Talk at CNI 2015 Spring Membership Meeting in Seattle on April 14th, 2015, see http://www.cni.org/events/membership-meetings/upcoming-meeting/spring-2015/ Abstract: The goal of the InFoLiS project is to connect research data and publications. Links between data and literature are created automatically by means of text mining and made available as Linked Open Data (LOD) for seamless integration into different retrieval systems. This enables scientists to directly access information about corresponding research data in a literature information system, and, vice versa, it is possible to directly find different interpretations and analyses in the literature of the same research data. In our talk, we will describe our methods for generating the links and give insight into the Linked Data infrastructure including the services we are currently building. Most importantly, we will detail how our solutions can be used by other institutions and invite all interested participants to discuss with us their ideas and thoughts on the requirements for these services to ensure broad interoperability with existing systems and infrastructures. InFoLiS is a joint project by the GESIS – Leibniz Institute for the Social Sciences, Cologne, Mannheim University Library, and Mannheim University supported by a grant from the DFG – German Research Foundation.

1. Integration of research literature and data
(InFoLiS)
Katarina Boland1
Philipp Zumstein2
1
GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany
2
Mannheim University Library, Mannheim, Germany
CNI 2015 Spring Membership Meeting
April 14th, 2015

2. the InFoLiS project:
Integration of research data and publications
InFoLiS I: 05/2011 - 05/2013
InFoLiS II: 08/2014 - 08/2016
InFoLiS is funded by the DFG (SU 647/2-1)
Integration of research literature and data (InFoLiS) 2/22
Introduction

3. Catalogue:
Publications
SSOAR (GESIS),
Primo (UB MA),
...
DataCatalogue:
Research Data
da|ra (GESIS),
...
Query
Query
Response
Links
Response
Response
Response
Integration of research literature and data (InFoLiS) 3/22
InFoLiS Project Goals

4. 1 Part I: Generation of Links
2 Part II: How can you reuse it?
Integration of research literature and data (InFoLiS) 4/22
Outline

5. Integration of research literature and data (InFoLiS) 5/22
Part 1: Generation of Links

6. Recommendation:1
:
Creator (Publication Date): Title. Publication
Agent. Identifier
Creator (Publication Date): Title. Version.
Publication Agent. Type of Resource. Identifier.
→ Extraction based on these patterns?
1
see
http://auffinden-zitieren-dokumentieren.de/zitieren/empfohlene-datenzitation/
Integration of research literature and data (InFoLiS) 6/22
Citation of Research Data

7. presentation and discussion of the empirical findings. For this purpose, data
from the Socio-Economic Panel (SOEP) of the years 1990 and 2003 are used
and for both periods, the impact factors are estimated using linear regression
models.
data from the title of the years year are used
Integration of research literature and data (InFoLiS) 7/22
References to Datasets

8. Table 1: Population forecast for Germany depending on age cohorts -
proportion in percent.
Data base: 10th Population Forecast of the Federal Statistical Office , variant 5.
(Data base: number title of the publication agent, variant
variant)
Integration of research literature and data (InFoLiS) 8/22
References to Datasets

9. Consulted were furthermore ...
Consulted were furthermore title1, title2, title3, ..., titleN.
Integration of research literature and data (InFoLiS) 9/22
References to Datasets

10. Table 3: Sample of the surveys conducted in the years 2003 and 2004 as well
as size of the sample, with valid data from both surveys
(Source: Ditton et al. 2005a)
(Source: citation of descriptive publication)
Integration of research literature and data (InFoLiS) 10/22
References to Datasets

11. ...are hard to detect!
see also...
Green, Toby (2009). We Need Publishing Standards for
Datasets and Data Tables. OECD Publishing White Paper.
doi: 10.1787/603233448430
Altman, Micah and Gary King (2007). A Proposed Standard
for the Scholarly Citation of Quantitative Data. In: D-Lib
Magazine 13.3.
url: http://www.dlib.org/dlib/march07/altman/03altman.html
Integration of research literature and data (InFoLiS) 11/22
References to Datasets

12. Integration of research literature and data (InFoLiS) 12/22
Automatic Identification of
References
Why not simply search for study titles in publications?

13. Integration of research literature and data (InFoLiS) 12/22
Automatic Identification of
References
Why not simply search for study titles in publications?
“ALLBUS/GGSS 1996 (Allgemeine Bev¨olkerungsumfrage der
Sozialwissenschaften/German General Social Survey 1996)”

14. Integration of research literature and data (InFoLiS) 12/22
Automatic Identification of
References
Why not simply search for study titles in publications?
“ALLBUS/GGSS 1996 (Allgemeine Bev¨olkerungsumfrage
der Sozialwissenschaften/German General Social Survey 1996)”
“ALLBUS 96”

15. Integration of research literature and data (InFoLiS) 12/22
Automatic Identification of
References
Why not simply search for study titles in publications?
“Youth 2010”

16. How do humans recognize study references?
Source: Estimations based on SOEP, wave 2002.
Integration of research literature and data (InFoLiS) 13/22
General idea

17. How do humans recognize study references?
Source: Estimations based on xyz, wave 2002.
Integration of research literature and data (InFoLiS) 13/22
General idea

18. Integration of research literature and data (InFoLiS) 14/22
Algorithm

19. for details see...
Katarina Boland, Dominique Ritze, Kai Eckert & Brigitte Mathiak (2012).
Identifying References to Datasets in Publications. In: Proceedings of the
Second International Conference on Theory and Practice of Digital Libraries
(TPDL), Lecture Notes in Computer Science Volume 7489, pp. 150-161. Berlin:
Springer. doi:10.1007/978-3-642-33290-6 17
Integration of research literature and data (InFoLiS) 15/22
Reference Extraction

