1. Digital Enterprise Research Institute www.deri.ie
Wikipedia (DBpedia):
Crowdsourced Data Curation
Edward Curry, Andre Freitas, Seán O'Riain
ed.curry@deri.org
http://www.deri.org/
http://www.EdwardCurry.org/
Copyright 2010 Digital Enterprise Research Institute. All rights reserved.

2. Speaker Profile
Digital Enterprise Research Institute www.deri.ie
 Research Scientist at the Digital Enterprise Research
Institute (DERI)
 Leading international web science research organization
 Researching how web of data is changing way business
work and interact with information
 Projects include studies of enterprise linked data, community-
based data curation, semantic data analytics, and semantic
search
 Investigate utilization within the pharmaceutical, oil &
gas, financial, advertising, media, manufacturing, health
care, ICT, and automotive industries
 Invited speaker at the 2010 MIT Sloan CIO Symposium
to an audience of more than 600 CIOs

3. Overview
Digital Enterprise Research Institute www.deri.ie
 Curation Background
 The Business Need for Curated Data
 What is Data Curation?
 Data Quality and Curation
 How to Curate Data
 Wikipedia (DBpedia) Case Study
 Best Practices from Case Study Learning

4. The Business Need
Digital Enterprise Research Institute www.deri.ie
 Knowledge workers need:
 Access to the right information
 Confidence in that information
 Working incomplete
inaccurate, or wrong
information can have
disastrous consequences

5. The Problems with Data
Digital Enterprise Research Institute www.deri.ie
 Flawed Data
 Effects 25% of critical data in world‟s top companies
(Gartner)
 Data Quality
 Recent banking crisis (Economist Dec‟09)
 Inaccurate figures made it difficult to manage operations
(investments exposure and risk)
– “asset are defined differently in different programs”
– “numbers did not always add up”
– “departments do not trust each other‟s figures”
– “figures … not worth the pixels they were made of”

6. What is Data Curation?
Digital Enterprise Research Institute www.deri.ie
 Digital Curation
 Selection, preservation, maintenance, collection, and
archiving of digital assets
 Data Curation
 Active management of data over its life-cycle
 Data Curators
 Ensure data is
trustworthy, discoverable, accessible, reusable, and fit for
use
– Museum cataloguers of the Internet age

7. What is Data Curation?
Digital Enterprise Research Institute www.deri.ie
 Data Governance
 Convergence of data quality, data
management, business process management, and
risk management
 Data Curation is a complimentary activity
 Part of overall data governance strategy for
organization
 Data Curator = Data Steward ??
 Overlapping terms between communities

8. Data Quality and Curation
Digital Enterprise Research Institute www.deri.ie
 What is Data Quality?
 Desirable characteristics for information resource
 Described as a series of quality dimensions
– Discoverability, Accessibility, Timeliness, Completeness, Inte
rpretation, Accuracy, Consistency, Provenance & Reputation
 Data curation can be used to improve these
quality dimensions

9. Data Quality and Curation
Digital Enterprise Research Institute www.deri.ie
 Discoverability & Accessibility
 Curate to streamline search by storing and classifying
in appropriate and consistent manner
 Accuracy
 Curate to ensure data correctly represents the “real-
world” values it models
 Consistency
 Curate to ensure data created and maintained using
standardized definitions, calculations, terms, and
identifiers

10. Data Quality and Curation
Digital Enterprise Research Institute www.deri.ie
 Provenance & Reputation
 Curate to track source of data and determine reputation
 Curate to include the objectivity of the source/producer
– Is the information unbiased, unprejudiced, and impartial?
– Or does it come from a reputable but partisan source?
Other dimensions discussed in chapter

11. How to Curate Data
Digital Enterprise Research Institute www.deri.ie
 Data Curation is a large field with sophisticated
techniques and processes
 Section provides high-level overview on:
 Should you curate data?
 Types of Curation
 Setting up a curation process
Additional detail and references available in book
chapter

12. Should You Curate Data?
Digital Enterprise Research Institute www.deri.ie
 Curation can have multiple motivations
 Improving accessibility, quality, consistency,…
 Will the data benefit from curation?
 Identify business case
 Determine if potential return support investment
 Not all enterprise data should be curated
 Suits knowledge-centric data rather than transactional
operations data

13. Types of Data Curation
Digital Enterprise Research Institute www.deri.ie
 Multiple approaches to curate data, no single
correct way
 Who?
– Individual Curators
– Curation Departments
– Community-based Curation
 How?
– Manual Curation
– (Semi-)Automated
– Sheer Curation

14. Types of Data Curation – Who?
Digital Enterprise Research Institute www.deri.ie
 Individual Data Curators
 Suitable for infrequently changing small quantity of
data
– (<1,000 records)
– Minimal curation effort (minutes per record)

