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Fukushima
Value Oscillation in Knowledge Infrastructure:
Observing its Dynamic in Japan’s Drug Discovery
Pipeline
Masato Fukushima
The School of Arts and Sciences, The University of Tokyo, Japan / maxiomjp@yahoo.co.jp
Abstract
This paper analyses the dynamics of assigned values in two cases relating to the knowledge
infrastructure of the national programme in Japan that develops drug discovery: in establishing a
database of natural product compounds and in constructing a library of virtual compounds. The
concepts of value oscillation and of the M-B (Marx-Bowker) index are proposed to designate the
uctuating appreciation of infrastructure value by its builders. These concepts combine insights from
classical Marxist thought on the infrastructure/superstructure distinction (neglected in recent studies
on infrastructure in STS) and Bowker’s infrastructural inversion. Though value oscillation is almost
ubiquitous in the development of any infrastructure, in the cases considered here, it takes peculiar
forms because of the complex interaction of the material and knowledge infrastructures. It is widely
distributed in the sub-layers that support the autonomy of these knowledge infrastructures and is a
precondition for knowledge infrastructures to function as delineated entities.
Keywords: value, infrastructure, drug discovery, oscillation, structure
Article
Introduction
Concepts are the ways through which we see
the world, and scholars have long realized that
apparent conceptual lucidity may hide winding
paths that can produce a variety of contradic-
tory nuances, leading to persisting controversies.
Thus, academics from various elds have traced
the meandering former paths – including their
etymology – of such concepts as subject/object
(Williams, 1976), liberalism (Hayek, 1982), society
(Luhmann, 1980), and even ‘thing’ (Heidegger,
1968; Latour, 2005; cf. Fukushima, 2005).
From this perspective, the recent rise of
so-called ‘infrastructure studies’ in STS apparently
falls short of re ecting infrastructure’s conceptual
genealogy, while there are numerous concrete
examples analysing what infrastructures are and
have been. A brief review of foundational works
indicates that infrastructure is usually conceived
as a collection of such conventional prototypes as
roads, water conduits, and electricity; later, infra-
structure took on new, extended meaning in terms
of such phenomena as communication, informa-
tion, and even knowledge (Star & Ruhleder, 1996;
Star & Bowker, 2002; Edwards et al., 2007; Bowker
et al., 2010). This approach to de ning the subject,
however, is plagued with historical amnesia in
8
terms of its intellectual genealogy. The concept
of historical amnesia, which will become clearer
through the rest of this article, can briefly be
de ned as blocking recourse to the proper legacy
of the past for systematic reasons, often organiza-
tional, political, or even social (cf. Bowker & Star,
1999, ch. 8), in STS scholarship.
By way of demonstration, in 1978, Current
Anthropology published an article by Maurice
Godelier and colleagues titled ‘Infrastructures,
Societies, and History’ (Godelier et al., 1978).
Godelier is well known for his innovative endeav-
ours to unify Marxist anthropology and French
structuralism (cf. Godelier, 2011). His paper was
intended to rede ne the Marxist version of infra-
structure to solve the evident contradiction
between societies in which such elements as
kinship or religious institutions seem to dominate
contra Marxists’ classical tenet that modes of
production determine other societal factors. At
stake here is the assumption of historical materi-
alism – namely, that the base, or ‘infrastructure’, of
a given society is de ned as the productive forces
and social relations of production that unilaterally
determine the rest of society, the superstructure
(henceforth capitalized to represent their unitary
character; Marx, 1973). Large amounts of energy
have been expended to improve or even alter this
rather rigid framework (Lichtheim, 1971; Howard
& Klare, 1972; McLellan, 1979), and Godelier and
colleagues radically expanded the Marxist under-
standing of Infrastructure to what he calls idéel
reality, a notion inspired both by phenomenology
and structuralism, consisting of thought and
language, knowledge of nature and tool usage,
and taxonomy and classi cation (Godelier et al.,
1978: 764).
The concept of Infrastructure has been
important since Marx (1973) formulated it in
his Grundrisse1, and it has underpinned the
social sciences to various extents. However, the
canonical collections of infrastructure studies
noted above seem to be silent about this speci c
line of Marx’s intellectual legacy (cf. Carse, 2012:
542–44). The reason for this amnesia may be that,
aside from the fact that the term ‘base’ is more
often used in Marxist terminology, the preferred
theoretical approaches of these authors of foun-
dational studies, such as symbolic interactionism
(Star & Ruhleder, 1996; Star, 1999), system theory
a la Parsons and von Bertalan y (Hughes, 1983),
and ANT/SCOT (others), have drawn researchers
away from this tradition. In fact, the merit of these
approaches is undeniable: by ‘clearing and erasing’
the past traces (Bowker & Star, 1999: 257), STS has
produced a fairly large number of empirical, ne-
tuned studies of more specific technical infra-
structures.
While admitting the advantages, I claim that at
least three major problems have been overlooked
by not critically conversing about and confronting
the Marxist legacy: 1) What is Infrastructure? 2)
How does it work? 3) How do we understand it?
1) In STS, the question of what infrastructure is
usually relies on Star and Ruhleder’s (1996) foun-
dational de nition, which presents eight features
that are seemingly distinct from the Marxist
concern with the mode of material production as
the unitary basis for Infrastructure. Overlooked
here is not so much the chance of comparing
the two as a missed opportunity to refer to the
extremely rich inventory of e orts to revise the
latter after its initial formulation in Grundrisse. In
addition to the ensuing attention to the pivotal
in uence of the Superstructure on its counterpart
(McLellan, 1979; Anderson, 1976), to be discussed
below, e orts have also made to nd alternatives
to modes of production, such as consumption
(Bataille, 1988; Baudrillard, 1981) or exchange
(Karatani, 2014; cf. Polanyi, 1944; Sahlins, 1972).
Among these, the most striking case is the above-
mentioned innovation of Godelier and others in
adding structuralistic elements like taxonomy
and classification into Infrastructure, directly
leading to Bowker and Star’s (1999) similar claim
20 years later, a foundational case for the present
treatment of knowledge infrastructure. By failing
to examine such preceding e orts, STS researchers
have clearly missed the chance of incorporating
certain insights into, for example, how the idéel
system works together with a more classic mode
of production, which could provide clues on the
link between the knowledge infrastructure and
the wider economy in the present argument2.