20. Integration of research literature and data (InFoLiS) 16/22
Mapping to Datasets in da|ra

21. Strategies: 1) greedy; 2) exact; 3) best
Integration of research literature and data (InFoLiS) 17/22
Mapping to Datasets in da|ra:
granularity of registration vs. citation

22. ALLBUS
ALLBUS 2000 ALLBUS 1996ALLBUS 1998
ALLBUS 2000
CAPI/PAPI
ALLBUScompact 2000
CAPI/PAPI
ALLBUScompact 2000
CAPI
ALLBUS - Cumulation 1980-2006 ALLBUS - Cumulation 1980-2008ALLBUScompact - Cumulation 1980-2010
ALLBUScompact 2000 ... ... ...
......
... ... ... ... ...
... ... ... ... ... ... ... ... ... ... ... ......
ALLBUScompact
→ use ontology
Integration of research literature and data (InFoLiS) 18/22
Mapping to Datasets in da|ra

23. Vocabulary: e.g. DDI-RDF Discovery Vocabulary2
2
Thomas Bosch, Richard Cyganiak, Arofan Gregory, Joachim Wackerow (2013): DDI-RDF Discovery Vocabulary: A Metadata
Vocabulary for Documenting Research and Survey Data. In: Proceedings of the 6th Linked Data on the Web (LDOW) Workshop at
the 22nd International World Wide Web Conference (WWW). CEUR Workshop Proceedings, pp. 46-55
Integration of research literature and data (InFoLiS) 19/22
Ontology: Approach

24. Integration of research literature and data (InFoLiS) 20/22
Links

25. Example: da|ra
Example: SSOAR
Integration of research literature and data (InFoLiS) 21/22
Integration of Links into Information
Systems

26. Thank you for your attention!
katarina.boland@gesis.org
Integration of research literature and data (InFoLiS) 22/22
Next part: How can you
reuse it?

27. Part II
How can you reuse it?

28. !
Work in Progress

29. Interna, Data Structure, Technology

30. (Internal) Data structure
Document
Pattern
Executation of
Algorithm
Study Title
Study URI

31. (Internal) Data structure
Document
Pattern
Executation of
Algorithm
Study Title
Study URI
Which studies
are found in a
document?

32. (Internal) Data structure
Document
Pattern
Executation of
Algorithm
Study Title
Study URI
How was a
pattern derived?
Which studies
are found in an
document?

33. (Internal) Data structure
Document
Pattern
Executation of
Algorithm
Study Title
Study URI
Which other study
titles are found with
the new
configuration of the
algorithm?
How was a
pattern derived?
Which studies
are found in an
document?

34. Technology stack

35. Web Services

36. RESTful API (web services)
 GET, POST, PUT, DELETE, PATCH resources
 Search, perform algorithms, upload files
 open for integration into other workflows, e.g. in
 ressource discovery systems
 research data catalogues
 digital repositories
 possible to orchestrate over a web interface for
individual use

37. Lookup services
DB
(links)
lookup service
publication
URI
study URI
study URI
reverse lookup
service
publication
URI

38. Extraction of study URIs from a PDF
pdf (fulltext)
DB
(patterns)
pdf2txt
txt (fulltext) extract study titles
study URI
study titles
linking

39. Recognizing patterns
pdfs
(fulltext)
pattern recognizer
seed
DB
(pattern)

40. Integration of publications and
research data

41. Quoting the Horizon Report 2014
“Visionary leadership for research data management
models is also required to determine how to best
incorporate data connections into library catalogs” (NMC
Horizon Report 2014 - Library Edition, p. 7)

42. Current situation: Several steps needed
 Common situation today:
 Search online catalogue
 Evaluate search results
 Find fulltext to relevant source
 Read the publication
 Spot the research data
 Moreover, often the reverse information is missing
completely
 Which publications are built on some specific
research data?

43. Clientside
load additional data in
catalogue view (e.g. over
Ajax)
 enrich view, links
 up-to-date data
 Embedd data in the web
presentation
Serverside
add additional data in your
catalogue database (e.g.
Primo enrichement process)
 enrich view, links, search,
sort, filter
 time-lagged because of
the update mechanism
 Do the data fit into
existing infrastructure?
(fields, tables, database)
Two Approaches

44. Integration as links
 Link from catalogue entry ...
 … to the corresponding research data

45. Integration as popup
Cited research data: 2
• ALLBUS 2010 (used in 512 publications)
• part of ALLBUS (used in 13.456 publications)
• own research data (used in 1 publications)

46. Integration in search/sort
Cited data sets 4
Cited data sets 1
Sort by data
citation

47. Integration in search/filter
Research data available

48. Enrich your research data catalogue
Cited in: Ritze, D., Paulheim, H., &
Eckert, K. (2013). Evaluation Measures
for Ontology Matchers in Supervised
Matching Scenarios. In The Semantic
Web – ISWC 2013 (p. 392–407).
Tags from Publication: Supervised
Ontology Matching, Evaluation, Recall,
Precision, F-Measure, Precision@N-
Curves, ROC-Curves, Precision-Recall-
Curves

49. Current Goals of the Project
1. Expansion to other disciplines and languages
2. Linked data based infrastructure
3. Improve the reusability of generated links

50. Dissemination
 our web services will be open for everyone
 project webpage
 http://infolis.github.io/
 background information,
slides, publications, news
 Additionally our code is open source
 https://github.com/infolis
 you can install/try out everything locally
 development of code

51. Questions, Discussions, Feedback
 Questions?
 Discussions
 Give us feedback
 Small online survey: http://t1p.de/infolis
http://wiki.bib.uni-mannheim.de/limesurvey/index.php?sid=55594