Blue Sky 19/09/16 Plenary 1

1. A Sky Without Horizons
Reflections: 10 years after
Luc Soete
UNU-MERIT,
Maastricht University
OECD Blue Sky III, Towards the next generation of data and indicators, 19-21 September 2016, Ghent, Belgium

2. 10 years after Ottawa
• 10 years ago, I presented at the Blue Sky II 2006 Forum a Keynote address
entitled “The Changing STI Climate: A sky without horizons” with the late
Christopher Freeman.
• In that contribution we looked at both past and future. As we stated: with a
combined average age of 70, it seemed logical to look at the past. Why
choices were made in the Frascati Manual with respect to the separation
between R&D and STS, despite the importance of the R&D and STS
distinction in international comparisons with exploding and imploding S&T
systems, how the desire to measure the professionalization of S&T became
to dominate , etc.
• Ten years after, with Chris Freeman no longer being there, I focus more on
present and future challenges with respect to STI indicators.
2

3. 1. The present “over-use” and “under-impact”
of R&D indicators
• Undoubtedly a major achievement of OECD and National Statistical
Offices:
• R&D 50 years later now well recognized in economic and policy circles
• Closely linked with productivity highlighting link with STS
• In the 2008 System of National Accounts R&D became a capital expenditure
for the first time rather than an expense as it was considered in the beginning
of national accounting.
• This is having a significant influence not only on indicators of science and
technology but also on re-estimation of GDP.
• In short, R&D has become a full economically well-integrated indicator.
• Yet, we do not seem to get sufficiently out of available R&D statistics

4. R&D and productivity on Google Trends
(as presented in Ottawa on September 26th, 2006)

5. R&D and productivity on Google Trends
(on September 20th 2016)
• https://www.google.com/trends/explore?date=all&q=R%26D,Product
ivity

6. STI (Mis-)Measurement: “plus ça change, plus
c’est la même chose…”
• However, links between R&D and productivity are becoming tenious,
a country’s high R&D intensity is not a guarantee for future growth or
productivity growth.
• Reasons:
• Global value chains undermining any direct link between national R&D
intensity investments and domestic value extraction
• World-wide increase in R&D, with more than a doubling in the number of
scientists and engineers worldwide over the last fifteen years with different
components of R&D distributed world-wide
• Impact of digitalisation on research collaboration

7. On the need for a system approach
• We need to take increasingly a systems approach to the development of
indicators and, in the course of doing that, find a way to measure value in
global value chains which will produce indicators directly relevant to fiscal
policy.
• A systems approach deals with the actors (agents) in the system wherever
they are, what they do (activities), how they interact (linkages) and what is
the result in the short term (outcomes) and in the longer term (impacts).
• The system is constrained by boundary conditions (framework conditions,
rules of the game, institutions, geographical boundaries…). The boundary
conditions are part of the system: goes back to Donella Meadows and
Limits to Growth and to Herbert Simon and J. Forrester.
• A simple graphical presentation limited to R&D indicators: R&D human
capital and public R&D funding, attracting global private R&D.

8. Public and private R&D are complementary, not substitutes
(USR, 2015)
Mutually reinforcing effect of strong government investment in R&D and researchers, 2010–2011
The size of the bubbles is proportionate to GERD funded by business as a share of GDP (%)
8
Finland
Denmark
Singapore
Korea, Rep. of
Norway
Luxembourg
SwedenJapan
Canada
Portugal
Austria
UK
Germany
Slovenia
USA
France
Belgium
New Zealand
Netherlands
Estonia
Ireland
Russian Fed.
Spain
Czech RepublicSlovakia
Lithuania
Hungary
Latvia
Italy
PolandCroatia
Malta
BulgariaMalaysia
UkraineCosta Rica Argentina
Serbia
Turkey
China
Romania
Brazil
Kazakhstan
Uruguay
MexicoColombia
0
1000
2000
3000
4000
5000
6000
7000
8000
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60
Researchers(FTE)permillioninhabitants
GERD funded from non-business sources as a percentage of GDP (%)

10. Indicators of innovation
• Why we have had since long indicators of R&D and patents, only since the 1990s
have we had innovation indicators thanks to the Oslo Manual and the Community
Innovation Survey and like surveys. However, these indicators have been quite
limited: the Innovation Union Scoreboard has 6 of the 25 indicators come from
the CIS
• What is clearly missing is a generalized definition of innovation for all of the SNA
sectors, not just for the business sector which is what the Oslo Manual has given
us for the last 25 years. There is a proposal at this conference for such generalised
definitions at this Forum (Gault).
• Indicators, to be indicators, should, however, be used in the policy process. One
of the central issues we face today is understanding products (goods or services)
resulting from global value chains.
• This is even more the case for Innovation as a leading question is to which
country the new value created should be attributed in terms of e.g. tax revenues.

