Linked Open Government Data: What’s Next?

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Linked Open Government Data: What’s Next? Li Ding , James A. Hendler, and Deborah L. McGuinness With thanks to the entire RPI Tetherless World LOGD team: logd.tw.rpi.edu particularly John Erickson, Tim Lebo, Dominic DiFranzo;, Alvaro Graves; Gregory Williams; Xian Li; James Michaelis; Jin Zheng; Zhenning Shangguan; Johanna Flores, Evan Patton Tetherless World Constellation, Rensselaer Polytechnic Institute SemTech 2011 San Francisco June 7, 2011

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Tetherless World. Linked Open Government Data: What’s Next?. Li Ding , James A. Hendler, and Deborah L. McGuinness With thanks to the entire RPI Tetherless World LOGD team: logd.tw.rpi.edu particularly John Erickson, Tim Lebo, Dominic DiFranzo;, Alvaro Graves; - PowerPoint PPT Presentation

Transcript of Linked Open Government Data: What’s Next?

Page 1: Linked Open Government Data: What’s Next?

Linked Open Government Data: What’s Next?

Li Ding, James A. Hendler, and Deborah L. McGuinness

With thanks to the entire RPI Tetherless World LOGD team: logd.tw.rpi.edu

particularly John Erickson, Tim Lebo, Dominic DiFranzo;, Alvaro Graves;

Gregory Williams; Xian Li; James Michaelis; Jin Zheng; Zhenning Shangguan; Johanna Flores, Evan Patton

Tetherless World Constellation, Rensselaer Polytechnic Institute

SemTech 2011 San Francisco June 7, 2011

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Outline

• Open Government Data

• Linked Open Government Data

• Challenges and Opportunities

• Future Directions

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Open Government Data:

Government data is already available and open on the Web and is growing.

Let’s create mash ups to expose more value.

?

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Opening Government Data

“Openness will strengthen our democracy and promote efficiency and effectiveness in Government.”

--- President Obama (Jan 2009)

“if people put data onto the web -- government data, scientific data, community data, whatever it is -- it will be used by other people to do wonderful things, in ways that they never could have imagined.”

-- Tim Berners-Lee (Feb 2010)

Source: http://www.whitehouse.gov/open, http://www.ted.com/talks/lang/eng/tim_berners_lee_the_year_open_data_went_worldwide.html

Linked Data and Semantic Tech are key enabler!

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International Open Government Data: A Great Opportunity

• 13 Other nations establishing open data• 24 States now offering data sites• 11 Cities in America with open data• 236 New applications from Data.gov datasets• 258 Data contacts in Federal Agencies• 308,650 Datasets available on Data.gov

• Open Government Data (OGD)– A public asset (collected by

government) with a large amount of high value data and wide domain coverage

– An international mandate for government transparency, business applications, citizen participation, and etc.

Deployment Status (source: Data.gov)

Source: http://www.data.gov/

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Challenges from Raw Open Government Data

Data in proprietary formats Independent curators

Distributed and unlinked Data

Smoke rate(Impacteen.org)

Policy coverage(NCI)

Limited Participation

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Linked Open Government Data

TWC: Tetherless World Constellation at Rensselaer Polytechnic Institute logd.tw.rpi.eduLOGD: Linked Open Government Data

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Linked Data is Large and is Growing

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Linked Open Government Data

A Linked Open Government Data (LOGD) ecosystem is a Linked Data-based system where stakeholders of different sizes and roles find, manage, archive, publish, reuse, integrate, mash-up, and consume open government data in connection with online tools, services and societies.

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Moving data.gov to linked data (US)

• Third parties (like RPI) translate the government datasets into linked data formats

• US Data.gov hosts 6.4B RDF triples 5/21/2010•acknowledges Semantic Web as a key technology for open government data

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Government Data within the LD Cloud12

http://linkeddata.org/

Government Data is currently over ½ the cloud in size (~17B triples), 10s of thousands of links to other data (within and without)

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TWC LOGD: 50+ Demos in Many Domains using Various Technologies

Technology• Semantic Web• Semantic CMS• Semantic Search• Social network• NLP• Mobile• Visualization• Provenance• …

Domain• Health• Finance• Politics • Society• Economy• …

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Selected TWC Mashups

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Trends in Smoking Prevalence, Tobacco Policy Coverage and Tobacco Prices (1991-2007)

PopSciGrid with NIH/NCI & Northwestern

Aimed at conveying complex health-related information to consumers and health decision makers Diverse datasets from NIH Uses lightweight semantic technologies to produce mashups that make data accessible that would be otherwise difficult to view in perspective Maintains provenance about data and manipulations Two-way communication: Feedback users’ comments to gov contacts (e.g. %)

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PopSciGrid Workflow

ConvertConvert

EnhanceEnhance

VisualizeVisualize

derive derive

create

IntegrateIntegrate

Ban coverage

PublishPublish

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The Abstract LOGD Workflow17

VisualizeVisualize End UserEnd User

GovAgency

GovAgency

MashedData

MashedData

LOGDLOGD

RAWOGDRAWOGD

EnhanceEnhance

IntegrateIntegrate

PublishPublish

ConvertConvert

DeveloperDeveloper

Usability of LOGD•Interoperability•Scalability•Provenance

Mashup Workflow(Conventional OGD)1.Publish2.Mashup3.Visualize

Mashup Workflow(Conventional OGD)1.Publish2.Mashup3.Visualize

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Challenge: Interoperability

★make your stuff available on the Web (whatever format) under an open license

★★make it available as structured data (e.g., Excel instead of image scan of a table)

★★★use non-proprietary formats (e.g., CSV instead of Excel)

★★★★use URIs to identify things, so that people can point at your stuff

★★★★★link your data to other data to provide context

Syntactic• Extract entities from HTML tables

• Parse Excel tables

Semantic• Does “Georgia” refer to a US state or a country?

