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Paper to be presented at the Summer Conference 2009
on
CBS - Copenhagen Business SchoolSolbjerg Plads 3
DK2000 FrederiksbergDENMARK, June 17 - 19, 2009
THE EMERGENCE OF ARCHITECTURE IN MODULAR SYSTEMS: COORDINATIONACROSS BOUNDARIES AT ATLAS, CERN
Philipp TuertscherVienna University of Economics and Business
Raghu GarudPennsylvania State University
Markus NordbergCERN
Abstract:The development of complex technological systems can be coordinated by pre-specifying system architecture.However, what are the origins of architecture? To address this question, we explore the development of ATLAS,a complex technological system that is being developed at CERN, the European Organization for NuclearResearch. Our study suggests that the emergence of technological architecture is characterized by an ongoingprocess of negotiations across actors with different perspectives who have to justify and explain their designrationales to one another. Such a process results in what we call as interlaced knowledge partial overlappingof knowledge across actors in an overall knowledge network. Such interlaced knowledge generates a deepersystemic understanding of the requirements of the various components, making it possible for multiple groupsto anticipate latent interdependencies and coordinate interdependent contributions even as the design emerges.
JEL - codes: O32, O33, -
1
Please do not circulate as this is a first draft.
THE EMERGENCE OF ARCHITECTURE IN MODULAR SYSTEMS: COORDINATION ACROSS BOUNDARIES AT ATLAS, CERN1
Philipp Tuertscher Vienna University of Economics and Business
Raghu Garud Pennsylvania State University
Markus Nordberg CERN
February 28, 2009
Paper submitted for consideration for the DRUID conference at Copenhagen, 2009
1 We thank the many scientists at ATLAS, CERN who have contributed generously of their time. We also thank Carlyss Baldwin, Paul David, Simone Ferriani, Oliver Gasmann, Simon Grand, Barbara Gray, and Georg von Krogh for their valuable comments which helped to improve this paper.
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THE EMERGENCE OF ARCHITECTURE IN MODULAR SYSTEMS: COORDINATION ACROSS BOUNDARIES AT ATLAS, CERN
ABSTRACT
The development of complex technological systems can be coordinated by pre-specifying
system architecture. However, what are the origins of architecture? To address this question, we
explore the development of ATLAS, a complex technological system that is being developed at
CERN, the European Organization for Nuclear Research. Our study suggests that the emergence of
technological architecture is characterized by an ongoing process of negotiations across actors with
different perspectives who have to justify and explain their design rationales to one another. Such a
process results in what we call as ‘interlaced knowledge’ – partial overlapping of knowledge across
actors in an overall knowledge network. Such interlaced knowledge generates a deeper systemic
understanding of the requirements of the various components, making it possible for multiple groups
to anticipate latent interdependencies and coordinate interdependent contributions even as the design
emerges.
3
Many technological systems are organized to benefit from the contributions of many different
organizations. To reduce transactions costs, the principle of decomposability (Simon, 1962) underlies
the division of labor across organizations within such technological systems. Decomposability
involves the division of complex problems into smaller subtasks so as to facilitate distributed problem
solving and reduce complexity. These distributed efforts must be integrated for the system to work, a
task that requires coordination across boundaries (Clark & Fujimoto, 1990; Ulrich, 2003). Such
coordination may start even before the development of a technological system. Typically, this involves
the specification of the functionality of the various components and their functionality as well as the
allocation of subtasks to different contributors (Baldwin & Clark, 2003; Langlois, 2006; Simon, 1996).
Given the uncertainties involved with innovation, however, such coordination can be
problematic. For instance, it may be difficult, if not impossible, to find the optimal decomposition of
the technological system ex ante when many system requirements and features have yet to be
identified and developed. Complicating matters, developments that occur with one component may
change the specifications of another. As a result, many design decisions may be only provisional
during the early stages of innovation (Mihm, Loch, & Huchzermeier, 2003).
How, then, are the various parts of a system coordinated during innovation? A way to provide
such coordination is to pre-specify architectures. However, pre-specification can both enable and
constrain actors in specific ways (Garud & Jain, 1996). Realizing this, the engaged actors actively try
to shape the emerging architectures based on their own frames of reference such that the emerging
architecture enables their vision of the project. The process of emergence, therefore, is likely to be
fraught with negotiations and potential conflict. In other words, not only are traditional coordination
mechanisms through architectures not available, but the very process of trying to institutionalize such
mechanisms generates dynamics that require coordination across a distributed set of actors.