2) The way Infrastructure works is tightly
related to its counterpart, Superstructure; for
Marx, his followers, and his critics, however, the
relation between these two poles has been the
Science & Technology Studies 29(2)
9
target of extensive examination and polemics
because critics regard the Marxist de nition of
Superstructure as too loose, as it includes virtually
everything except modes of production. In
contrast, STS circles seem to have shown relatively
ambiguous attitudes to questions concerning the
e ect of infrastructure and how it is constructed.
Again, the point here is not to adopt the unilat-
eral determination of the earlier formulation,
but to re-examine ensuing e orts to reformulate
the very meaning of determination: for instance,
some even argue that Althusser and Balibar’s
(1970) concept of overdetermination is essentially
in line with the notion of complexity (Shiozawa,
2002), possibly contributing to the present discus-
sion of how multiple infrastructures interact with
each other (cf. Vertesi, 2014).
This determination thesis is also directly related
to the problem of power in terms of the class that
dominates Infrastructure. This element, as part of
the legitimate vocabulary of political sociology,
seems to have some shadowy resonance in
contemporary infrastructure studies; however,
references to the issue are both hesitant and
lacking theoretical cultivation in terms of what
kind of power is related to the issue (cf. Edwards et
al., 2007: 24–31; Edwards et al., 2009: 371).
3) The question of the understanding of Infra-
structure and the value directly attached to such
an act of recognition, the central theme of this
article, requires full exploration. In the Marxist
conceptualisation of these paired concepts, the
latter represents the surface and visible values that
apparently dominate society, whereas the former
is submerged. The Marxist strategy of historical
materialism, in essence, is to destroy this naive
view of the dominance of such surface values by
‘turning Hegel on his head’ (Marx, 1976/81), an act
of inversion in the face of the ladder of values that
exists both in Hegelian idealism and in the real
world, highlighting this apparent inferiority of the
value of Infrastructure in order to reveal its deter-
minant power.
Thus formulated, the following arguments
concerning infrastructure in STS have followed
a similar path without attending to its intellec-
tual ancestry. References to the negative evalua-
tion of infrastructure have been scattered in the
preceding body of research, in which infrastruc-
ture is described as boring and unexciting (Star,
1999: 377), as maintained by undervalued and
invisible workers (Star & Bowker, 2002; Bowker
et al., 2010: 98), and as often characterized by
‘tension’ with regard to its value (Edwards et al.,
2013: 26)3. One description of the ambivalent
aspect of treating taxonomy as infrastructure
summarizes the issue here:
“Being treated as infrastructure has hitherto
been a dubious honour. While being considered
essential gives one a certain amount of leverage, it
also means one risks being taken for granted and
neglected in the face of other, more prominent
topics.” (Hine, 2008)
When this idea is extended to metadata, things do
not seem to be radically di erent:
“All recognize metadata’s potential value, but when
the rubber meets the road, an unfunded mandate
to be altruistic [...] does not prove highly attractive.”
(Edwards et al., 2012)
Thus, although the conflict of values regarding
infrastructure has been a matter of constant, if
sporadic, concern even within the study of infra-
structure in STS, its formulation lacks the consist-
ency of the Marxist tradition in dealing with their
own version of Infrastructure.
Value Oscillation and the
M-B (Marx-Bowker) Index
In this article, drawing upon the last point above,
I focus on this discrepancy: whereas the power of
infrastructure is recognized, the practices related
to it, such as service to others and its maintenance
and repair, are not highly ranked in the existing
value system, being often regarded as invisible
and even ‘boring’. Because of this par ticular nature
of infrastructure, Bowker (1994) proposed ‘infra-
structural inversion’, a strategic analytical opera-
tion to bring hidden infrastructure to the surface
and expose its importance. My claim in this paper
is that this particular operation is, in essence,
structurally isomorphic with the Marxist opera-
tion of ‘turning Hegel on his head’, di erent only
in terms of its focus and scope of theorization.
Fukushima
10
These operations have thus far been con ned
to analysts’ strategies, whereas my examination
relates to how practitioners in situ regard the value
of infrastructure and its related practices. Con ict,
contradiction, and oscillation (as is evident to
some extent in the preceding monographs on the
issue) are expected from this approach, precisely
because practitioners are the ones who develop
and maintain infrastructures. Hence, I will adopt
the term ‘value oscillation’ for describing this
aspect of uctuating attitudes, between these two
poles of the recognition of its supportive value
and avoidance of its shadowy character.
This observation relates intrinsically to the
very concept of infrastructure itself, which is
almost oxymoronic: though infrastructure exerts
immense power as it structures other things, it
is inferior (inferus, inferior from infra, in Latin)
because it lacks surface value. By way of analogy,
Weick and Westley (1999) have claimed that
‘organisational learning’ is an oxymoron because
organizing is a process of reducing complexity,
whereas learning increases it; hence, organisa-
tional learning is rare. Infrastructure as oxymoron
exists rather steadily but generates a double-bind
(Bateson, 1972) for its concerned practitioners,
owing to its intrinsically opposing vectors of
value. Because its value oscillates between these
two poles, like other double-bind situations, it is
hung in indeterminacy. Hence, my term, ‘value
oscillation’, is more adequate than conventional
expressions like ‘value con ict’ or ‘contradiction’:
these are both too macroscopic, and they also
easily connote a ‘dialectical’ solution of cancelling
the contradiction out (aufheben!), which, I believe,
rarely happens in a double-bind.
To describe this zig-zag movement of inde-
terminacy, I introduce a second term, the ‘M-B
(Marx–Bowker) index’, to show the degree of
appreciation for the invisible infrastructure values.
Here, ‘infrastructure’ is de ned not only as the
material entity designated by the term, but also
the wider assemblage of activities involving quasi-
public services to others, works of a sub-contrac-
tive nature, and backstage e orts including those
indirectly related to infrastructure building. The
juxtaposition of these two names signi es the
intrinsic continuity of the two approaches in terms
of inverting the underlying value, while simulta-
neously emphasising the practitioners’ view and
action; in addition, the index becomes an easily
visualized means for observing the oscillating
attitude of the concerned practitioners.
Presupposing practitioners’ recognition of the
validity of any given infrastructure, the M-B index
is de ned as concerned practitioners’ observed
degree of commitment to developing and main-
taining a given infrastructure: hence, a high index
means a high degree of commitment to it, and a
low index implies avoidance of such commitment.
In this paper, this index is used as a gurative tool
for visualising the observed oscillation of practi-
tioners’ attitudes as demonstrated by both their
discourse and their actions vis-à-vis the issue of
building and maintaining infrastructure. One may
argue that such values behind our actions are too
complex to be adequately identified with this
index. This argument admittedly has some truth;
however, I claim that when we focus sharply and
directly on the issue of building and maintaining
infrastructure, we may reduce it to a simple
question of whether one promotes it or avoids it,
though there may be intermediate choices with
accompanying complementary reasons. Such
focused action and discourse, along with any oscil-
lation, are in fact observable, rea rming Geertz’s
(1973) classical formulation of cultural practice as
a public vehicle of meaning.
