1. Open Data Publication and ConsumptionAn Overview of Relevant Data Access Approaches and DaaSSolutions@ESWC Summer School, 2014
DumitruRoman, SINTEF, Norway
dumitru.roman@sintef.no

2. Outline
•The context: Open Data
•Data access: Web APIs, OData, SPARQL/LDP
•DaaSsolutions landscape and open DaaSarchitecture
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3. Outline
•The context: Open Data
•Data access: Web APIs, OData, SPARQL/LDP
•DaaSsolutions landscape and open DaaSarchitecture
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4. The context: Open Data
•Open Data Movement: make data available (primarily government data)
–Businesses and citizens can develop new ideas, services and applications
–Can support (government) transparency and accountability
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Source: McKinsey http://www.mckinsey.com/insights/business_technology/open_data_unlocking_innovation_and_performance_with_liquid_information
Gartner:
By 2016, the use of "open data" will continue to increase —but slowly, and predominantly limited to Type A enterprises.
By 2017, over 60% of government open data programs that do not effectively use open data internally, will be scaled back or discontinued.
By 2020, enterprises and governments will fail to protect 75% of sensitive data and will declassify and grant broad/public access to it.
Source: Garner http://training.gsn.gov.tw/uploads/news/6.Gartner+ExP+Briefing_Open+Data_JUN+2014_v2.pdf

5. Lots of open datasets on the Web…
•A large number of datasets have been published as open data in the recent years
•Many kinds of data: cultural, science, finance, statistics, transport environment, …
•Popular formats: tabular (e.g. CSV, XLS), HTML, XML, JSON, …
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6. …but few applications
•Applications utilizing open and distributed datasets have been rather few, e.g.
•Challenges include:
–Lack of resources: unreliable data access
–Lack of expertise: not easily available to organisations
–Technical/organizational
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Open Data Portal
Datasets
Applications
data.gov
~ 110 000
~ 350
publicdata.eu
~ 50000
~ 80
data.gov.uk
~ 20000
~ 350
data.norge.no
~ 300
~40

7. Open data publication and access
• Data publishers: complicated data publishing and maintenance
process
• Data consumers/developers: complicated programmatic data
access
• A decision which lifts a data publication burden from a data
publisher will place that burden on the data access for the data
consumer
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Easy data
publication
Easy data
access
Complicated
data access
Complicated data
publication
Simplify data publication ! Simplify data access!

8. Outline
•The context: Open Data
•Data access: Web APIs, OData, SPARQL/LDP
•DaaSsolutions landscape and open DaaSarchitecture
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9. (Programmatic/Web-based) Data access
•Traditional approaches for programmatically consuming data: ODBC, JDBC, RMI, CORBA, ...
•Modern Web applications and data services rely extensively on lightweight Web service based approaches exchanging data via standard protocols (HTTP) and formats (e.g. XML, JSON, RDF, …)
•Relevant approaches for programmatic access to open data
–Web APIs
–OData
–SPARQL and Linked Data Platform (LDP)
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10. Web APIs
•Programmatic interfaces accessible through HTTP calls (e.g. GET, POST)
•Data (requests/responses) typically in JSON or XML
•Very popular among application developers
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Source: http://www.programmableweb.com/
Protocol: HTTP
Payload: JSON/XML/…
Data Consumer / Dev
Data Provider
Client Library
App
Web Service
Web API

11. Web APIs -example
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Request:
GET http://api.yr.no/weatherapi/locationforecast/1.9/?lat=60.10;lon=9.58
Response payload:
http://api.yr.no/weatherapi/locationforecast/1.9/documentation

12. Open Data Protocol (OData)
•“ODBC for the Web”
•A protocol for creating and consuming data APIs
•Builds on HTTP and REST
•OASIS Standard (2014), promoted by Microsoft, IBM, and SAP
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http://www.odata.org/

13. OData
•Principles: Metadata, Data, Querying, Editing, Operations, Vocabularies
•The OData Data Model –based on the Entity Data Model (EDM)
•The OData protocol: CRUD + query language
•XML and JSON serialization
Source: Microsoft
http://msdn.microsoft.com/en-us/data/hh237663.aspx

14. OData -requesting data examples
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Request (entity by ID):
GET serviceRoot/People('russellwhyte')
Source: http://www.odata.org/getting-started/basic-tutorial/
Response payload:
Request (collections):
GET serviceRoot/People
Request (individual property):
GET serviceRoot/Airports('KSFO')/Name

15. OData -querying data examples
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Source: http://www.odata.org/getting-started/basic-tutorial/
Request (filter):
GET serviceRoot/People?$filter=FirstNameeq'Scott'
Response payload:
Filter on complex type:
GET serviceRoot/Airports?$filter=contains(Location/
Address, 'San Francisco')
orderby:
GET serviceRoot/People('scottketchum')/Trips?
$orderby=EndsAtdesc
top:
GET serviceRoot/People?$top=2
count:
GET serviceRoot/People/$count
expand:
GET serviceRoot/People('keithpinckney')?$expand= Friends
select:
GET serviceRoot/Airports?$select=Name, IcaoCode
search:
GET serviceRoot/People?$search=Boise
Lambda Operators: any / all
GET serviceRoot/People?$filter=Emails/any(s:endswith(s, 'contoso.com'))