These discussions point to two central questions that drive this paper. First, how do
architectures emerge? Specifically, what are the processes and underlying mechanisms that shape the
emergence of an architecture? A related question concerns a 'coordination of coordination' problem.
Specifically, what are the mechanisms that can engender coordination among actors trying to agree
upon an architecture that, only when it has been institutionalized, an provides embedded coordination?
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To address these issues, we studied the development of ATLAS2, a complex technological
system that has been developed at CERN, the European Organization for Nuclear Research. The
development of ATLAS is revelatory with respect to several dimensions. First, the project is a
collaborative effort amongst approximately 2000 scientists and engineers from more than 165
institutions located in 34 countries. The different groups contributing to the project are distributed
around the globe with few opportunities to meet physically and engage in collocated collaboration.
Second, ATLAS involves many specialized scientists and engineers from a variety of backgrounds,
such as high-energy physics (HEP), semi-conductor technology, cryogenics, superconductivity,
material science, electronics, opto-electronics, electrical engineering, mechanical engineering, and
computer sciences, to name just the most important disciplines. Third, the scientists and engineers who
are involved in this decentralized project have been collaborating in the absence of traditional
organizational structures or hierarchy. Finally, the ATLAS detector has not evolved from a dominant
design but represents a one-of-a-kind technological system, making it an excellent case for studying
the emergence of technological architectures.3
We offer a perspective that acknowledges ongoing interaction between both the social and
technical facets of a given system. Actors are embedded within such systems, mobilizing its resources
towards their own individual and collective purposes. We use this broader perspective to motivate a
longitudinal study of the development of a complex innovation project, the ATLAS experiment at
CERN. Whereas prior literature on modularity focuses on specifications that are clearly understood a
priori, we suggest that there is value in understanding the role of ambiguity in the emergence of
architectures. In particular, we explore the role of different perspectives that arise from alternative
technological solutions and interpretations. We study how these diverse views are sorted out through a
process of confrontation and justification. Such engagement generates what we call ‘interlaced
knowledge’ – a partial overlap of knowledge across actors and groups. Such interlaced knowledge, we
suggest, facilitates coordination of the distributed development efforts as the architectures emerge.
2 ATLAS is an acronym for A Toroidal Large Hadron Collider Apparatus, but is now used simply as a name. 3 It should be noted that, ex ante, there was no inevitability in the emergence of a specific architecture – there are three other experiments that are unfolding, each with its own architecture. In fact, one of the experiments, CMS, also has been designed to identify the Higgs Boson particle just as the Atlas experiment has been, but, the architectures of the two detectors are very different.
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MODULAR ARCHITECTURES
The existing literature on innovation points to the role of modularity and architecture in the
coordination of innovation systems (Baldwin & Clark, 2000; Henderson & Clark, 1990). A modular
architecture has certain advantages over other designs with respect to coordination (Sanchez &
Mahoney, 1996). This type of architecture consists of modules that can be used as self-contained
building blocks for high-level systems. Each module interacts with another only through standardized
interfaces that define functional, spatial, and other relationships among the components (Garud &
Kumaraswamy, 1995). In this way, modular architecture allows for a range of variations in its loosely
coupled components without having to change the designs of other components (Sanchez, 1995). As
long as components conform to standardized interface specifications, there is no need to directly
manage or monitor the processes of the individual component developers.
While modular components can be developed autonomously by different groups, coordination
of the overall development process is generated because of the presence of interface specifications
embedded in the architecture, thereby shifting the burden of coordination away from managerial
authority (Sanchez, 1995). Less need for managerial coordination makes it possible to engage in
parallel and distributed processes even while reducing costs (Garud & Kotha, 1994). In addition,
modularity increases the range of manageable complexities because the scope of interaction between
elements or tasks is limited by agreed-upon standard interface specifications (Baldwin & Clark, 2000).
Moreover, modularity is a means to accommodate uncertainty. Modular architecture is flexible
because standardized interfaces allow for variations in components (Ulrich & Eppinger, 2000) that
may be substituted in response to market and technological changes (Garud & Kumaraswamy, 1995;
Sanchez & Mahoney, 1994).
