sti2014 presentation title A methodological study to structure liquid biofuel science and put its publication dynamics into perspective sti2014 paper abstract Climate change is unequivocal, human influence on the process is clear, and substantial and sustained reductions of greenhouse gas emissions will be required to mitigate and adapt to it. An early global response has been to use liquid biofuel for transport, a development that has triggered a vivid public debate. We try to provide insight in interactions, and the timing thereof, in this debate between science, policy and society. We look at the entire biofuel knowledge base, which is a heterogeneous body of scientific publications and applied ‘grey’ literature. As a first step we present this paper on the methodology applied to structure the scientific part of biofuel knowledge and to put its time dynamics in perspective. We combine quantitative bibliometric data and contextual, qualitative expert interpretation. We used the Web of Science and the CWTS global science classification system to create a body of publications, structured into biofuel related clusters that are based on citation relations and patterns. Each cluster contains both ‘pure’ liquid biofuel publications and surrounding articles that are relevant but not specific enough to be part of the biofuels core. We annotated the selected clusters, extracted data on key players, calculated cluster ages, and presented the number of publications per year for each cluster graphically, always distinguishing between core biofuel- and related surrounding articles. In our analysis, and the main reason for this paper, we then illustrate that it is the actual integration of these different types of detailed data that provides additional information to arrive at an understanding of publication dynamics.

1. A methodological study to structure liquid biofuel
science and put its publication dynamics into
perspective
Mirjam Schomaker 1, 2 and Ed Noyons 1
1 Centre for Science and Technology Studies, Leiden University
2 African Studies Centre, Leiden
19th International Conference on Science and Technology Indicators
Leiden, the Netherlands
September 5, 2014

2. Outline
• Context of this biofuel knowledge mapping project
• Data sources, tools and collection
• Structuring publications into clusters
• Analysis on publication dynamics
• Conclusions
• Next steps
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3. Context of this biofuel knowledge mapping
project
• Geographer with background in integrated environmental
assessment and reporting: connecting science and policy
• Dynamics in the science-policy interface remain
un-transparent and thus intriguing
• Decided to study inter-linkages in biofuel for transport
- Using a systematic approach to map biofuel knowledge
- Integrating scientific and grey literature
• Discovered CWTS and the magic of bibliometrics
• First paper: focus on methodology of structuring
scientific biofuel publications and their dynamics
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4. Data sources and tools
• Web of Science (WoS) database
• CWTS global classification system of science
(Waltman and Van Eck 2012)
- automated clustering of citation relations at publication level
- over 18 million publications between 1993 - 2012
- three levels (broad, intermediate, detailed)
- cluster size varies considerably
- each cluster contains both biofuel specific and surrounding
publications
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5. Actual data collection
• Searched the WoS database: English only; 20 years; titles,
abstracts and keywords
• Long iterative process to define the search strategy
• Delineation problems: definitions, habits, different contexts, and
terminology changes over time
• Combined two sets of publications to arrive at a final set for
further analysis (21,422 publications)
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Web of Science
set_0
not_set_0
set_0 and not_set_0
final_set

6. Comparing renewable energy publications
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Relative increase in publications in the entire WoS for some
forms of renewable energy, 1993 – 2012
7000%
6000%
5000%
4000%
3000%
2000%
1000%
0%
solar energy
wind energy
Indexed at 1993
modern solid biomass energy
liquid biofuel for transport

7. Structuring publications into clusters – 1
Final WoS set combined with CWTS science classification
Second level: position of biofuel, solar- and wind energy (colored) among
the total of ± 800 science clusters in the WoS (blue)
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Biofuel – 21 clusters
Solar – 12 clusters
Wind – 5 clusters

8. Structuring publications into clusters - 2
• Third level: 1689 biofuel clusters
– Each with at least one biofuel-specific core publication and
– surrounding pubs that do not match the biofuel search rules, but are
relevant in a biofuel context
– The more biofuel publications compared to surrounding
publications, the higher the biofuel coverage and the more biofuel
relevant the cluster
• Number of clusters for analysis was limited to 40
– selected clusters with a coverage of at least 5 % and
– at least 10 core biofuel publications,
– while also applying some minor data cleaning
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9. Details for the 40 biofuel clusters - 1
Number of core biofuel pubs per year
from ± 2005 onwards
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10. Details for the 40 biofuel clusters - 2
Top ten scientific publishing countries in 1993 – 2012
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All pubs in WoS All pubs in 40 clusters Biofuel core in 40 clusters
USA 28 % USA 21.2 % USA 24.1 %
Japan 7 % P. R. China 9.2 % P. R. China 9.8 %
Great Britain 7 % Japan 5.6 % India 6.3 %
P. R. China 6 % India 4.5 % Brazil 5.9 %
Germany 6 % Great Britain 4.1 % Japan 3.6 %
France 4 % Brazil 4.1 % Spain 3.6 %
Canada 4 % Canada 3.8 % Great Britain 3.3 %
Italy 3 % Spain 3.7 % Canada 2.9 %
Spain 3 % Germany 3.6 % South Korea 2.7 %
India 2 % France 3.5 % Turkey 2.6 %