11. Global value chains in an innovation system
• Innovation can happen everywhere, in government departments and research
institutes, in hospitals, universities and museums, in households (including
individuals), and in the business sector where innovation indicators have been
part of official statistics.
• There are, however, two sets of innovation indicators not well represented in the
current set: those dealing with linkages; and those related to framework
conditions.
• For a product like the iPod, its design, production and marketing take place in different
countries and involve different elements of the innovation system (actors, activities, linkages
and outcomes). The challenge is how to identify and record each transaction in the value
chain including its geographical location. Before we go there, consider briefly the framework
conditions that apply to the system.
• Framework conditions vary with jurisdiction and include history, education and culture of
participants in the system. These are difficult to change in the short term. However, terms of
trade, standards, and the terms of labour contracts can be changed in the shorter term by
governments as can the taxes related to value creation.

12. R&D and Innovation in Google Trends
(as presented in Ottawa on September 26th, 2006)

13. R&D and Innovation in Google Trends
(on September 20th 2016)
• https://www.google.com/trends/explore?date=all&q=R%26D,innovati
on

14. 2. The future: the “Blue Sky” of ST--I
• There is of course the incremental progress, such as getting a discussion of
generalised definitions of innovation into Chapter 2 of the Oslo Manual
revision. After 25 years (in 2017), it seems useful to deal with more than
just the business sector as the Manual has done up to now.
• But the impact of the digitalisation and democratization of innovation, the
emergence of global, general purpose platforms and local innovations
apps, implies that we are confronted with a global systemic feature of STI,
whereby Innovation is much more widely distributed than R&D, less
dependent on the professional R&D lab, more involving trial and error, with
a more crucial role of users.
• Robert Madelin, the previous innovation advisor to the EC, put it more
radically: “research and innovation are growing in different directions”

15. Implications for STI: lessons from the past
(slide from 2006 Ottawa presentation)
• Early Frascati distinction between R&D and STS particularly relevant today
• Dichotomy between novelty and routine, between professional R&D and production
less relevant today
• Implications for international STI measurement particularly with respect to emerging
economies
• In addition, dichotomy between production as traditional locus of
innovation and consumption less relevant
• From old insights into user-producer relationships (Lundvall)..
• to new visions about role of user in R&D process (von Hippel), collaborative
innovation (David and Ghosh)
• Broader economic impact of innovation again revealed through Google
Trends

16. GDP and Innovation in Google Trends
(as presented in Ottawa on September 26th, 2006)

17. GDP and Innovation in Google Trends
(on September 20th 2016)
• https://www.google.com/trends/explore?date=all&q=GDP,innovation

18. A crazy idea: let’s use Blockchain
• Blockchain is a distributed database, spread across computers with no
central control that transforms governance, the economy, businesses and
the functioning of organisations.
• It’s most popular use is in Bitcoins, but also in other services and
commodities – badges, credits, and qualifications.
• Each ‘block’ is transparent but tamper-proof. A ‘block’ has a timestamp for
recording transactions and offers indelible proof of all of them. It is a
frictionless method for transacting with others.
• The basic idea is that one cuts out the middleman. There is no central
database as everything is distributed, public, synchronised and encrypted.
• All transactions are logged with a time, date and other details – then
verified by smart maths. Consensus decides, every transaction is public.

19. Blockchain as STI indicator tool
• Blockchain technology appears particularly interesting when confronted with
complex products whereby the value chains is based on intellectual property (IP).
• STI seems an interesting application area alongside other applications for
distributed ledger technologies as in the case of the music and film making
industry, where distributional issues are global and trust (amongst artists,
composers, movie makers, producers) is based on reputation.
• The Harvard Business Review conducted a two-year research project exploring
how blockchain technology could securely move and store host "money, titles,
deeds, music, art, scientific discoveries, intellectual property, and even votes“
(See Tapscott, Don (2016), "The Impact of the Blockchain Goes Beyond Financial
Services“, Harvard Business Review, May 2016).
• Two areas would need to be prioritized to implement Blockchain as STI indicators
tool: science and the move towards “open science” and innovation and the
search for the location of value creation and recuperation of innovation rents.