However, these benefits are obtained when interfaces have been specified and understood by
the actors, a situation that is typically encountered after the emergence of a dominant design. In many
innovation systems, however, architecture needs to be created in the first place (Wood & Brown,
1998). While several scholars have studied how dominant architectures are selected in an evolutionary
process on an industry level (Tushman & Murmann, 1998, 2003), there is known about the emergence
of a specific architecture on the organizational level. The puzzle is that, on the one hand, architecture
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is required for coordination, but on the other hand, coordination is required for the architecture to
emerge.
How do architectures emerge?
Current research on modularity focuses on the natural partitioning of complex technological
systems. For instance, Baldwin and Clark (2003) suggest that technological systems have “natural
transfer bottlenecks” that represent optimal locations for the decomposition of complex technological
systems into components. Recent contributions provide tools and heuristics, such as the “design
structure matrix” (Baldwin & Clark, 2005; Eppinger, Whitney, Smith, & Gebala, 1994), to identify
natural boundaries between partitions of complex systems. The intent of such tools is to offer “design
rules” (Baldwin & Clark, 2000) that are useful for organizing and improving the architecture of
existing systems. Similarly, recent work on task decomposition by Ethiraj and Levinthal (2004)
suggests that the problem of designing a complex system can be represented as the search for the
optimal modular architecture. Common to these approaches is that they presuppose the existence of an
optimal architecture, determined by properties of the technology, that needs only to be discovered.
The partitioning of novel systems is not as simple as the literature suggests. Because many
interdependencies between components of emerging technological systems are latent (Alexander,
1964) and become visible only with developmental work, it is not feasible to identify natural
boundaries within novel systems even if they may seem obvious post hoc. Moreover, it is difficult to
discover architecture that is inherent when a system and its components are co-emerging (Garud &
Munir, 2008). Even if emerging architectures build upon existing technologies, novel ways of linking
the existing components may cause interference that may not have been observed in prior systems
(Barry & Rerup, 2006).
Consequently, rather than assume that designers can identify architectures inherent in
technological systems, we would like to draw attention to additional social factors that influence the
emergence of architecture. For instance, Bijker, Hughes and Pinch (1987) illustrated how “interpretive
flexibility” surrounds the emergence of technologies as different social groups, through their
engagement, shape the path through which technological systems develop. Indeed, strategic actions of
firms involved are critical in shaping these technological paths (Tushman & Rosenkopf, 1992). As
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these paths emerge, institutional pressures in the form of standards (Tushman & Murmann, 2003) can
generate path dependencies (David, 1985).
The presence of these various technological, institutional and social contexts of the actors
involved in complex projects results in a situation where coordination is not automatically guaranteed
by the system architecture as it has yet to emerge. In determining the architecture, differences of
opinion are bound to arise as members from different communities with different perspectives interact.
Key design decisions revolve around issues such as detailing the boundaries of each component and
establishing stable interface specifications to ensure smooth functioning between modules. A number
of interdependencies may exist among components that make it difficult to identify the “one best”
(i.e., optimal) solution. For example, more physical space for one system could imply less for another.
If each group tries to optimize the performance of its own component, conflicting claims are bound to
arise as to ways the geometrical boundaries of the components should be specified. Similar differences
are likely to emerge around other specifications, such as, in the case of ATLAS, the thermal or
electromagnetic properties of interdependent components.
Consequently, a central task is to understand how a disparate group of actors with different
perspectives are able to coordinate their activities to develop an architecture. It is to this task that we
focus our attention. Specifically, we study the development of a complex technological system during
its early stages when its architecture had yet to emerge and stabilize. In our study, we consider
alternative interpretations of the architecture as it emerged, the controversies that were generated, and
how they were resolved (see Galison (1997) for disagreement that unleash social dynamics of
controversy particularly in scientific settings). This provides us with a more in-depth understanding of
the micro-processes of coordination across emergent boundaries in the emergence of a technological
system.
RESEARCH DESIGN
This research investigates the development and construction of a complex technological
system, in this case a detector that measures subatomic particles in a high energy physics (HEP)
experiment. Specifically, we study the ATLAS experiment at the European Organization for Nuclear
Research, known as CERN, in Geneva, Switzerland. The development, construction and running of
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the actual experiment is organized in the form of a collaboration, i.e., a distributed problem-solving
network. ATLAS is an archetypal example of this type of scientific project; similar endeavors can be
found in basic physics, astronomy, and even life sciences (Galison & Stump, 1996).
