This was a short talk given on BibBase (http://data.bibbase.org) in LDTC 2010, Graz, Austria.

1. BibBase Triplified http://data.bibbase.org/
Presented by:
Reynold S. Xin UC Berkeley
Joint work with:
Oktie Hassanzadeh, Yang Yang, Jiang Du, Minghua Zhao,
Renee J. Miller University of Toronto
Christian Fritz University of Southern California

2. Outline
 Goals and Status
 Duplicate detection
 Interlinking of data sources
 Additional features
 Conclusions and future work

5. Goals http://www.bibbase.org
 Makes it easy for scientists to maintain publications pages
 Scientists maintain a bibtex file; BibBase does the rest
 Publishes them in HTML

6. Goals http://data.bibbase.org
 Makes it easy for scientists to maintain publications pages
 Scientists maintain a bibtex file; BibBase does the rest
 Publishes them in HTML
 Publishes them in RDF
 Links entries to the open linked data cloud
 With incentive, scientists are helping us build a
bibliographic database (think DBLP but automated)
 Invaluable data set for benchmarking duplicate
detection and semantic link discovery systems

8. Some statistics
 “Beta” went online in June 2010
 As of yesterday (September 1, 2010)
 ~ 100 active users
 4520 publications, 4883 authors, 502 journals, 1881
proceedings, 88 keywords
 39201 author links, 2768 publication links, 30 keyword links
 Note that this is before we do any form of “marketing”

9. Duplicate Detection
 Examples
 Authors: “Renee J. Miller” or “R. J. Miller” or “RJ Miller”
 Publication entries
 Journal & conferences: “VLDB” or “Very Large Data Base”
 Solutions
 Local detection (within a single bibtex file)
 Global detection (across multiple files)

10. Local Detection
 A set of predefined rules to identify duplicates.
 E.g. within a single file, it is highly likely that “Renee J Miller” is
the same as “RJ Miller”.
 Users can specify a suffix to the name to differentiate
them (DBLP approach).
 E.g. “Min Wang” vs “Min Wang2”

11. Global Detection
 Duplicate detection, also known as entity resolution,
record linkage, or reference reconciliation is a well-
studied problem and an active research area. [Tutorial-
VLDB’05, Tutorial-SIGMOD’06]
 We use existing declarative techniques [D.App.σ-SIGMOD’07]
to detect duplicates across multiple files.
 Display disambiguation page on HTML interface and
rdfs:seeAlso attribute on RDF interface.
 Also enables user to provide feedback by
@string{vldb = Very Large Data Base}

12. Interlinking of Data Sources
 Leverages both offline dictionaries and online real-time
URL verifications.
 Some external data sources
 DBLP
 DBpedia
 RKBExplorer
 Semantic Web Dogfood
 LOD foaf

13. Additional Features
 Storage and publication of provenance information
 Dynamic grouping of entities (by year, keyword, etc)
 RSS feed for notification
 DBLP scraper to generate bibtex files from DBLP records
 Statistics on usage
 Enhancement to existing MIT bibtex ontology file

14. Conclusion and Future Work
 BibBase
 Light-weight publication of bibliographic data
 Semantic web technologies as a result of complex
triplification performed inside the system
 Invaluable data set
 Future Work
 More comprehensive duplicate detection
 Links to more external data sources
 Better engineering and service level agreement (99.99%?)
 Broader user base

15. Questions?