20. Blockchain in science and open access
A quote from Zach Ramsay
• “The thing that had me most excited about Bitcoin back in 2013 was its potential to re-align the incentives in
academia and re-define how science and research is conducted.
• Taught in every Research Methods 101 course, the file-drawer problem – more generally referred to as
publication bias – does perhaps the most disservice to the scientific community at large. .. Publishing a “non-
result” in a “third-tier” journal won’t advance a researcher’s career the way a “significant” result in, say,
Nature will… everything that doesn’t work is locked up in that researchers’ file drawer… As far as I could tell
from 5 years in academia, the scale of duplicate work across labs around the world is both unknowable and
likely enormous. It isn’t time consuming for these data to be published, but I suspect many academics don’t
feel it is worth their time, or that the contribution isn’t meaningful enough if it isn’t in a prestigious journal,
or that it won’t be archived and indexed properly.
• The concepts of pre-registering experiments and widening the scope of acceptable citations begin to address
this issue… the challenge – assuming we want this knowledge free, distributed, and easily accessible
(forever) to anyone with an Internet connection – is archiving and indexing all the content such that our
assumption is satisfied.
• Another failing of academic research is its inability to effectively incorporate user-generated content. As a
student of animal behavior, I watch in awe at the scientifically interesting (and relevant) discussion about
tricking your cat into a circle and wonder how to parse this content into useful data that might lead to a
scientifically sound conclusion. As far as I can tell, the public has a thirst to understand – and participate in –
scientific inquiry; a thirst left wholly unquenched by mainstream academia. How can we aggregate useful
user-generated content to improve the throughput of scientific research?

21. Ctd:
https://bitcoinmagazine.com/articles/how-blockchains-can-further-public-science-
1457972964
• When first dreaming up chain-based apps, one idea stuck with me… the study of geographical distribution of
life on earth i.e., analyzing “where life is” – is both a logistical nightmare and labor intensive. Roughly: 1) get
a research grant, 2) hire some graduate students, 3) gather data and 4) analyze & publish the data.
• The submission of content that meet specific parameters can be incentivized. That is, the content can be
checked for its purported authenticity before being added to a shared database for subsequent analysis. For
example, the Marmot Recovery Foundation’s Observer Program could have a mobile app that allows users to
submit geo-tagged images of marmots to be used for analysis in exchange for tokens – tokens redeemable
for marmot merchandise. .. an image is uploaded, processed, and sent to the Google Cloud Vision API to get
descriptions of the image; these descriptions are checked against a user-defined list of words, and if there is
a match, the image is added to the toadserver. Although the implementation is quite simple, a few hundred
lines more of code and you’d have, say, a smart contract that sends the submitter of matched content some
amount of tokens as a function of the match score and/or the users’ reputation.
• This is part a growing set of tools for the scientific community. That won’t cut it so long as the data is siloed
within research labs/groups, journals are pay-per-view for the public and the average citizen hasn’t the
means or method to contribute meaningfully to global shared knowledge. After all, shouldn’t citizen science
really be called science proper? With blockchains I think it can be…
• The fight for open access to knowledge has been an ongoing battle... Science is ultimately a public endeavor,
and making that dream a reality now appears possible with blockchains.”

22. Blockchain in Innovation
• More complex but ultimately more interesting is the use of Blockchain in measuring and
allocating the contribution to innovation.
• In so far as an innovation builds on numerous inputs from frontier science (“standing on the
shoulder of giants”) to development and design, will be produced within, and be subject to,
global value chains of different sorts, involving not only firms, but also research labs, universities,
governments, a technology such as Blockchain with its decentralized, neutral ledger inventory
system might well provide an essential input into identifying the various contributions to
particular innovations.
• One of the central issues policy makers face today is understanding how and where new products
(goods or services) resulting from global value chains, create value and where such value should
be taxed.
• As Maryann Feldmann (and Marianna Mazzucato) have argued science indicators need to adjust
to the new reality where corporation invest less in R&D, relying more on acquisitions and mergers
and public research to gain access to knowledge.
• Blockchain might well provide the tool to reallocate innovation rents to the frontier science on
which such innovative breakthroughs were built, providing ultimately a new funding source for
publicly funded science.

23. Conclusions
• This is a meeting about indicators, specifically about new indicators or new use of existing
indicators for science, technology and innovation. Indicators, to be indicators, should be used in
the policy process. One of the issues we face today is understanding products (goods or services)
resulting from global value chains. STI indicators contribute in very different ways to global value.
• Countries seem all to become focused on extracting STI value within their own borders. Few
countries have increased their focus on frontier research substantially over the last 10 years, even
though we all know that such research is essential for addressing global challenges.
• The STI community should investigate the possibilities of Blockchain as radical new measurement
instrument. The financial industry has shown a preference to build applications on top of private,
distributed ledgers as opposed to a public Blockchain. This reduces regulatory concern, and allows
closer monitoring of data, information and access privileges among the participants. For STI , and
certainly for science, use of public Blockchains seems much more appropriate.
• In an ideal world, Blockchain in STI would do justice to the systemic nature of innovation and
incorporate more fully citizen science and user innovation into STI. At the same time Blockchain
would also allow as FINTECH instrument better use of knowledge “intangibles“ as collateral and
as “GOVTECH” instrument, provide a neutral instrument to redistribute privatized monopoly rents
back to the systemic network of public collaborative science and innovation, making public
funding of research less dependent on countries’ short term budgetary priorities.