The development of ATLAS is a revelatory case on several dimensions. First, the project is a
collaborative effort amongst approximately 2000 scientists and engineers from more than 165
institutions located in 34 countries. The different groups contributing to the project are distributed
around the globe with few opportunities to meet physically. Second, ATLAS involves many
specialized scientists and engineers from a variety of backgrounds, such as HEP, semi-conductor
technology, cryogenics, superconductivity, material science, electronics, opto-electronics, electrical
engineering, mechanical engineering, and computer sciences, to name just the most important
disciplines. Third, the scientists and engineers who are involved in this decentralized project have
been collaborating in the absence of traditional organizational structures and hierarchies. Finally, the
ATLAS detector has not evolved from a previous design thereby making it an excellent case for
studying the emergence of technological architectures.
Data Sources
We had the opportunity to collect different types of data from a variety of sources. Archival
records, meeting minutes, electronic mailing list archives and written reports were used as the main
sources of data for the longitudinal study that explored the emergence of the ATLAS detector.
Moreover, we were fortunate to obtain the right to use CERN archives that contain internal memos,
technical reviews and other similar material. In addition to documents from the CERN archives,
personal notes written by participants of the meetings offered insights into the micro details of
emergence that were not readily apparent in the meeting minutes.
Documents of the discourse that unfolded in co-located meetings were complemented by
electronic mailing list archives that captured real time ongoing conversations amongst development
groups who were globally dispersed. As a result, a significant amount of information regarding the
events, the participants, and the context within which the architecture emerged was readily available
and easily retrievable. The availability of this searchable mailing list archive, which contains tens of
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thousands of messages dating back to 1993, proved very useful for reconstructing events in the
emergence of the ATLAS architecture.
During field visits, we conducted semi-structured interviews with 32 scientists and engineers
involved with the collaboration throughout the genesis of ATLAS. Some of these actors were
interviewed on multiple occasions. These respondents helped us make sense of the many technical
details. They also helped us identify controversies and differences in opinion that existed during the
emergence of the ATLAS architecture. Indeed, respondents had no difficulty remembering
controversial issues, such as around the ‘air core toroid decision’ or the ‘inner detector cooling
review’. In addition, during eight field visits conducted over a period of two years, each typically
lasting one week, we had the opportunity to observe conferences, participate in meetings, and engage
in many informal conversations with members of the ATLAS collaboration.
Data Analysis
We adopted a process perspective (Mohr, 1982) to explore the dynamics of emergent
architectures. In order to generate a longitudinal study, we relied on archival records that were created
from the very beginning of the collaboration (Van de Ven, 1992). In many cases, the same event had
been discussed in various types of meeting, such as working groups, review panels, or plenary
meetings. Although the descriptions of the events were often recounted from different perspectives,
they were mutually confirming, thereby generating confidence in the quality and depth of the data.
Overall, we analyzed several hundred pages of meeting minutes and correspondence that
covered the development of ATLAS from 1991 to 2003. We also studied documents such as the Letter
of Intent, Technical Proposal and the Technical Design Reports of the ATLAS components. These
detailed descriptions of the technological concepts and design considerations represented snapshots of
the ATLAS architecture for the years 1992, 1994, and 1997. These data were complemented by semi-
structured interviews and many informal conversations we had with scientists and engineers during
eight field visits over a period of two years.
We constructed a database that contains the controversial issues identified by the respondents
as well as other controversies that were captured in the archival data. The database includes the events
around these controversies as well as our interpretations (Miles & Huberman, 1984). We captured how
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the controversial issues were resolved and tracked changes in the technical architecture before, during
and after each event.
Consistent with a process perspective, we considered each event as an important occurrence
within a larger flow of events (Van de Ven, 1992); an approach that helped us generate a deep and
consistent understanding of the unfolding processes. We focused on the controversial issues that were
identified and paid particular attention to the motivations and justifications of the actors involved. In
particular, we studied if and how these controversies were resolved as the advocates of the different
technological components and the various groups confronted one another in meetings and review
panels. As Knorr-Cetina (1999: 190) noted in her work on HEP experiments, “discourse is … the
activity through which much of the construction work is not only exhibited, but done.”