My own research is based upon ethnographic
observation, and I use such relative expressions
as ‘high’ and ‘low’ with regard to the M-B index.
However, my approach does not preclude the
possibility of substantiating the claims by using
questionnaires, though I did not attempt such in
this project. In such a case, the M-B index could
be tentatively quanti ed, with zero meaning the
practitioners’ avoidance of any commitment to
infrastructure building, and 5 or 10 showing full
commitment to its construction, thus expressing
a continuum.
Some laboratory studies seemingly present
cases of apparent value oscillation concerning
the ambivalent role of research tools and related
work practices (Clark & Fujimura, 1996; Gaudil-
liere & Löwy, 1998; Joerges & Shinn, 2001; Mody,
2011), the interchangeability of epistemic things
and research technology (Rheinberger, 1997;
Joerges & Shinn, 2001), and the problem of the
Science & Technology Studies 29(2)
11
uctuating status of such tools in the hierarchy
of credibility in laboratory settings (Clark &
Fujimura 1992: 16)4. However, infrastructure goes
far beyond the limited scopes of laboratory and
disciplinary boundaries, and its multi-layered
character increases the complexity of analysing
value oscillation, as it is distributed across diverse
spaces and various layers. It is further complicated
when extended to its knowledge aspect, wherein
‘infrastructure’ generally signi es the whole set of
heterogeneous elements of databases, computer-
ization, grid systems, e-science, and so on without
(thus far) a proper de nition (Edwards et al., 2009;
Edwards et al., 2013).
In fact, the question of how value oscilla-
tion takes shape arises in light of the ongoing
momentum and extensive in uence of computers,
information, and even data science as ‘science’
(Hine, 2006b, 2008; Edwards et al., 2007; Edwards
et al., 2009; Bowker et al., 2010; Edwards et al.,
2013). We can presume that these factors push
the M-B index both upwards – because the halo of
new science attracts devotion – and downwards
because ‘infrastructuralization’ is avoided in such
areas compared to established engineering e orts
to maintain roads, water, and electricity. Thus,
possible strategies that concern the dynamics of
knowledge infrastructure become a question of
concern.
The Research Subject
The remainder of this article will discuss ‘value
oscillation’ as it relates to the knowledge infra-
structure in two distinct case studies, both related
to attempts to build a sort of database as part of
the larger scheme of Japan’s national policy of
developing an infrastructure for drug discovery
(sôyaku-kiban) that is academia-based. First, we
look at a faltering endeavour to establish a data-
base of natural product compounds to make the
search for drug seeds more e ective and to facili-
tate basic research for ligand–protein interaction.
Second, we will examine the ongoing construc-
tion of a large-scale virtual library of chemical
compounds, using a world-class supercomputer.
The analytical focus in these case studies is
twofold. The rst is on how value oscillation is
observable in the multi-layered infrastructures
wherein these databases are embedded. The
schemes for building such drug discovery infra-
structure require coordinating and constructing
various layers of sub-infrastructures simultane-
ously, providing intriguing examples of how the
problem of value oscillation is approached in the
di erent layers beyond the con nes of the speci c
databases that are the main focus.
The second focus is how this issue is related to
the context of knowledge and material interac-
tion. As drugs are material entities that require a
vast amount of heterogeneous knowledge, the
development of the knowledge infrastructure
in this context is closely related with its material
counterpart in producing drugs. By highlighting
these two aspects, this paper examines the various
appearances of value oscillations throughout
the complex, multi-layered character of the
knowledge infrastructure and how the practi-
tioners deal with the situation in each contextual
e ort, along with the consequences5.
Background: Drug Discovery
Infrastructure as Knowledge
Infrastructure
Drug discovery is a hugely complex process that
demands a vast amount of heterogeneous knowl-
edge and related infrastructure, beginning with
nding the proper target proteins and drug seeds
and progressing to a range of steps from animal
testing to clinical trials, which include Phases I to
III (Epstein, 2007; Petryna, 2009; Keating & Cam-
brosio, 2003, 2012). Behind the policy idea of
developing a national drug discovery infrastruc-
ture lies the fact that the productivity of drug dis-
covery has decreased sharply despite the growing
knowledge and technology related to the process,
and controversies have occurred about its possi-
ble causes (Epstein, 2006; Ryzewski, 2008; Bartafai
& Lees, 2006; Kubinyi, 2003). Drug companies have
thus urged governments to promote the idea of
outsourcing such development to academia,
which is supposed to be able to bear greater risks.
This idea gained momentum when the National
Institutes of Health (NIH) in the United States pub-
lished their Roadmap Initiative for Biomedical
Research in 2003 to promote constructing an aca-
demic drug discovery infrastructure in the form
Fukushima
12
of public chemical libraries and screening centres
for academic use (Wikstrom, 2007; cf. Mazzucato,
2013). In response, the Japanese government
launched their version of the policy (Fukushima,
2015).
Here, I comment brie y on the peculiarities of
considering the drug discovery infrastructure as
a particular type of (knowledge) infrastructure.
Despite the general usage of the term kiban in
policy discourse, ‘infrastructure’ here means the
very specific purpose of producing drugs, as
opposed to more general infrastructures like roads
and the Internet. The alternative term, the drug
discovery ‘pipeline’, also connotes the horizontal
integration of the temporal procedures from
bench to bedside. Thus, some researchers prefer
using terms like ‘platform’ (Keating & Cambrosio,
2003) to highlight the horizontal assemblage
of knowledge and material rather than the term
‘infrastructure’.
Nevertheless, the term ‘drug discovery infra-
structure’ has its own legitimacy. First, this process
consists of multi-layered entities, ranging from
the national plan to speci c institutions to the
laboratory level, where various aspects of infra-
structure-like characteristics can be spotted,
exhibiting similarity with other types of more
conventional infrastructures, such as databases
open to academic purposes (Star & Ruhleder,
1996; Edwards et al., 2007; Edwards et al., 2013).
Second, the process includes a unique entan-
glement of materiality and knowledge. Although
drugs are an industrial material, they are also what
Barry (2005, borrowing from Bensaude-Vencent
& Stengers, 1996) calls ‘informed material’, which
requires a huge complex of knowledge from
protein science, chemistry, and medicine, wherein
the elements of the knowledge infrastructure play
pivotal roles.