15. Types of Data Curation – Who?
Digital Enterprise Research Institute www.deri.ie
 Curation Departments
 Curation experts working with subject matter experts
to curate data within formal process
– Can deal with large curation effort (000‟s of records)
 Limitations
 Scalability: Can struggle with large quantities of
dynamic data (>million records)
 Availability: Post-hoc nature creates delay in curated
data availability

16. Types of Data Curation - Who?
Digital Enterprise Research Institute www.deri.ie
 Community-Based Data Curation
 Decentralized approach to data curation
 Crowd-sourcing the curation process
– Leverages community of users to curate data
 Wisdom of the community (crowd)
 Can scale to millions of records

17. Types of Data Curation – How?
Digital Enterprise Research Institute www.deri.ie
 Manual Curation
 Curators directly manipulate data
 Can tie users up with low-value add activities
 (Sem-)Automated Curation
 Algorithms can (semi-)automate curation activities
such as data cleansing, record duplication and
classification
 Can be supervised or approved by human curators

18. Types of Data Curation – How?
Digital Enterprise Research Institute www.deri.ie
 Sheer curation, or Curation at Source
 Curation activities integrated in normal workflow of
those creating and managing data
 Can be as simple as vetting or “rating” the results of a
curation algorithm
 Results can be available immediately
 Blended Approaches: Best of Both
 Sheer curation + post hoc curation department
 Allows immediate access to curated data
 Ensures quality control with expert curation

19. Setting up a Curation Process
Digital Enterprise Research Institute www.deri.ie
 5 Steps to setup a curation process:
1 - Identify what data you need to curate
2 - Identify who will curate the data
3 - Define the curation workflow
4 - Identity appropriate data-in & data-out formats
5 - Identify the artifacts, tools, and processes needed to
support the curation process

20. Wikipedia
Digital Enterprise Research Institute www.deri.ie
The World Largest Open Digital Curation Community

21. Wikipedia
Digital Enterprise Research Institute www.deri.ie
 Open-source encyclopedia
 Collaboratively built by large community
 Challenges existing models of content creation
 More than 19,000,000 articles
 270+ languages, 3,200,000+ articles in English
 More than 157,000 active contributors
 Studies show accuracy and stylistic formality are
equivalent to resources developed in expert-
based closed communities
 i.e. Columbia and Britannica encyclopedias

22. Wikipedia
Digital Enterprise Research Institute www.deri.ie
 MediaWiki
 Wiki platform behind Wikipedia
– Widespread and popular technology
 Wikis can also support data curation
– Lowers entry barriers for collaborative data curation
 Widely used inside organizations
 Intellipedia covering 16 U.S. Intelligence agencies
 Wiki Proteins, curated Protein data for knowledge
discovery and annotation

23. Wikipedia
Digital Enterprise Research Institute www.deri.ie
 Decentralized environment supports creation of
high quality information with:
 Social organization
 Artifacts, tools & processes for cooperative work
coordination
 Wikipedia collaboration dynamics highlight good
practices

24. Wikipedia – Social Organization
Digital Enterprise Research Institute www.deri.ie
 Any user can edit its contents
 Without prior registration
 Does not lead to a chaotic scenario
 In practice highly scalable approach for high quality
content creation on the Web
 Relies on simple but highly effective way to
coordinate its curation process
 Curation is activity of Wikipedia admins
 Responsibility for information quality standards

25. Wikipedia – Social Organization
Digital Enterprise Research Institute www.deri.ie
 Four main types of accounts:
 Anonymous users
– Identified by their associated IP address
 Registered users
– Users with an account in the Wikipedia website
 Administrators/Editors
– Registered users with additional permissions in the system
– Access to curation tools
 Bots
– Programs that perform repetitive tasks

26. Wikipedia – Social Organization
Digital Enterprise Research Institute www.deri.ie

27. Wikipedia – Social Organization
Digital Enterprise Research Institute www.deri.ie
 Incentives
 Improvement of one‟s reputation
 Sense of efficacy
– Contributing effectively to a meaningful project
 Over time focus of editors typically change
– From curators of a few articles in specific topics
– To more global curation perspective
– Enforcing quality assessment of Wikipedia as a whole

28. Wikipedia – Artifacts, Tools &
Processes
Digital Enterprise Research Institute www.deri.ie
 Wiki Article Editor (Tool)
 WYSIWYG or markup text editor
 Talk Pages (Tool)
 Public arena for discussions around Wikipedia resources
 Watchlists (Tool)
 Helps curators to actively monitor the integrity and quality of
resources they contribute
 Permission Mechanisms (Tool)
 Users with administrator status can perform critical actions such
as remove pages and grant administrative permissions to new
users

29. Wikipedia – Artifacts, Tools &
Processes
Digital Enterprise Research Institute www.deri.ie
 Automated Edition (Tool)
 Bots are automated or semi-automated tools that perform repetitive
tasks over content
 Page History and Restore (Tool)
 Historical trail of changes to a Wikipedia Resource
 Guidelines, Policies & Templates (Artifact)
 Defines curation guidelines for editors to assess article quality
 Dispute Resolution (Process)
 Dispute mechanism between editors over the article contents
 Article
Edition, Deletion, Merging, Redirection, Transwiking, Archiv
al (Process)
 Describe the curation actions over Wikipedia resources