Beyond the historical reconstruction of the emergence of the ATLAS detector through the
analysis of archival records, we also used additional approaches to data analysis to complement the
historical account. Specifically, we used bibliometrics and social network analysis to infer the
collaborative structure over time and identify the locus of problem-solving activity throughout the
emergence of ATLAS. We used Qualitative data from archival sources, interviews, and electronic
databases to identify instances of justification in different subsystem communities. For instance, we
used ‘latent semantic analysis’ (Deerwester, Dumais, Furnas, Landauer, & Harshman, 1990) to
explore discourse around controversies that we had identified through our qualitative probe of the
data. To understand the structure of the distributed yet collective knowledge that emerged over time,
we used co-word analysis. In combination, latent semantic analysis and co-word analysis helped us to
generate graphs of different subsystem’s knowledge structures using network analysis techniques. We
present some of these results in this paper.
THE EMERGENCE OF ATLAS
ATLAS is one of four particle detector experiments unfolding at the Large Hadron Collider
(LHC), a new particle accelerator at CERN. The detector, completed in 2008, is 45 meters long and 25
meters in diameter and weighs about 7,000 tons. By measuring the reactions of massive particles not
measurable by earlier low-energy accelerators, ATLAS is expected to shed light on new theories of
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particle physics that go beyond the Standard Model, the most comprehensive model of particle
interactions available today.
The ATLAS project, now involving around 2,000 scientists and engineers from 167
institutions from 37 countries – has its roots in UA1 and UA2, two very successful HEP experiments
conducted at CERN in the 1980s. These experiments became well known for the discovery of the W
and Z bosons that led to a Nobel Prize awarded to CERN physicists in 1984. While these two
experiments were running, a core group initiated the development of future particle detector concepts.4
Members of these “proto-collaborations”, as they are called by Knorr-Cetina (1995), met during HEP
conferences where they discussed new concepts. In 1989, CERN started funding institutions to
conduct R&D and to develop technologies for new generation detectors. Four independent
collaboration clusters emerged from this initiative in the early 1990s. Each cluster was comprised of
multiple R&D projects (please see Table 1 for an overview) and each was built around a new detector
concept.
--- Table 1 here ---
A critical incident occurred in 1992 when CERN decided that it was not feasible to continue
with four large experiments. As a consequence, the collaborators tried to join forces to develop and
construct two independent detectors – ATLAS and CMS.5 The various proto-collaborations had
already developed idiosyncratic technological paths. That is, although the functional requirements for
each particle detector were the same, each group had opted for different technological solutions that
were manifest in the form of different architectures. Consequently, the independent groups were
forced to think about ways that their design concepts could be merged into a new architecture.
Besides seeking to integrate the technological approaches, it was also important for the
institutions to be organizationally aligned. Two of the collaborations, Experiment for Accurate
Gamma, Lepton and Energy measurement (EAGLE) and Apparatus with Superconducting Toroids
4 This parallel development of upgrades and future generations of experiments is typical of HEP experiments because development and construction of a new detector requires 10 – 15 years of work. While ATLAS was being developed, some groups within the collaboration were already working on upgrades for 2015 and beyond. 5 According to the scientists we interviewed, they always have checks and balances by conducting at least two experiments. There are two other smaller experiments as well besides ATLAS and CMS.
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(ASCOT), seemed to be the most similar; both had opted for a complex configuration consisting of
two magnets. Consequently, the two groups decided to merge, and formed ATLAS.
The emergence of controversies
EAGLE and ASCOT included four key components: an inner tracker, a calorimeter system, a
muon spectrometer and a magnet system (see Figure 1 and Table 2). The two collaborations had
placed different emphases on the different components. The core feature of the EAGLE concept was
an elaborate calorimeter (a hybrid calorimeter consisting of two independent subsystems) combined
with a powerful inner tracker. By contrast, the ASCOT architecture was dominated by a
superconducting magnet system required for its powerful muon spectrometer.
--- Figure 1 and Table 2 here ---
A reason for these differences between EAGLE and ASCOT is the fundamental uncertainty
that underlies high energy physics. For each of the four components of the detector, several different
technologies were considered as potential candidates for the emerging design. Indeed, options had to
be developed before a confirmation could be sought as to whether or not a particular approach would
meet the requirements of a challenging environment. With such irreducible uncertainty, preferences
and prior experiences of the EAGLE and ASCOT groups played an important role in the choices that
they had made. Each group focused on the components with which they were most familiar and had
most experience. Because ASCOT’s strength was in muon detection, its design was constrained by the
characteristics of a muon system designed around a very large superconducting magnet system.
EAGLE, on the other hand, was spearheaded by a group with a strong background in calorimetry.