In the following sections, the sub-institution
levels are given priority for the detailed analysis,
but higher levels are by no means unrelated.
The focal institution is RIKEN, a public research
institute representative of basic science in Japan.
RIKEN’s involvement in the infrastructure plan is
the main background. RIKEN has experienced a
series of ups and downs, from its pre-war status
as the pivotal nexus of research and industry to
post-war decline and revival in recent years in
the form of national genomic and postgenomic
research projects given by its supervising ministry
(RIKEN, 2005). After a series of major science
projects, such as Protein 3000 Project (Fukushima,
2016), RIKEN launched a plan to establish a more
tightly woven infrastructure for drug discovery
with a more e ective organization of its branches,
which had not previously been tightly combined
with one another. The following cases both fall
within the larger scheme of RIKEN’s policy6.
The Chemical Biology Centre as
Future Quasi-Infrastructure
The first major topic of this paper is the falter-
ing effort to establish NPEdia (whose name is
abridged from ‘Natural Products Encyclopaedia’),
a database for public use. This project was imple-
mented along with the development of NPDepo,
a public library of natural product compounds.
These plans were launched in parallel with a
government plan to establish a national library
of chemical compounds open to academic use.
Natural products are the chemical entities pro-
duced by living things, such as microbes, plants,
and marine organisms. These entities have bioac-
tivity—namely, the e ects exerted on other living
things. This genre of research has had extensive
relations with drug discovery, most notably in the
case of antibiotics extracted from fungus, such as
penicillin, or recent searches for plants and marine
organisms to provide new seeds for drugs (Fuku-
shima, 2015).
This speci c idea was promoted by a number
of RIKEN’s leading laboratories; among them, the
antibiotic laboratory (of more than 60 members),
which boasts a long genealogy of preceding
laboratories in the same genre of research (Ueno,
2008), has taken the pivotal role. This infrastruc-
tural innovation was accompanied by an organi-
zational plan to establish a new centre for an
emerging hybrid science called ‘chemical biology’,
wherein chemical compounds are used to regulate
and probe the activity of life phenomena. In the
United States, the above-mentioned Roadmap
Initiative policy to promote chemical biology
includes a public chemical library and screening
centre (Wikstrom, 2007); however, controversies
have developed between the NIH and leading
Science & Technology Studies 29(2)
13
scientists there over how best to orient chemical
biology for drug discovery (Fukushima, 2013).
Like Matryoshka (Russian nesting) dolls, the
problem of value oscillation vis-à-vis the devel-
opment of various layers of infrastructure can be
observed on various levels, from RIKEN itself down
to the laboratory practices. One of the focuses
here is the centre level, within which the NPEdia/
NPDepo complex is situated. The chemical biology
centre plan was once intended to establish one
of the hubs for the coming drug discovery infra-
structure, both within and without RIKEN, symbol-
ising RIKEN’s commitment to connect academia
and industry by implementing governmental
biomedical policy more directly. For that purpose,
RIKEN has increased the number of time-limit
centres to improve the infrastructural functioning
of various kinds of large facilities, libraries, and
databases (RIKEN, 2005). The chemical biology
centre, under the leadership of the antibiotic labo-
ratory mentioned above, was once part of this
long-term plan. The centre was intended to be
equipped with not only the database and library,
but also with various assay systems as well as
high-throughput machinery to enable the rapid
examination of ligand–protein interactions, for
public service as well as for their own research.
However, a contradiction has thus been revealed
about what the centre was meant to be from the
beginning.
First, despite the o cial emphasis on the infra-
structural objective, the promoters of this plan
also intended to use the centre to pursue their
own research innovation. I observed this divided
intention during my visit to the laboratory, where
a large part of the researchers’ energy was spent
preparing for the coming centre. In fact, the main
members of the laboratory were subdivided into a
number of teams, each consisting of a team leader
and several members and technicians, each tasked
with various infrastructural obligations, such as
improving the high-throughput machinery, estab-
lishing new assay systems, and collecting and clas-
sifying materials for NPEdia/NPDepo.
Here, the division of labour is not confined
to scientist/technician distinctions; almost all
the scientists were also assigned to one or more
infrastructure-related tasks for the coming centre.
However, the distribution of such workloads was
uneven, with some teams doing basic work like
collecting materials and organizing informa-
tion, while others were only doing their own
homework7.
Many examples of value oscillation occurred
in this complex distributions of workloads. For
instance, the 2008 intra-RIKEN official report,
which is issued every seven years about the
activity of the laboratory, was concerned mainly
with the activities directly related to the infra-
structural aspects of the future centre, while the
outcomes of the individual research activities
were given only passing references. Thus, its M-B
index for emphasis on infrastructure elements
was high. However, these individual papers
were published in major journals and reported
in a separate annual record about the labora-
tory’s academic activity (interview, 24/6/2008). In
addition, the uneven distribution of the infrastruc-
tural workloads led to some rather cutting remarks
by some of the sta about their colleagues’ work.
For instance, after the o cial interview, one of the
team leaders suggested to me that there would
be no need to interview some of them, as their
work was nothing but technicians’ work, not that
done by scientists. Such remarks clearly demon-
strate a contrastively low M-B index score despite
the laboratory’s general policy ( eld note, 20/11/
2007).
The changing discourse of the laboratory head
was a living example of such value oscillation. In a
meeting with the whole laboratory, for instance,
he rather openly warned those who were then
too keen to do service work for outsiders about
their infrastructural duties, such as examining the
bioactivity of the compounds entrusted to them.
Even though these are the sort of preliminary
duties that the future centre would be expected
to carry out, he underlined the possible danger of
doing too much service work for outsiders, which
could decrease the quality of their own scien-
ti c activity ( eld note, 15/4/2008). On another
occasion, he suggested that the sta collaborate
on their entrusted work if they found the job
interesting enough to do as part of their own
research ( eld note, 13/11/ 2007). This impressive
degree of ambivalence was observed throughout
the laboratory, even, as demonstrated, with the
Fukushima
14
same leader, with the M-B index score seeming to
change daily, like stock prices.
NPEdia and NPDepo:
Between Material and
Knowledge Infrastructure
The above example, wherein the whole laboratory
was related to the centre plan, rather simply dem-
onstrates the problem of value oscillation. NPE-
dia and NPDepo, however, present a more subtle
picture of how value oscillation is embedded in
the more complex layers of multiple infrastruc-
tures. To understand this, we must take a closer
look at the very concept of both databases as the
public library of ‘natural product’ compounds. As
I have shown, this project is o cially in line with
the wider national science policy programme to
establish a public library of chemical compounds,
but the uniqueness of this plan lies in its adher-
ence to collecting natural products as opposed
to collecting ordinary chemical compounds, as
directed in the competing scheme of RIKEN’s rival,
the University of Tokyo (Fukushima, 2013)8.
