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Server-side Analytics
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Server-side AnalyticsAnalytics e.g. to reveal anomalies in Air temperature (2m), sourced from the
ERAInterim reanalysis product,Copernicus Climate Change service
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Greenest pixel in Europe Live View
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Greenest pixel in Europe; variance in time
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EO value-chains with micro-remitances on a blockchain
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Consuming data in your application
➔ Use API to directly consume the data in your app➔ Available for several development platforms◆ Android◆ Javascript◆ NodeJS◆ iOS➔ Different data access methods◆ OPeNDAP link◆ LayerID➔ Many different return types both text and
images➔ Maps-API ontology to make API logic explicit
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Air Temperature Anomalies Live View
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What is next?Build your App, expanding beyond urban ‘greenness’...
Consider other relevant ‘urban well-being’ aspects. such as air quality from COPERNICUS Atmosphere (here rendered in an augmented reality-app).
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Maps-API
On-screen demos with sample App to guide App-developers
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What is next?Expand on this ‘greenest capital’ use case together with us by, for example:
● Rank-order Europe’s capitals by ‘greenness’ (using other LOD, WP4), i.e. to arrive at a top-3 and a ‘winner’.
● Expand beyond urban land-cover, for example by adding other relevant aspects to ‘well-being’ in cities (e.g. sustanianbility, air quality, micro-climate in relation to heat island-effects, demographics and heat-wave casualties) to allow for a more holistic approach in assessing who is the ‘greenest capital’ of Europe. We even support ‘what-if’ scenarios, e.g. does rainfall in Paris change if the sea-surface or land-surface temperature elsewhere becomes warmer?
● In competing for the trophy ‘greenest capital of Europe’, what infographic or media exposure works best for city marketing purposes? Imagineer new ways of giving this a spin.
● Explore within-city patterns, discover relationships aka correlations between datasets
● Explore what UIX works best to market ‘greenest capital of Europe’ claims?
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Fact-checking claims using triangulation
Greenest European metropolis - population above 2M, only considering ‘greenness’:The greenness was evaluated w i th the Norm al ized Di f ference Vegetat ion Index and al lows com par ison am ong the 43 analyzed capi talsht tps:/ / phi l ippgaer tner .gi thub.io/2017/ 10/ european- capi tal -greenness- evaluat ion/
Fact?
Valida t e an y cla im s of green es t cap it a l o r cit y by a llowin g sea rch en gin es t o fin d you r fact - ch ecks (e .g . u s in g sch em a .org’s r eviewCla im s t yp e, a s p a r t o f t h e JSON- LD- sn ip p et cr ea t ed by Ap p Lab’s s em an t ica lly en r ich ed MAProom , for va lida t in g cla im s by o t h er jou rn a lis t s / webs it es for bein g ‘green es t ’)
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who validates or reviews claims (i.e. being the ‘greenest’ capital)?
?
Here ‘ Greenness’ as key KPI , and the m ethods used to calculate th is, are disputed by others and even deem ed as “ cr im inal ly m isleading” .
But who establ ishes the ‘ t ruth’ ?
Or f iction...
Peer-reviewing claims “Europe's greenest capital?”...
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how can one review such claims (i.e. who is the ‘greenest capital 2018’)?
A web of docum ents is not enough, a web of data helps to t r iangulate the ‘ t ruth’ !
Semantics WCS 3.0
Example: facilitating robust peer-review workflows
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Working with Semantic Web Technologies
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Benefits of Linked Data TechnologiesApproach without Copernicus App Lab Tools
● Download all datasets from their respective repositories
● Understand the data● Make conversions to comply with
standards● Align data from different datasets to
be able to combine the information (interlinking process)
● Store the transformed data using a new model
● Consume data● Analyse data● Visualisation
Approach with OPeNDAP only
● View metadata to understand the data
● Consume data● Make conversions to comply with
standards● Align data from different datasets to
be able to combine the information (interlinking process)
● Analyse data● Visualisation
Approach with all Copernicus App Lab Tools
● View metadata to understand the data● Consume data● Analyse data● Visualisation
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Building Apps with Linked Data
Linked Data applications have three main parts:● Consume Linked Data● Analyse Linked Data● Application User Interface
Consume Linked Data using HTTP requests● GET request with a query parameter:
○ query : SPARQL query string (url encoded)● Use Accept header according to the required results format:
○ application/sparql-results+xml (XML)○ application/sparql-results+json (JSON)○ text/tab-separated-values (TSV)○ text/html (HTML table)○ application/json OR application/geojson (GeoJSON)○ application/kml (KML)
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Explore within-city patterns, e.g. parks vs. urban greenness (Paris)
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Explore within-city patterns, e.g. parks vs. urban greenness (Amsterdam, Paris, Helsinki, Brussel)
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Explore within-city patterns, e.g. parks vs. urban greenness (Amsterdam, Paris, Helsinki, Brussel)
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Query Example - “Greenness within Paris”SELECT ?w1 (ceil(avg(?lai)) as ?meanLAI) ?name WHERE {
?s lai:lai ?lai .?s geo:hasGeometry ?geo .?s lai:observationTime ?t .?geo geo:asWKT ?w .?adm a gadm:AdministrativeUnit .?adm gadm:hasName ?name .?adm geo:hasGeometry ?geo1 .?geo1 geo:asWKT ?w1 .?adm gadm:belongsToAdm2 ?adm2 .?adm2 gadm:hasName "Paris" .FILTER (geof:sfIntersects(?w,?w1))
}GROUP BY ?w1 ?meanLAI ?name
Select LAI values, their geometries and valid time.
Select Administrative Units
Filter Administrative Units that belong to Paris
Filter LAI values that are inside Paris
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Examine within-city patterns, e.g. CLC vs. temporal urban greenness (Paris)
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Launched in
2014> 70
Apps developed
> 550Participants
41.241Hours of Coding
Jul Aug Sept Oct Nov Dec … July Aug Sept Oct Nov
START EVENT
STARTUPPHASE AWARDS
CEREMONY
Dec
Recruitment and training of the candidates
Awarding of all winner(s)Shortlist for the AppCamp
Provision of acceleration and incubation services & syndication
Example timeline of an typical event and RAMANI’s role
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RAMANI is
• 3 locations worldwide• 6 FTE with a combined
+35 year experience in Web 3.0 technology and Geospatial data
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Valentijn Venus (CEO)+31 (0)6 290 72 [email protected]
RAMANI B.V. a Ujuizi HOLDING B.V. company Rondweg 407468MC EnterThe NetherlandsW: Maps-APII: Resume