UMBCUMBCan Honors University in an Honors University in

MarylandMaryland 1

Adding Semantics to

Social Websites for Citizen Science Pranam Kolari

University of Maryland,Baltimore County

Joint work with Andriy Parafiynyk, Tim Finin, Cynthia Parr, Joel Sachs, and Lushan Han

http://ebiquity.umbc.edu/paper/html/id/365

http://creativecommons.org/licenses/by-nc-sa/2.0/ This work was partially supported by DARPA contract F30602-97-1-0215, NSF grants CCR007080 and IIS9875433

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This talk

• Motivation• Swoogle Semantic Web

search engine• Social Semantic Web

• Conclusions

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Social media describes the online technologies and practices that people use to share opinions, insights, experiences, and perspectives and engage with each other.

Wikipedia 07

SOCIAL MEDIA

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Social Media for agents

• Today social media supports information sharing among communities of people - enables Citizen Journalism

• An infrastructure based on pings, feeds, content aggregators, and filters (e.g. pipes) aids scalability

• Social media now accounts for ~1/3 of new Web content!

• We need to explore how networks of agents can use the same strategies to share data and knowledge

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This talk

• Motivation• Swoogle Semantic Web

search engine• Social Semantic Web

• Conclusions

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Google has made us smarter

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But what about our agents?

tell

register

Agents still have a very minimal understanding of text and images.

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But what about our agents?

A Google for knowledge on the Semantic Web is needed by software agents and programs

SwoogleSwoogle

Swoogle

Swoogle

SwoogleSwoogle

SwoogleSwoogle

Swoogle SwoogleSwoogle

SwoogleSwoogle

SwoogleSwoogle

tell

register

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•http://swoogle.umbc.edu/•Running since summer 2004•2.2M RDF docs, 434M triples, 10K

ontologies,15K namespaces, 1.5M classes, 185K properties, 49M instances, 800 registered users

•http://swoogle.umbc.edu/•Running since summer 2004•2.2M RDF docs, 434M triples, 10K

ontologies,15K namespaces, 1.5M classes, 185K properties, 49M instances, 800 registered users

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Analysis

Index

Discovery

IR Indexer

Search Services

Semantic Webmetadata

Web Service

Web Server

Candidate URLs

Bounded Web CrawlerGoogle Crawler

SwoogleBot

SWD Indexer

Ranking

document cache

SWD classifier

human machine

html rdf/xml

…

the WebSemantic Web

Information flow Swoogle‘s web interface

Swoogle Architecture

pings

Archive

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Applications and use cases

Supporting Semantic Web developers– Ontology designers, vocabulary discovery, who’s using

my ontologies or data?, use analysis, errors, statistics, etc.

Searching specialized collections– Spire: aggregating observations and data from biologists

– InferenceWeb: searching over and enhancing proofs

– SemNews: Text Meaning of news stories

Supporting SW tools– Triple shop: finding data for SPARQL queries

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An NSF ITR collaborative project with•University of Maryland, Baltimore County •University of Maryland, College Park•U. Of California, Davis•Rocky Mountain Biological Laboratory

An NSF ITR collaborative project with•University of Maryland, Baltimore County •University of Maryland, College Park•U. Of California, Davis•Rocky Mountain Biological Laboratory

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An invasive species scenario• Nile Tilapia fish have been found in a California lake.

• Can this invasive species thrive in this environment?• If so, what will be the likely

consequences for theecology?

• So…we need to understandthe effects of introducingthis fish into the food webof a typical California lake

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Food Webs• A food web models the trophic (feeding)

relationships between organisms in an ecology– Food web simulators explore consequences of ecological

changes, i.e., species introduction or removal

– Food web are constructed from studies of a location’s species inventory and the known trophic relations.

• Goal: automatically construct a food web for a new species using existing data and knowledge

• ELVIS: Ecosystem Location Visualization and Information System

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East River Valley Trophic Web

http://www.foodwebs.org/

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The problem

• We have data on what species are known to be in the location and can further restrict and fill in with other ecological models=> Maybe we can mine social media for species

observations data?

• But we don’t know which of these the Nile Tilapia eats of who might eat it.

• We can reason from taxonomic data (similar species) and known natural history data (size, mass, habitat, etc.) to fill in the gaps.

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Food Web ConstructorPredict food web links using database and taxonomic reasoning.

In an new estuary, Nile Tilapia could compete with ostracods (green) to eat algae. Predators (red) and prey (blue) of ostracods may be affected

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Status• ELVIS (Ecosystem Location Visualization and

Information System) as an integrated set of web services for constructing food webs for a given location.