The idea behind this project derives rst from
the historical fact that natural products have
been powerful sources of drug seeds, espe-
cially in microbial cases, which have included a
variety of powerful discoveries, from penicillin
to statins (Newman & Cragg, 2007; Endo, 2006).
Second, the relatively strong tradition of Japanese
research in this area, to which the antibiotic labo-
ratory belongs, led the promoters to maximize
their traditional advantages. Third, the unique
chemical structures of these natural products
were expected not only to promote the search for
drug seeds, but also to lead to the development
of unique bio-probes for basic biological research
(Fukushima, 2015).
NPEdia was designed to supplement the
collection of materials, to serve as a legitimate
knowledge infrastructure in the wider context
of the drug discovery infrastructure, and to
function as an encyclopaedia for natural product
compounds with annotated meta-information,
such as bioactivity and the details of related assay
methods. It was also meant to serve as a catalogue
for NPDepo to give details on the further uses of
the actual compounds that NPDepo provides
Thus, the NPDepo/NPEdia complex was consid-
ered pivotal for the coming chemical biology
centre, and a speci c team was assigned responsi-
bility for them. This team included a leader – who
also acted as o ce manager of the laboratory
administration and coordinator of the other teams
that collaborated to develop the various elements
of the library/database – as well as a couple of
informaticians. This meticulous organization
suggests that the managers of this facility require
full commitment to its development and admin-
istration – demanding high M-B index scores –
unlike other team leaders whose attitudes were
often lukewarm vis-à-vis such infrastructural obli-
gations.
This initial scheme, however, did not develop
as planned, owing perhaps to entangling factors.
First, collecting natural products from individual
laboratories presented a hindrance because these
materials take years or even decades to extract,
unlike commercially synthesized materials; being
thus the object of researchers’ attachment, it is
di cult to get them released for public use (inter-
views, 25/5/2008, 30/6/2011). This aspect can be
interpreted as a certain version of value oscillation:
researchers o cially understand the value of such
a library, but they do not want to commit to it. A
similar situation was found in the mouse genome
database, where young researchers hesitated to
submit their research outcomes to the database
(Hine, 2006a).
Obtaining materials from retiring researchers
before they closed their laboratories was slightly
easier, but changing property rights trends, in
which universities started to strengthen their
control over the products of individual laborato-
ries, are now a problem (interview, 29/5/2014).
Thus, a sort of vicious cycle occurred: the failure to
collect material enough to demonstrate the merit
of such a library with its capacity for processing
information in a high-throughput manner further
diminished incentives for researchers to submit
theirs.
The NPDepo’s delay fostered stagnation in
NPEdia’s development. One of the expected
functions of NPEdia, to serve as a full database
for natural products, proved too feeble to work
autonomously because of competition from rival
databases for chemical compounds. Generally, in
Science & Technology Studies 29(2)
15
chemistry, SciFinder, by the American Chemical
Society, has been one of the world’s most compre-
hensive and authoritative sources of chemical
compounds9. The chemists in the laboratory
a rmed that SciFinder is su cient for all parts
of their work (interview, 14/8/2014). However,
PubChem, released in 2004 by the National Center
for Biotechnology Information (NCBI) as an open
source database, focuses on the biological activi-
ties of small molecules and has recently gained
popularity10. The informatician in charge of NPEdia
explained that in NPEdia’s earlier days, the idea
of an open database speci c to natural product
compounds worthy of trial, such as PubChem,
was still underdeveloped. However, the speed of
data enrichment at PubChem surpassed that of
NPEdia, making it extremely di cult for NPEdia
to compete with its global rival (interview,
29/5/2014).
However, NPEdia could have retained its
advantage if its catalogue function had been
developed further. Natural products often occur
in minuscule quantities in laboratory settings
and are usually very hard to synthesize, which
makes their production challenging for synthetic
chemists – in some cases, global competition has
developed among leading chemists to synthesize
natural products rst11.
This situation differs generally from that of
chemical or genomic databases. For instance, the
chemical databases mentioned above provide
ample data related to methods of synthesis or
about the vendors that sell such compounds. In
the genomic database case, the recent devel-
opment of commercial service companies has
made it possible to quickly produce the necessary
vectors from the genetic sequence information in
such databases when a researcher asks for them.
In other words, there are large networks of articles,
laboratories, and vendors between the data in the
database and the corresponding materials, which
constitute a sub-layer of infrastructure, enabling
the users of such databases to adapt the informa-
tion to develop the materials they need (inter-
views, 22/5/2014; 6/6/2014; 22/8/2014)12.
In the case of natural products, this sub-layer
has not developed fully, because of limited quan-
tities and di culty in reproduction. Thus, even
if data about a particular compound are gained
through the database, the only way to obtain the
compound is to ask the laboratory to share the
substance. According to a veteran natural product
chemist, this is a complicated process because the
laboratory may not exist any longer or because
the laboratory has such a limited amount of the
target compound that it cannot be shared. Even if,
in rare cases, the compound might be synthesized
and sold by vendors, its purity may be question-
able, and further e ort to re ne the compound by
reanalysing its real components may be required
(interview, 22/8/2014).
NPDepo would thus be tremendously bene -
cial for users of such compounds because it would
increase the ease of nding the target compound
in the library, and the open protocol would
simplify the procedure for obtaining material,
eliminating negotiations with individual labora-
tories. NPEdia’s full potential would be realized
in this way as users could refer to the annotated
information within the database and use it as a
catalogue, as well.
However, this potential has not been realized
thus far. Without NPDepo, NPEdia cannot
compete with the existing databases, because its
merit is su ciently strong only with the support
of NPDepo. Thus, the apparent powerlessness of
NPEdia as a small, emerging database should not
be understood solely as the problem of ‘gateways’
in terms of connecting isolated systems to larger
ones (Edwards et al., 2007; Edwards et al., 2009),
but also in the context of the data-material
complex, where the material scarcity of natural
products may have produced a unique set of data-
material relations not seen in the wider genres of
chemical or genetic databases.
This situation also relates to the relative invis-
ibility of the problem of value oscillation here, in
contrast with the preceding case of the chemical
biology centre. Needless to say, as part of the
centre, NPDepo/NPEdia would inevitably invite
value oscillation for those who were obliged
to commit themselves to infrastructural work.