11. Details for 10 selected clusters
# cluster code N all
pubs
N BF
pubs
cluster impression * cover-age
overall
cluster
age
biofuel
cluster
age
(a) 10 22 1 4916 4267 biodiesel blends - production and
performance
86.8 % 2008.58 2009.01
(b) 10 8 1 3636 1788 ligno-cellulosic feedstock
decomposition [for bioethanol]
49.2 % 2007.87 2008.92
(c) 6 7 8 1393 853 biofuel debate 61.2 % 2009.22 2009.86
(d) 10 22 2 2816 783 micro-algae [for large-scale biomass
production]
27.8 % 2006.16 2010.74
(e) 6 7 3 1869 421 non-food [energy] crop yield
improvement
22.5 % 2005.37 2008.16
(f) 20 4 1 3146 286 thermo-chemical biomass conversion
(pyrolysis) [into bio-energy]
9.1 % 2006.71 2008.74
(g) 10 8 4 2486 257 ligno-cellulosic feedstock
decomposition
10.3 % 2003.78 2009.50
(h) 1 55 7 919 253 [potential of bio-] butanol 27.5 % 2006.18 2010.31
(i) 10 16 4 1380 245 fermentation; beer, wine, bioethanol,
…
17.8 % 2003.05 2006.75
(j) 10 22 4 771 153 re-use of glycerol [waste from
biodiesel]
19.8 % 2009.19 2009.64
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* see last ppt sheet for an example of cluster annotations

12. Publication dynamics – three examples
presenting annual numbers in graphs gives additional insight
dark = biofuel core; light = surrounding publications
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(a) biodiesel
production and
performance
‘only’
more popular
(c) Biofuel debate
between more popular
and new
(d) micro-algae
biofuel - new
algae – become
more popular

13. Conclusions
• On biofuels for transport
– We obtained interesting initial clues on scientific publication structure
and dynamics which is a nice incentive to continue
• On methodology
– Integration of quantitative bibliometric data with qualitative textual
information provides additional insights
– Such cross-fertilization gives added-value for both communities (the
subject experts and the bibliometrists)
– Visualizing annual publication numbers for each science clusters can
provide additional information on publication dynamics
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14. Next steps
• A comprehensive mapping of the scientific biofuel landscape:
– term map including all clusters pointing to multiple disciplines
– term maps within specific clusters
– classification cluster map of main topics
– cluster- and author networks
– ……….
• Creation of a compatible database on grey literature, including official policy
documents and legislation, and integrating it with the scientific core set (pdf
format problems)
• Analysis of the integrated biofuel for transport knowledge database,
zooming in on linkages (or not) between science and policy, with a focus on
Europe and Africa
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15. Thank you very much for your attention
(see the paper itself for more details and reference to actual data via internet)
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16. The biofuel debate – an example of cluster annotations made
Cluster gives a comprehensive overview of the (liquid) biofuel debate, using a wide variety of arguments, applying
different methodologies and tools to make ones point: life cycle- and sustainability assessments, vulnerability-uncertainty-
risk modeling, footprint analyses, energy/green accounting, supply chain studies, national strategies and
policies (on energy, economy, transport, sustainable development), and more political, philosophical, social or ethical
reasoning (sustainability standards, new paradigms, smallholders, poverty, ...).
Potential and/or perceived impacts are discussed:
(1) on the environment (changes in land use, greenhouse gas emissions, the nitrogen cycle, water resources,
biodiversity);
(2) on social aspects (food security, social unrest due to unjust land allocation, gender issues); and
(3) on economy and development (changes in e.g. the energy, transport and agricultural sectors and policies,
international trade, energy consumption, deteriorating livelihoods, inequality/poverty, ....).
Contradictions used in biofuel core titles are:
good or bad; benefits versus risks; food versus fuel; constraints and potential; constraints and synergies; promises and
perils; (landscape-scale) trade-offs; success story or cautionary tale; opportunities, challenges and pitfalls; realistic or
foolish; biofuel-poverty-growth; authorities and controversies.
The surrounding non-biofuel pubs in the cluster are not far from biofuel issues. Some pubs are e.g. on biogas or
combined heat and power (CHP) - usually in smaller scale (local) burners-, but even then often in combination with
liquid biofuel. In some pubs the search terms are not used, but are relevant nonetheless (sugarcane/sugar footprint,
Jatropha, renewable energy, bioenergy, soil sustainability).
Strangely enough the issue on land grabbing related to biofuel is hardly included in this cluster (is covered in cluster 6
20 11).
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