16. OData -data modification example
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Source: http://www.odata.org/getting-started/basic-tutorial/
Request (Create an Entity):
POST serviceRoot/PeopleOData-Version: 4.0Content-Type: application/json;odata.metadata=minimalAccept: application/json
{ "@odata.type" : "Microsoft.OData.SampleService.Models.TripPin.Person", "UserName": "teresa", "FirstName" : "Teresa", "LastName" : "Gilbert", "Gender" : "Female", "Emails" : ["teresa@example.com", "teresa@contoso.com"],"AddressInfo" : [ { "Address" : "1 Suffolk Ln.", "City" : { "CountryRegion" : "United States", "Name" : "Boise", "Region" : "ID“ } }] }
Response payload:
Remove an Entity:
DELETE serviceRoot/People('vincentcalabrese')
Update an Entity(uses PATCH or PUT)
Relationship Operations (Link to Related Entities):
POST serviceRoot/People('scottketchum')/Friends/$ref…
{ "@odata.id": "serviceRoot/People('vincentcalabrese')" }

17. SPARQL
•A set of specifications that provide languages and protocols to query and manipulate RDF graph content on the Web or in an RDF store
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Service Description
Request:
GET /sparql/
Host: www.example.org
Response: An RDF description, using the Service Description vocabulary
Protocol for RDF
Request:
GET /sparql/?query=[SPARQL Query]
Host: www.example.org
Response: A SPARQL Results Document or RDF graph
Update Language
PREFIX foaf: <http://xmlns.com/foaf/0.1/> .
INSERT DATA { <http://www.example.org/alice#me>
foaf:knows[ foaf:name"Dorothy" ]. } ;
DELETE { ?person foaf:name?mbox}
WHERE { <http://www.example.org/alice#me> foaf:knows?person .
?person foaf:name?name FILTER ( lang(?name) = "EN" ) .}
Examples taken from http://www.w3.org/TR/sparql11-overview/
Query Language
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name (COUNT(?friend) AS ?count)
WHERE {
?person foaf:name?name .
?person foaf:knows?friend .
} GROUP BY ?person ?name
Result(serialized in XML, JSON, CSV, TSV):
Graph Store HTTP Protocol
POST /rdf- graphs/service?graph=http%3A%2F%2Fwww.example.org%2Falice
Host: example.org
Content-Type: text/turtle
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
<http://www.example.org/alice#me> foaf:knows[ foaf:name"Dorothy" ] . http://www.w3.org/TR/sparql11-overview/

18. Linked Data Platform
•Describes the use of HTTP for accessing, updating, creating and deleting resources from servers that expose data as Linked Data
•Centered around LDPRs, LDPCs, membership, containment
•Under development at W3C; working draft
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http://www.w3.org/TR/ldp/
LDP-BC
Request: GET /c1/
Response payload:
Resource
Request: GET /netWorth/nw1
Response payload:
LDP-DC
Request: GET /netWorth/nw1/liabilities/
Response payload:
Examples taken from http://www.w3.org/TR/ldp/
LDP-DC
Request:

19. Data Access Summary
•Web APIs
–Very flexible, popular with Web developers, no specific commitment to data models
•OData
–ER-based data model, abstract interface to datastores(focus on CRUD), perceived as vendor-pushed (strong tool support)
•SPARQL and LDP
–Graph data model, community-pushed, some interesting features (querying, federation, linking,…)
•Though there is overlapping between the various approaches, they all aim to simplify access to distributed data sources for application developers
–Which approach to choose depends on many factors, e.g. type of data, size, relationships, infrastructure, skills to support, frequency of updates, end-use scenarios, …
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20. Outline
•The context: Open Data
•Data access: Web APIs, OData, SPARQL/LDP
•DaaSsolutions landscape and open DaaSarchitecture
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21. Data publication
•Data access mechanisms simplify data consumption for application developers
•But data needs to be provisioned to applications according to the chosen data access mechanism
–And applications will always be dependent on the hosting for the data they use
•Data publishers and application developers need to rely on generic Cloud platforms and build, deploy and maintain a complex Open Data software and data stack from scratch
–Complicated data provisioning and maintenance process
–Data-as-a-Service (DaaS) solutions are emerging to address this issue
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“Likeallmembersofthe"asaService"(XaaS)family,DaaSisbasedontheconceptthattheproduct, datainthiscase,canbeprovidedondemandtotheuserregardlessofgeographicororganizationalseparationofproviderandconsumer.”
Source:Wikipedia;https://en.wikipedia.org/wiki/DaaS

22. Relevant DaaSsolutions
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Windows Azure Marketplace
Socrata
DataMarket
Factual
Junar
PublishMyData
DaPaaS
…

23. Windows Azure Marketplace
• A marketplace for applications
and data (~170 datasets; ~700
applications)
• Charging data consumers
• Tools and APIs for data
publishing, analytics, metadata
management, account
management and pricing,
monitoring and billing, as well
as a data portal for dataset
exploration
• Supports OData
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https://datamarket.azure.com/
Source: Microsoft
http://go.microsoft.com/fwlink/?LinkID=201129&clcid=0x409