However, the more visible aspect of value oscilla-
tion lies at the sub-layer of the infrastructure – in
the supporting network that enables the process
of converting data in the database to its corre-
sponding materials, under the guise of individual
laboratories’ reluctance to submit their materials
Fukushima
16
to support the coming library as infrastructure.
This contrasts with the case of the chemical
biology centre, where the sway of the M-B index
is much more easily observable as the centre
scheme itself has more manifestly advanced.
The Virtual Library as the Coming
Knowledge Infrastructure?
To observe the knowledge aspect of value oscil-
lation more clearly in the emerging knowledge
infrastructure of NPEdia—which has been real-
ized only to a limited degree—let us brie y exam-
ine a supplementary case: the emerging virtual
library of chemical compounds within the related
scheme of RIKEN’s drug discovery pipeline. This
idea has been promoted by a research group
related to the so-called K supercomputer in Kobe,
West Japan, as part of a scheme to redevelop the
city within a large biomedical complex after the
199 5 e ar th qua ke (K BIC, 2012) . K , f ro m kei, meaning
‘qua drillion’ in Japane se, s ymbolizes t he computa-
tion of 10 peta ops per second; this computer is
intended to have the fastest computing speed in
the world13. A number of projects related to this
supercomputer are specifically concerned with
computational drug discovery. There are at least
two major plans: The rst is to build a huge library
of virtual chemical compounds, and the other to
analyse ligand protein interaction using big data14.
The rst plan relies on use of Archem – existing
software originally designed for rapid analysis
of the optimal paths for synthesizing the target
compound – so as to produce large amounts
of virtual compounds by reversing the process.
The research group succeeded in producing
ve billion virtual chemical compounds (Ashida,
2010), an astronomical number compared to
NPDepo’s tens of thousands of compounds or to
those of the drug companies, perhaps 10 million
at best (interview, 12/5/2012). However, this does
not include some of the complex cases of natural
products that may often exhibit 3D structural
complexity, such as chirality (interview, 2/9/2014).
The purpose of this library is to examine the
possible interaction between virtual compounds
and the target proteins to predict the best-fit
cases. The rising expectation that the supercom-
puter would handle huge computational loads
made computer companies like Fujitsu eager to
participate in this newly emerging eld15.
However, these methods are not without
problems. First, the issue of computational
explosion remains in terms of how to balance
between calculations based upon either
Newtonian or quantum dynamics, and how (not)
to calculate the influence of the molecules in
the mediating substances, such as solutions or
intracellular environments, existing between
proteins and their ligands (interview, 12/8/2014).
Most problematic, however, is the huge amount
of noise. Just as in the past case of combinato-
rial chemistry, where the once-popular high-
throughput production of new compounds has
lost its glamour because of the huge nonsen-
sical structures it produces (Barry, 2005; Borman,
2004), the virtual library must also sort signi cant
structures from the huge amount of meaningless
ones (interview, 2/9/2014). In fact, past reports
indicate that existing calculations not done by K
computers have produced a prediction success
rate of less than 10% for proper protein-ligand
binding (Kanai, 2012).
Thus, the second programme is designed to
raise this success rate by enabling the computer
to learn the pattern of such bindings using the
existing databases on protein–ligand relations.
In principle, this is performed similarly to the way
a neural computer learns ngerprints or human
faces. The success rate for prediction is expected
to double from the traditional way of computing
the molecular dynamics of these interactions
(Kanai, 2012; Okuno, 2012).
In terms of value oscillation, these new
radical features reveal intriguing problems not
clearly seen in the NPEdia case. Although these
programmes are still largely in development and
are not ready for public use, their main researchers
have enumerated hindrances to plan develop-
ment, some of which I interpret as indicating
value oscillation. For instance, they are uncertain
whether they should continue maintenance work
to promote the public use of this library as a
resource centre after the present phase of system
development. The laboratory head responsible for
this scheme seems to have high M-B index scores,
as he fully recognizes the importance of the
infrastructural aspect of his role. His somewhat
Science & Technology Studies 29(2)
17
subtle value oscillation, then, may derive from
his peculiar background, a hybrid of computing
sciences and other disciplines, such as biology
and astronomy. This background often makes him
unsure of his position in each of these commu-
nities. At informational science meetings, he
often nds his colleagues too excited over trivial
software innovations; in our terms, he regards
them having insu cient M-B index scores for what
they should do. However, in life science meetings,
he feels that his computational approach is often
merely subcontract work for the mainstream wet
approaches, meaning that, paradoxically, he is
dissatis ed with the way the biology community
regards his work as infrastructural.
This means that his generally high M-B index
is not sustainable all the time; occasionally, he
feels that the essential work that he assigns to
his sta – related to deleting all possible noise
or the nonsensical chemical structures produced
in the library – can be problematic when consid-
ering career development possibilities after such
tedium (cf. Hine, 2008 for similar uncertainty)
(interview, 2/8/2014).
The researcher in the second programme for
the machine learning of ligand–protein binding,
who seemed to have a very low M-B index score,
shrewdly evaded the service aspect of work by
entrusting it to a venture company that he estab-
lished, exempting his laboratory from any further
infrastructural work so that he could concen-
trate on the development of the new method
(interview, 8/8/2014). Nevertheless, the value
problem is unavoidable when his new method
is applied in the real drug discovery context. The
problem is how to gain support from chemists
for synthesizing their computational predictions
into the embodied compounds. The researcher
admits that to synthesize the outcome of his
very pragmatic machine learning with a process
that is theoretically blackboxed would be consid-
ered by the synthetic chemists’ community to be
service work without scienti c value – the M-B
index score is close to zero here; thus, he asks for
help with synthesis only from an old friend from
high school. In the case of the virtual library, the
researcher from the beginning plans to entrust
the job to companies to avoid possible con icts
with scientists who do not want such subcontract-
like duties (interviews, 8/8/2014; 2/9/2014).
These programmes are in a development stage
wherein their innovative characteristics are spot-
lighted in public, but eventually, they will move
into a maintenance – that is, infrastructural –
phase. The knowledge aspects of such infrastruc-
tural e orts entail the problem of data-material
relations similar to the case of natural products
above – namely, the problem of collaborating
with synthetic chemists whose M-B index scores
are often close to zero in terms of doing service
work purely for such a virtual method. Likewise, in
natural products, the chemists tend to be hesitant
to become involved with the library plan, which
is also interpretable as showing a low M-B index
score.