• Background ontologies– SpireEcoConcepts: concepts and properties to

represent food webs, and ELVIS related tasks, inputs and outputs

– ETHAN (Evolutionary Trees and Natural History) Concepts and properties for ‘natural history’ information on species derived from data in the Animal diversity web and other taxonomic sources. 250K classes on plants and animals

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This talk

• Motivation• Swoogle Semantic Web

search engine• Social Semantic Web

• Conclusions

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• Social media sites have become thebiggest source of new content on the Web

• Blogs, Wikis, Photo sites, forums, etc.• Accounting for ~1/3 of new Web content

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• Social media sites embrace new ways of letting users add semantic information

• Shows users the potential of semantics• This graph shows the uptake of tags in blogs

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Social Media and the Semantic Web• Many are exploring how Semantic Web technology

can work with social media

• Social media like blogs are typically temporally organized– valued for their timely and dynamic information!

• If static pages form the Web’s long term memory, then the Blogosphere is its stream of consciousness

• Maybe we can (1) help people publish data in RDF on their blogs, (2) mine social media sites for useful information, (3) exploit new infrastructure ideas for sharing Semantic Web data.

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The OWL icon links to the data in RDF

A BioBlitz involves going out to an area and recording every organism you see

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Here’s the post’s RDF

data

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A good Semantic Web opportunity• We want to make it easy for scientists to enter

and collect information from social media –Professionals, students and amateurs!

• Some early examples–SPOTter – a tool to add Semantic Web data

to blogs–Splickr – a system to mine Flickr for images

of organisms–RDF123 – an application and Web service to

render spreadsheets as RDF data

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SPOTter: SPire Observation Tool

• We’ve developed some simple components to help people add RDF data to blogs and ping Swoogle to get it indexed.

• SPOTter is an initial prototype that uses the ETHAN ontology and is being used in some BioBlitz activities with students.

• We’re working toward a version that uses Twitter so that people can make the blog entries from the cell phones via SMS– The SPOTter agent will get the entries (via RSS)

and index the data

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SPOTter button

Once entered, the data isembedded into the blog postand Swoogle is pinged toindex it

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Prototype SPOTterSearch engine

• We can draw a bounding box onthe map and find observations

• An RSS feed provided for eachquery

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Flickr • The Flickr “photo sharing” site has millions of

photographs– Many of plants and animals

• Most of them have descriptions, timestamps, tags and even geo-tags– Flickr has even introduced “machine tags” that can

be mapped into RDF• Any Flickr users (humans or bots) can add comments

and annotations• There’s a good API• It could be a good source of ecological information

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Results for people and machines

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RDF123An application and web service to generate RDF data from spreadsheets

MAP

MAP

DATA

Graphically create & edit spreadsheet to RDF map

map + spreadsheet=> RDF data

Some metadata canBe embedded in spreadsheet

CSV or Googledoc

See http://ebiquity.umbc.edu/project/html/id/82/

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RDF123• The Bioblitz project needed a way to

collect and share observational data from students

• Spreadsheets selected as a common data format and templates developed

• RDF123 application and web service developed to ease exporting the data as RDF for a Maryland BioBlitz group– Supports a web service to generate RDF given

URLs for the sheet and map– Works on CSV files and also Google spreadsheets

UMBCUMBCan Honors University in an Honors University in

MarylandMaryland 35

A map provides a template for

an RDF subgraph for

each row

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The map is also represented in

RDF

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Here’s the RDF that’s produced

from the spreadsheet

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Metadata, including the URI of a map, can be embedded in the

spreadsheet

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Ping and Feed Design Pattern

• The Web uses a ping and feed design pattern that is a variant of publish and subscribe

• It accounts for the scalable, smooth function of the Blogosphere and related social media systems

• Pings push and feeds pull

• We can use the same approach to managing volumes of Semantic Web data

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Pings and Feeds in the Blogosphere• Content provider send pings to ping servers when

they have a new item

• Ping servers aggregate pings and stream them to aggregators and indexers, like Google

• Indexing sites retrieve new items from content provider’s feed

PingServer

C1

C2

C3

pings SearchEngine

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Pings and Feeds in the Semantic Web

• Content provider send pings to ping-the-semantic-web when they have new RDF data

• PTSW aggregates pings and streams them to SW aggregators and indexers, like Swoogle

• Indexing sites retrieve new RDF data from content provider’s feed

PTSW

C1

C2

C3

pingsSwoogle

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Semantic Web Feeds drive Mashups• As in the regular web, sites and query engines use

feeds to capture queries

• Accessing a feed runs the query and produces a list of the first N results (usually 10 ≤ N ≤ 20)

• Such query feeds can drive mashups

• Systems like Yahoo pipes make it easy to compose feeds

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This talk

• Motivation• Swoogle Semantic Web

search engine• Social Semantic Web

• Conclusions

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Conclusion• The web will contain the world’s knowledge in

forms accessible to people and computers– We need better ways to discover, index, search and

reason over SW knowledge

• SW search engines address different tasks than html search engines– So they require different techniques and APIs

• Swoogle like systems can help create consensus ontologies and foster best practices

• Social media provide new challenges and opportunities for the Semantic Web

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Annotatedin OWL

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