24. Socrata
•Specific focus on Open Data
•Open Data Portal: data publishing & clean-up, metadata generation, data- driven portals for data exploration and portal management
•API Foundry for creating and deploying RESTfulAPIs on top of the data
•Hosted data is accessible through the SocrataOpen Data API (SODA) –a RESTfulinterface for searching and reading data in XML, JSON or RDF
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http://www.socrata.com/
Source: Socrata

25. DataMarket
•Provides statistical data from almost 100 data providers
•~ 71 000 datasets
•Supports embeddable visualisations of data, data export, live feeds for data updates, ability for data publishers to monetize data via the marketplace, custom data driven portals for publishers, data portal, Web API
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http://datamarket.com/

26. Factual
•Data for ~ 65 million local business and points of interest in 50 countries; a product database of over 650,000 products
•Used to provide the option for hosting thousands of 3rd party data sets (“Community Data”) but activity has been discontinued
•Data is populated by means of Web crawls, data extraction and 3rdparty data services; data model is tabular, based on taxonomy of around 400 categories
•Pricing is based on a pay-per-use model
•Data access is provided through a RESTfulAPI
•Provides a set of tools for data management
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http://www.factual.com/

27. Junar
•Cloud-based Open Data platform to collect, enrich, publish and analyse open data
•Data can be consumed either directly via the JunarAPI, or via various visual widgets
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http://www.junar.com/

28. PublishMyData
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•Hosted, as-a-service solution for Open and Linked Data publishing
•Uses DCAT and provides data access via Web APIs, a SPARQL endpoint and raw data-dumps
http://www.swirrl.com/publishmydata

29. Other relevant solutions
•Comprehensive Knowledge Archive Network (CKAN) (http://ckan.org/) –web-based open source data management system for the storage and distribution of open data; datahub(http://datahub.io/)
•LOD2 (http://lod2.eu/) –research project aimed at providing an open source, integrated software stack for managing the lifecycle of Linked Data, from data extraction, enrichment, interlinking, to maintenance; not meant to be as-a-service solution
•Project Open Data(http://project-open-data.github.io/) –a set of open source tools, methodologies and use cases for publishing and utilising Open Data
•COMSODE (http://www.comsode.eu/) –research project aiming to create a publication platform for Open Data called Open Data Node
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30. DaPaaS – towards an Open Data- and
Platfom-as-a-Service for Open Data
• DaPaaS – research project for simplifying data publication and
consumption via a Data- and Platform-as-a-Service approach
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http://dapaas.eu
DaPaaS Platform
Data Publisher
End-Users Data Consumer
Application Developer
publishes
open data
develops and deploys
applications on top
published data
consumes data resulting
from the available
applications

31. DaPaaS – Requirements for Data Publisher
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DP-02: Data
storage and
querying
DP-04: Data
interlinking
DP-03: Dataset
search &
exploration
DP-09: Data availability
DaPaaS Platform
DP-05: Data
cleaning &
transformation
DP-01: Dataset
Import
DP-11: Secure
access to platform
DP-10: User
registration & profile
management
Data
Publisher
DP-08: Data scalability
DP-06: Dataset
bookmarking &
notifications
DP-07: Dataset metadata
management, statistics &
access policies
DP-12: UI for data
publisher
DP-13: Data
publishing
methodology support

32. DaPaaS–Requirements for Application Developer
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AD-04: Configure application deployment
AD-01:Access to Data Publisher services
(DP-01 –DP-13)
AD-03:Develop applications in state- of-art programming languages
AD-05:Deploy and monitor application
AD-06:Application metadata management, statistics & access policies
DaPaaS Platform
AD-07:UI for application developer
AD-08:Application development methodology support
AD-02:Data export
Application Developer

33. DaPaaS – Requirements for End-Users Data
Consumer
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DaPaaS Platform
End-User
Data Consumer
EU-03: Datasets and
applications bookmarking
and notifications
EU-01: User
registration & profile
management
EU-02: Search &
explore datasets
and applications
EU-04:Mobile and
desktop GUI access
EU-07: High availability of
data and applications
EU-05: Data export and
download

34. DaPaaSPlatform Abstract High-Level Architecture
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Data Layer
UX Layer
UX Services
Open Data Warehouse
Platform Layer
Usage Monitoring
Application Hosting Environment
Security & Access Control
Tool-supported Methodology for
Data Publishing/Consumption
DaaS Services
PaaS Services
Datasets
DaaS Services
DaaS Services
Data-Driven Applications
PaaS Services
PaaS Services
UX Services
UX Services

35. Summary
•Lots of open datasets, but few applications using them
•Simplifying data publication/consumption can enable an increase in the number (and quality) of applications using open data
•Various approaches emerging
–For data access: Web APIs, OData, SPARQL/LDP
–For data publication/provisioning: DaaSsolutions
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36. Thank you!
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Contact: dumitru.roman@sintef.no