This rather unstable relation between the
knowledge and related material aspects in the
form of non-collaboration by synthetic chemists
shows the inherent instability of the in-process
knowledge infrastructure. On this point, another
specialist in the simulation of protein structures
who participates in the K computer programme
pointed out the inevitable duality of the infra-
structural and innovative aspects of computer
technology and the di culty of balancing them.
He noted that computer technology is now
widely distributed even in the basic tools of the
structural analysis of proteins – namely, in X-rays
and NMR spectroscopy – where complex signals
are analysed with the help of computerized data
processing. Thus, he underscored that even in
his laboratory, the aspects of the cutting edge
of innovation and infrastructural work exist side
by side. He emphasized that the latter should be
treated carefully in such ways as developing and
ne-tuning the software needed for such simu-
lations, which is ordinarily seen as infrastruc-
tural work that does not produce appreciable
credentials; thus, careful persuasion is needed to
enlist members of the laboratory for such work
(interview, 12/8/2014).
Discussion
The main claim of this research is that value oscil-
lation is intrinsic to consolidating and maintaining
infrastructures of any type. The problem, then,
Fukushima
18
is how it takes shape and is dealt with accord-
ing to different degrees of infrastructure con-
solidation within multiple layers. In fact, a series
of preceding discussions have taken place on
the perpetual tension or contradiction between
the approaches of biology and computer sci-
ence, often dubbed ‘wet’ and ‘dry’ approaches in
the research on genomic sciences. For instance,
García-Sancho (2012) traces the relation between
genetic/protein science and sequence technique
as a constant swinging between antagonism
and accommodation. In more detailed micro-
scopic studies, Lewis and Bartlett (2013) discuss
the problem of bio-informatician identity, which
sways between scientists pursuing new knowl-
edge and technicians supporting the jobs of wet
biologists. In preceding studies more on knowl-
edge-infrastructural aspects of laboratory work,
Star and Ruhleder (1996: 126) refer to a primordial
case of value oscillation that they call ‘tool build-
ing and the reward structure’ in their case study
of the gene-sequencing network. In relation to
the mouse-based genetic database, Hine (2006a)
details various potential con icts and their avoid-
ance in cases similar to the institutional separation
between biologists and the resource centre, while
her analysis of systematics (Hine, 2008) delineates
the value oscillative aspects in more detail.
Compared to these preceding examples, the
two cases in this paper appear to be situated
on a more complex institutional ladder – one in
the chemical biology centre, the other in the K
computer project, and both within RIKEN’s wider
programme. These two are also situated in the
wider context of a more established knowledge
infrastructure: the databases of chemical and
genomic information.
Hence, the phenomenon of value oscillation is
most visible at the rather established level of the
centre, whose purpose from the beginning has
been torn between the goals of an infrastructural
service centre and those of a centre for innovating
research; the M-B index appeared to be literally
uctuating, as observed in both the leader’s and
researchers’ discourses and action in various
contexts. In contrast, the subsequent cases of
NPEdia and the virtual library demonstrate a more
complex picture owing to their being embedded
in multiple layers of both organizations and other
databases while falling short of establishing a
proper level of autonomy. Hence in the case of
NPEdia, the value oscillation is spotted in the
sub-layer that supports this database, while in the
case of the virtual library, diverse strategies were
observed for avoiding a double-bind situation:
that is, the shrewd avoidance of a further commit-
ment to maintenance and dissatisfaction with
the indeterminate character of the concerned
researcher’s role in terms of infrastructure devel-
opment. Thus, compared to the preceding
arguments that emphasized a rather black-and-
white image of contradictory values, these cases
exhibit a more subtle and layered embodiment of
value oscillation, as well as diverse ways the prac-
titioners deal with it.
Conclusion
I have argued here that current studies of infra-
structure have su ered from historical amnesia
lacking critical dialogue with the preceding Marx-
ist discussions on Infrastructure in terms of the
genealogy of concepts. I have pointed out that
an opportunity has been missed for theoretical
dialogue in relation to at least three major ques-
tions, the last of which is highlighted in this paper:
the pivotal importance of the Marxist opera-
tion of inverting the unseen value of Infrastruc-
ture, which has been occulted by the shadow of
Superstructure – the operation represented by
the phrase ‘turning Hegel on his head’. I claimed
that this operation is intrinsically isomorphic with
Bowker’s ‘infrastructural inversion’, now regarded
as pivotal in contemporary research on this topic.
Behind the need for this operation lies the recog-
nition that the concept of infrastructure is an oxy-
moron, imbued with contradictory meaning – that
is, infrastructure is endowed with power while it is
simultaneously inferior to the surface value.
‘Value oscillation’ is the term used to describe
this double-bind situation whereby practi-
tioners hang in indeterminacy between opposite
vectors, and the M-B index is the tool used to
visualize these oscillating values. Two cases of
such value oscillation were taken from the drug
discovery infrastructure building in Japan where
the knowledge of drugs is uniquely entangled
with the physical material in a complex, layered
manner.
Science & Technology Studies 29(2)
19
To elucidate further implications of my
approach here, we must note that the recent
rise in concern with the infrastructure in the
STS community derives not only from growing
academic interest in such individual cases as the
computer network or energy infrastructure but
also from increasing attention within the research
community to the more structuralized, longue
duree elements of socio-technical development
rather than to the early and rapidly changing
aspects of technoscientic transformation. These
renewed intellectual concerns can be observed
in such diverse expressions as a reference to the
‘cold’ situation (Rip, 2010), the ‘obduracy’ of urban
technology (Hommels, 2005) or even ‘the shock of
the old’ (with regard to technologies) (Edgerton,
2006; cf. Fukushima, 2015).
Two points can be drawn from this observa-
tion. The rst is the merit of talking about infra-
structure vis-à-vis the related concepts cited
above. Conceptually, infrastructure leads us to
focus on the dual aspects of a) its power to exert
in uence upon that which hinges upon it and b)
its invisibility. In this article, I have pointed out the
diverse strategies produced by value oscillation,
ranging from devotion to shadow work – that is,
e orts to raise the status of what is invisible – to
the minimal commitment devoted to maintaining
and repairing infrastructure. Beyond the micro-
sociological examples presented in this paper,
larger-scale and more historical consequences of
such value oscillation will be similarly important
in further examining the longitudinal dynamics
of the infrastructure at large – represented, say,
by such instances as the recent issue of roads and
bridges in decay, owing to politicians’ general lack
of interest in their proper maintenance (Nemoto,
2011).