Smaller groups, which had strong interests in inner tracker systems using semiconductor technologies,
complemented the EAGLE community.
Scientists of both EAGLE and ASCOT clearly were closely attached to their respective
proposal. Therefore, members of the ATLAS collaboration agreed upon a convention that competing
options “…can and should be analyzed in a scientific (and not emotional) way.”6 The objective was to
ensure that controversies, if any, would largely be of a technical nature. Beyond performance issues,
competing technologies would be evaluated in terms of cost, construction time and technical risks, as
6 “Emotional way” refers to political controversies between competing groups at that time.
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well as on the basis of the impact that choices would have on other subsystems. Working groups
identified areas of consensus and tried to find common solutions. A series of ‘concept optimization
meetings’ were held between members of different groups to discuss the strengths and weaknesses of
each approach. Based on these insights, representatives of EAGLE and ASCOT started to negotiate
ways that their technologies and personnel could potentially be integrated into a single experiment.
Divergent opinions emerged when decisions were to be made for and against specific
technologies. A major concern was that a vote against a particular technology could alienate some
members and that ATLAS could thereby potentially lose necessary critical knowledge, manpower and
funding as a result. Consequently, a process was embraced that could accommodate negotiations
between the two groups.
Going beyond the controversies generated by differences in technological perspectives, the
actual composition of each of the two groups also began to play a role. ASCOT was dominated by two
large French and German research institutes. EAGLE, by contrast, was a larger community, but
consisted of small to medium sized groups. Whereas big national laboratories have a tendency to work
on large systems, such as muon spectrometry, small institutes often focus on areas that do not require
large infrastructural investments, such as chip design for the inner tracker (please see Table 3 for an
overview of the countries with research interests per subsystem). These smaller institutes with a strong
stake in the EAGLE inner detector were afraid that the large institutes could force adoption of
ASCOT’s superconducting toroid into the collaboration, an eventuality that would result in the
domination of the design by larger components.
--- Table 3 here ---
It became apparent during the course of negotiations that there were two fundamentally
different sets of assumptions at play. Both EAGLE and ASCOT had proposed a large toroid magnet to
create an independent measuring capability for muons7 and other highly energetic particles. The
EAGLE group wanted to increase the reliability of the experiment with this additional measurement
capability, which would become a significant advantage once the collaboration made new discoveries.
7 These muon particles were considered to be very important for the experiment because theories predict that they are related to the Higgs mechanism that physicists need to discover in order to explain physics beyond the Standard Model.
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For example, when the detector identifies a new particle, the measurements taken by the muon
spectrometer can be compared with observations from more central detectors that are located closer to
the collision, such as the inner detector. The ASCOT group, on the other hand, feared a failure of the
inner detector because of the unprecedented energy that would be released – 700% higher than in
previous experiments. Components close to the collisions, such as the inner detector, are especially
subject to aging and radiation damage. For the ASCOT group, a separate muon spectrometer would
provide the redundancy required to overcome any damage that might occur to the inner detector.
The two groups had different perceptions of this risk based on their assumptions. EAGLE
expected to operate at low to moderate luminosity levels during the first phase of the experiment
because it usually takes several years for accelerators to reach their full potential. Therefore, EAGLE
emphasized a balanced detector concept featuring an elaborate inner tracker for optimal particle
detection at low luminosity levels. The inner detector would sustain this first phase and could be
upgraded at a later stage if necessary. ASCOT, on the other hand, expected early operation of the
accelerator at high luminosity levels. In its scenario, which was driven by expected competition from
the Superconducting Super Collider planned in the United States,8 the risk of damage to the inner
detector was much higher than that anticipated by EAGLE. ASCOT, therefore, optimized the overall
detector layout for the muon spectrometer while the inner tracker was a relatively simple device,
because the inner tracker was expected to fail at high luminosity levels in any case.
In short, the different socio-cognitive bases of the two groups created a collaborative
challenge. Specifically, individuals from EAGLE and ASCOT were driven by different sets of beliefs,
artifacts and evaluation routines. Although a convergence of ideas and practices within each
collaboration facilitated exchange of information and ideas, it was difficult to generate an
understanding across the boundaries of the collaboration because each group was locked into its own
ways of thinking.
Unfolding of Architecture
In the Letter of Intent signed in October 1992, the 88 institutions already involved in the
collaboration explicitly agreed on a shared schema that included provisional specifications of the key
8 The Superconducting Super Collider was a particle accelerator which was planned to be built in Texas. During the design and first construction phase, Congress cancelled the project in 1993 by due to rising cost estimates.