• Is “2000” calendar year, fiscal year or dollar amount?

TBL’s 5-star Deployment Scheme for Linked Data

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Mashing up data from different countries

http://data-gov.tw.rpi.edu/demo/USForeignAid/demo-1554.html

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Even if not “rationalized” together

Build ontology mappingbased on shared terms“Economic”

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Enhance interoperability using Linked Data: drill down contextual knowledge

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• Identity : URI

• Context– Description: metadata, esp. type & datatype– Mapping (linking identities)

• Syntactic– Common string name– Common URI

• Semantic– Complex Object: attributes + context (siblings)– Ontological Mapping: e.g., owl:sameAs– Rule-based Mapping: e.g. mapping “Liter” to “Gallon”

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Scalability factors in LOGD deployment

• Large number of OGD datasets– 6k+ Data.gov.uk – 200k+ Data.gov– 323k+ International OGD datasets

• Non-trivial human workload: clean-up syntax, enhance semantics, integrate datasets, visualize resulting data …

• Substantial computing workload: running time of complex tasks, memory and disk space, maintenance costs …

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International catalog23

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Scalability issues in the International Open Government Dataset Catalog

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Crawled 40+ different dataset catalogs from 19 countries“non-trivial customized programming workload”

Searching 323,304 datasets“Complex SPARQL query got timeout”

Social AspectSocial Aspect

Computing AspectComputing Aspect

International Open Government

Dataset Catalog

International Open Government

Dataset Catalog

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Social Aspect: Distribute human workload to the right developers

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Domain Expertise

App

licat

ion

Dev

elop

men

t E

xper

tise

Joint work with Alvaro Graves, PhD student at RPI

LaymanEnd Users

Software Engineers

Scientists,Experts

Genus

Students

ConvertConvert

EnhanceEnhanceCombineCombine

KnowledgeEngineers

VisualizeVisualize

PublishPublish

1. Decompose workload to fine-granular jobs

2. Leverage a wider range of developers

1. Decompose workload to fine-granular jobs

2. Leverage a wider range of developers

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Computing Aspect: fit computing power to LOGD deployment

• Scale up for more government data– Support collective incremental data processing– Support large scale data analysis: graph connectivity,

complex pattern/hypotheses discovery– Map repetitive developers’ workload to automated tools– Reduce service maintenance costs

• Scale down for wider range of end user apps– Limited computing power, e.g., mobile devices– End users’ cognitive constraints, e.g., screen-size,

executive summary

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Provenance

• Provenance-aware frameworks are needed to support transparency, appropriate attribution, and ultimately trust of any kind of open data.

• Versioning and persistence are important factors to sustainable applications

• Workflow provenance can help increase understanding and trust since it can be used to explain behavior and dependencies of intelligent systems

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Attribution in PopSciGrid

demo

persontechnology

dataset

agency

version

conversion

logd:uses_technology

dcterms:contributor

Example scenarios• List direct/indirect contributors • End users send feedback to curators• Curators learn usage of datasets• List demos by technology

void:subset

void:subset

dcterms:publisher

logd:uses_dataset

State-wise Tobacco Policy coverage stats

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TWC Semantic Water Quality Portal

Aimed at helping people investigate local water quality Diverse datasets, regulations, datatypes Uses lightweight semantic technologies to produce mashups that make data accessible that would be otherwise difficult to view in perspective Maintains provenance about data and manipulations Exposes unexpected uses of data (and thus unexpected usage patterns)

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Detailed View of Pollution

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Provenance of regulations

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Challenges Revisited

• Interoperability– Syntactic: Linked Data, RDF– Semantic: ontology, evolving

• Scalability (9.9 billion triples on the TWC LOGD)– Effective Social platform for task dispatching– More automations, e.g., data cleaning, and linked detection– Scalable tools, esp. SPARQL endpoint

• Provenance– Accountability: Privacy, licensing, trust– Credit / Blame– Replicate applications and transfer system building knowledge

• More issues – Persistent data access for changing data– …

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Summary

• The Open Government data is a key resource– Many governments releasing data, growing number in structured form

• Government (and general data) transparency comes through in the “mashing up” of data from many sites maintaining (and exposing) provenance– Key to linked data

• While there has been tremendous progress, many challenges remain– Trust, Provenance, Scaling, Interoperability, Archiving, Curation, …

• The Research agenda for linked government data is an important driving area for semantic technologies

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Questions?

The work presented in this talk was primarily conducted at the Tetherless World Constellation at Rensselaer Polytechnic Institute.

Comments / Questions: [ dingl | dlm ] @ cs.rpi.edu.

Events:

Open Linked Govt. Data Symposium: submission deadline June 15 http://tw.rpi.edu/web/event/AAAI/2011/Fall_Symposium_OGK

TWC / Elsevier Hackathon: June 27-28

http://tw.rpi.edu/web/event/TWCElsevierHackathonJune2011

Reference: Li Ding, Timothy Lebo, John S. Erickson, Dominic DiFranzo, Gregory Todd Williams, Xian Li, James Michaelis, Alvaro Graves, Jin Guang Zheng, Zhenning Shangguan, Johanna Flores, Deborah L. McGuinness and Jim Hendler, TWC LOGD: A Portal for Linked Open Government Data Ecosystems, submitted to JWS, special issue on semantic web challenge’10