The second point is the yet unexamined rela-
tionship, in this era wherein STS scholarship high-
lights the rapidly changing, unstable network
of humans and nonhumans, between current
concepts of infrastructure and the century-old
use of ‘structure’ in the social sciences. Though
not detailed above, the concept of infra-‘structure’
is not only comparable to its Marxist counterpart
but it also partakes of the larger genealogy that
has taken its intellectual inspiration from the
Fukushima
concept of structure found in structural functional
sociology or even structuralism.
Take, for instance, my formulation of value
oscillation vis-à-vis the dual aspects of infrastruc-
ture – namely, its power to exert in uence and
its invisibility. If we slightly modify this idea to
consider the contrast between the various forms
of our ‘existence’ in terms of l’engagement, and
the power of invisible structure – whatever that
means – to exert an implicit in uence upon this
existence, this contrast dimly echoes a well-known
historical controversy: Sartre’s revised concept of
existentialism, somewhat modi ed by his conver-
sion to historical materialism (Sartre, 1976), versus
Levi-Strauss’s (1966) fatal criticism in which he
highlighted the determining power of classi ca-
tion and taxonomy as the invisible structure that
regulates our very understanding of history. In
fact, the missing link with Marxism which I have
highlighted in this paper is only the tip of the
iceberg in terms of possible linkages. Godelier
(2011; Godelier et al. 1978), for instance, can also
be regarded as a concrete embodiment of the
con uence of both Marxism and structuralism,
which later leads to the thesis of ‘classi cation as
infrastructure’ that is foundational for the current
discussion of knowledge infrastructure.
My emphasis on the resurgence of the intellec-
tual concern with the concept of structure lurking
in infrastructural studies, however, does not deny
the novelty of the later approach vis-a-vis the
earlier. Compared to the more traditional ways
of dealing with structure – either as an invisible
mental structure or as the social structure, mostly
as it relates to humans – current infrastructure
studies provide a series of fresh perspectives on
the socio-technical complex. Its workings can
be more closely observed through modern than
through more traditional ways, such as with case
studies on roads and databases, which were unan-
ticipated in the past. This is why infrastructure
studies, even if they share a concern with past
problematics in the social sciences, do not merely
repeat the past (cf. Marx, 1994) but may be consid-
ered as more finely-tuned re-examinations of
persisting controversies from the past, generated
by the historical genealogy of concepts through
which we see the world.
20
Notes
1 The earliest version of this formula appeared in the posthumous publication of a draft called Grundrisse
der Kritik der politischen Ökonomi (Outline of the Critique of Political Economy), written around 1857–58.
2 The labour process theory is a possible candidate for bridging these two research traditions (Braver-
man, 1974; Nakaoka, 1971; Knights & Willmott, 1990; Sturdy et al., 1992). Vann and Bowker (2006),
somewhat exceptionally, re ect this line of concern by focusing on the production side of e-science,
emphasising the role of funding agencies, thus recalling classical arguments on the role of the capital-
ist class.
3 This nuance can be contrasted with technological regimes, highlighting the total visibility of the phe-
nomena (Rip, 1995; Rip & Kemp, 1998, followed by many).
4 Included in this category are requests for more attention to neglected aspects of laboratory techni-
cians and technical workers at large (Barley & Bechki, 19 94 ; Bar le y & Orr, 19 97) a s wel l as t he Bur ri ’s
(2008) analysis of radiologists’ strategy in terms of cultural capital and boundary work.
5 This paper draws on data from various phases of my ethnographic research in the antibiotic laboratory
and chemical biology (2007–2010), the Protein 3000 Project (2010–2013), and drug discovery infrastruc-
ture (2013–), which are all related to RIKEN. Interviews were conducted with researchers in various gen-
res on the topic of this theme, both inside and outside the institute.
6 RIKEN’s recent programme can be seen at http://www.riken.jp/dmp/english/index_en.html (accessed
22/8/2014)
7 In 2007, ten teams covered the following themes:
1. Streptomyces
2. Genetic analysis of secondary metabolites
3. Fractions
4. Chemical library
5. Compound array
6. Protein analysis
7. Cancer related issues
8. Cell cycles
9. Transcription
10. Chemical compounds at large 2–5 and 10 are largely for infrastructural works
8 See Parry (2004) for the history of the U.S. Natural Products Repository of the National Cancer Insti-
tute. Compared to this global scheme, NPDepo is straightforwardly intended for public use for both
research and drug discovery.
9 SciFinder’s o cial home page is http://www.cas.org/products/sci nder (accessed 22/8/2014). For its
history since 1995, see Chemical Abstract Service (2007).
10 Pu bCh em, l aun che d in 2 004 b y the N ation al Ce nter for Biotechnology Information (NCBI), is a free-
access database focusing on the biological activities of small molecules. It has experienced serious fric-
tion with SciFinder (Marris, 2005). https://pubchem.ncbi.nlm.nih.gov/about.html (accessed 22/8/2014).
11 T h e g l o b a l c o m p e t i t i o n o f s y n t h e s i z i n g t a x o l , a n a n t i - c a n c e r m a t e r i a l e x t r a c t e d f r o m P a c i c yew, is
such a case. In 1993, R. Holton succeeded in its total synthesis. Despite millions of dollars spent, the
resulting method, which has more than 40 steps, has not been used for actual drug production (Sato,
2007: 78-86).
12 T he ca se p re se nt ed h er e h ig hl ig ht s th e li mi t of Pa rry’s (2004) claim concerning the growing use of what
she calls the dominance of ex-situ data mining. In addition, this line partially refutes Elvebakk’s (2006)
claim that chemistry has largely become a matter of examining information.
13 http://www.aics.riken.jp/en/k-computer/about/ (accessed 20/8/ 2014).
14 h ttp :// ww w.m ex t.g o.j p/ b_m en u/h ou dou /24 /09/_ _ic sF ile s/a eld le/2012/09/04/1325265_1_1.pdf
(accessed 20/8/2014).
Science & Technology Studies 29(2)
21
15 T hu s, t he Un ive rs it y of To ky o, Fu jit su , an d t he K owa C om pan y an nou nc ed t he di sco ve ry o f an an ti -c an -
cer drug candidate through computer-based virtual design. http://www.rcast.u-tokyo.ac.jp/research/
report/2014/140807PR.pdf (accessed 18/8/2014).
Acknowledgements
I thank all the interviewees in RIKEN and elsewhere for kindly answering my questions. I thank Geof Bowker
for introducing me to the world of knowledge infrastructure studies; Antti Silvast and two anonymous
reviewers for their constructing comments. This research was conducted with the support of grants-
in-aid for scienti c research from the Japan Society for the Promotion of Science, under Grant 26350359
(2014–2016).
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