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Adding Semantics to Social Websites for Citizen Science

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Title: Adding Semantics to Social Websites for Citizen Science


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
2
This talk
  • Motivation
  • Swoogle Semantic Websearch engine
  • Social Semantic Web
  • Conclusions

3
SOCIAL MEDIA
  • 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
4
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

5
This talk
  • Motivation
  • Swoogle Semantic Websearch engine
  • Social Semantic Web
  • Conclusions

6
Google has made us smarter
7
But what about our agents?
  • Agents still have a very minimal understanding of
    text and images.

8
But what about our agents?
  • A Google for knowledge on the Semantic Web is
    needed by software agents and programs

9
  • 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

10
Swoogle Architecture
Analysis

Ranking
SWD classifier
Index
Search Services
Semantic Web metadata
IR Indexer
Web Service
Web Server
SWD Indexer
html
rdf/xml
Discovery
the Web
document cache
SwoogleBot
Semantic Web
Candidate URLs
Bounded Web Crawler Google Crawler
Archive
human
machine
pings
Information flow
Swoogles web interface
11
Applications and use cases
  • Supporting Semantic Web developers
  • Ontology designers, vocabulary discovery, whos
    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

1
2
3
12
2
  • An NSF ITR collaborative project with
  • University of Maryland, Baltimore County
  • University of Maryland, College Park
  • U. Of California, Davis
  • Rocky Mountain Biological Laboratory

13
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 likelyconsequences for
    theecology?
  • Sowe need to understandthe effects of
    introducingthis fish into the food webof a
    typical California lake

14
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
    locations 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

15
East River Valley Trophic Web
http//www.foodwebs.org/
16
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
  • gt Maybe we can mine social media for species
    observations data?
  • But we dont 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.

17
Food Web Constructor
  • Predict 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
18
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

19
This talk
  • Motivation
  • Swoogle Semantic Websearch engine
  • Social Semantic Web
  • Conclusions

20
  • 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

21
  • 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

22
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 Webs 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.

23
A BioBlitz involves going out to an area and
recording every organism you see
The OWL icon links to the data in RDF
24
Heres the posts RDF data
25
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

26
SPOTter SPire Observation Tool
  • Weve 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.
  • Were 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

27
SPOTter button
Once entered, the data isembedded into the blog
postand Swoogle is pinged to index it
28
  • We can draw a bounding box onthe map and find
    observations
  • An RSS feed provided for eachquery

Prototype SPOTter Search engine
29
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
  • Theres a good API
  • It could be a good source of ecological
    information

30
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31
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32
Results for people and machines
33
RDF123
  • An application and web service to generate RDF
    data from spreadsheets

Graphically create edit spreadsheet to RDF map
MAP
map spreadsheet gt RDF data
CSV or Googledoc
Some metadata can Be embedded in spreadsheet
See http//ebiquity.umbc.edu/project/html/id/82/
34
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

35
A map provides a template for an RDF subgraph for
each row
36
The map is also represented in RDF
37
Heres the RDF thats produced from the
spreadsheet
38
Metadata, including the URI of a map, can be
embedded in the spreadsheet
39
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

40
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
    providers feed

C1
PingServer
Search Engine
C2
C3
41
Pings and Feeds in the Semantic Web
  • Content provider send pings to ping-the-semantic-w
    eb 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
    providers feed

C1
PTSW
Swoogle
C2
C3
42
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

43
This talk
  • Motivation
  • Swoogle Semantic Websearch engine
  • Social Semantic Web
  • Conclusions

44
Conclusion
  • The web will contain the worlds 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

45
For more information
http//ebiquity.umbc.edu/
Annotatedin OWL
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