30. Wikipedia - DBPedia
Digital Enterprise Research Institute www.deri.ie
 DBPedia Knowledge base
 Inherits massive volume of curated Wikipedia data
 Built using information info box properties
 Indirectly uses wiki as data curation platform
 DBPedia provides direct access to data
 3.4 million entities and 1 billion RDF triples
 Comprehensive data infrastructure
– Concept URIs, definitions, and basic types

31. Digital Enterprise Research Institute www.deri.ie

32. Wikipedia - DBPedia
Digital Enterprise Research Institute www.deri.ie

33. Overview
Digital Enterprise Research Institute www.deri.ie
 Curation Background
 The Business Need for Curated Data
 What is Data Curation?
 Data Quality and Curation
 How to Curate Data
 Wikipedia (DBpedia) Case Study
 Best Practices from Case Study Learning

34. Best Practices from Case Study
Learning
Digital Enterprise Research Institute www.deri.ie
 Social Best Practices
 Participation
 Engagement
 Incentives
 Community Governance Models
 Technical Best Practices
 Data Representation
 Human- and AutomatedCuration
 Track Provenance

35. Social Best Practices
Digital Enterprise Research Institute www.deri.ie
 Participation
 Stakeholders involvement for data producers and
consumers must occur early in project
– Provides insight into basic questions of what they want
to do, for whom, and what it will provide
 White papers are effective means to present these
ideas, and solicit opinion from community
– Can be used to establish informal „social contract‟ for
community

36. Social Best Practices
Digital Enterprise Research Institute www.deri.ie
 Engagement
 Outreach activities essential for promotion and
feedback
 Typical consumers-to-contributors ratios of less than
5%
 Social communication and networking forums are
useful
– Majority of community may not communicate using
these media
– Communication by email still remains important

37. Social Best Practices
Digital Enterprise Research Institute www.deri.ie
 Incentives
 Sheer curation needs line of sight from data curating
activity, to tangible exploitation benefits
 Lack of awareness of value proposition will slow
emergence of collaborative contributions
 Recognizing contributing curators through a formal
feedback mechanism
– Reinforces contribution culture
– Directly increases output quality

38. Social Best Practices
Digital Enterprise Research Institute www.deri.ie
 Community Governance Models
 Effective governance structure is vital to ensure
success of community
 Internal communities and consortium perform well
when they leverage traditional corporate and
democratic governance models
 Open communities need to engage the community
within the governance process
– Follow less orthodox approaches using meritocratic
and autocratic principles

39. Technical Best Practices
Digital Enterprise Research Institute www.deri.ie
 Data Representation
 Must be robust and standardized to encourage
community usage and tools development
 Support for legacy data formats and ability to
translate data forward to support new technology and
standards
 Human & Automated Curation
 Balancing will improve data quality
 Automated curation should always defer to, and never
override, human curation edits
– Automate validating data deposition and entry
– Target community at focused curation tasks

40. Technical Best Practices
Digital Enterprise Research Institute www.deri.ie
 Track Provenance
 All curation activities should be recorded and
maintained as part data provenance effort
– Especially where human curators are involved
 Users can have different perspectives of provenance
– A scientist may need to evaluate the fine grained
experiment description behind the data
– For a business analyst the ‟brand‟ of data provider can
be sufficient for determining quality

41. Conclusions
Digital Enterprise Research Institute www.deri.ie
 Data curation can ensure the quality of data and
its fitness for use
 Pre-competitive data can be shared without
conferring a commercial advantage
 Pre-competitive data communities
 Common curation tasks carried out once in public
domain
 Reduces cost, increase quantity and quality

42. Acknowledgements
Digital Enterprise Research Institute www.deri.ie
 Collaborators Andre Freitas & Seán O'Riain
 Insight from Thought Leaders
 Evan Sandhaus (Semantic Technologist), Rob Larson (Vice President Product
Development and Management), and Gregg Fenton (Director Emerging Platforms)
from the New York Times
 Krista Thomas (Vice President, Marketing & Communications), Tom Tague
(OpenCalais initiative Lead) from Thomson Reuters
 Antony Williams (VP of Strategic Development ) from ChemSpider
 Helen Berman (Director), John Westbrook (Product Development) from the Protein
Data Bank
 Nick Lynch (Architect with AstraZeneca) from the Pistoia Alliance.
 The work presented has been funded by Science
Foundation Ireland under Grant No. SFI/08/CE/I1380 (Lion-
2).

43. Further Information
Digital Enterprise Research Institute www.deri.ie
The Role of Community-Driven
Data Curation for Enterprises
Edward Curry, Andre Freitas, & Seán O'Riain
In David Wood (ed.),
Linking Enterprise Data Springer, 2010.
Available Free at:
http://3roundstones.com/led_book/led-curry-et-al.html