15
properties and functionalities of the various ATLAS components and the ways that these would
interact with one another. Although the overall detector concept outlined the basic design
consideration, the choice of the specific technologies for the different components was left open. The
R&D projects conducted by participating institutes since the late 1980s resulted in various
technologies that potentially could be used for parts of detectors. Development of multiple
technological options was considered to be important during the early phases as it was unclear which
of the new technologies would be capable of operating under the harsh radiation conditions of the
LHC.
The Letter of Intent listed several competing technological options for each subsystem. In
most cases, a preferred technology was selected as a “baseline design” with alternative options that
would be chosen if the baseline turned out to be untenable. However, in some cases, several R&D
projects were continued even when it was clear that the baseline technology was the most appropriate
one to pursue. Such continuation of some of the R&D projects allowed technological decisions to be
postponed in the hope of retaining members who favored options that had not been chosen. The
ATLAS community hoped that, by continuing such R&D projects and testing prototypes, the
superiority of a particular approach over others would become apparent to all participants and would
encourage the proponents of paths not chosen to nevertheless remain engaged with ATLAS (cf. Knorr-
Cetina, 1995).
Another reason to defer decision-making was to gain the time required to set up review panels
that could evaluate the various technologies. The review panels did not have any mandate to select a
particular technology; rather, they were set up to investigate the potential of the competing
technologies and to make recommendations to the collaboration board, which consisted of all ATLAS
members. The collaboration nominated senior scientists, highly respected by those in the HEP
community, to serve on these panels. The aim of the review panels was to reduce the role of politics
by allowing obvious decisions to emerge. As a physicist described, the review panel operated in ways
similar to a tribunal:
The panelists who are chosen by the management are the judges, and you have two parts against each other. In our case, for the hadronic part [of the calorimeter], we were against the liquid argon people, and we were looking for problems of their approach and they were looking for problems with our approach. The whole thing was relatively formal. We would
16
present our results and our calculations, and they would present their results and their calculations. And then we would ask them nasty questions in writing, and they would ask us nasty questions in writing. And then, at the next meeting, there would be the answers to these questions. The processes that unfolded in these review panels challenged both the proponents and the
opposition of a given technology. Many assumptions that had been taken for granted by the
proponents of a certain technology were now challenged by the members of the review panel or by
scientists who proposed competing approaches. Each group had to justify their assumptions – through
analytical reasoning, evidence from simulation studies and tests of prototypes, or support from
external experts. Although the scientists worked hard to justify their technologies, even more
demanding was the effort to identify potential shortcomings of competing technologies and to ask
probing questions, as this effort required a deep understanding of the concepts proposed by the
competing groups.
To some extent, the competing technologies could be exchanged with little impact on the
overall architecture. Some solutions, however, required an adaptation of the architecture, thereby
critically shaping the developmental path of the overall detector. Therefore, mastery of the question
and answer procedure in the review process required knowledge not only of the components that the
groups were creating, but also the interdependencies with other systems and the reasons that such
interdependencies were critical. For example, during the review for the calorimeter, it was essential
that the groups understood the implications of the proposed specifications for neighboring systems,
such as the inner detector. As an ATLAS scientist explained:
(The) liquid argon calorimeter has a lot of advantages and so on, but it is a very expensive technology. It has a lot of channels and so on and so forth. This is kind of forcing you to a small radius, and therefore has certain implications on the inner detector. The liquid argon calorimeter group prepared to defend against this possible critique and
worked on solutions for this conflict between the two interdependent subsystems. Specifically, the
solenoid magnet, a part required for the inner detector to identify charged particles, was integrated into
the cryostat of the calorimeter. In this way, material and space constraints for the inner detector were
mitigated, and the proponents of the liquid argon calorimeter could justify the viability of their
proposal.
17
The ATLAS scientists had come from different backgrounds and, therefore, had different
knowledge bases and experiences with these technologies. As a result, they also had varying
judgments as to which technological option would be most appropriate for a particular component of
ATLAS. Specifically, the scientists tended to have great confidence in their technologies because they
had worked with them for a long time. From their experiences, these scientists could anticipate
potential problems and knew the options that could offer a potential fix. These scientists were
therefore convinced that their own proposal was preferable in terms of feasibility and reliability and
risk and cost because of this familiarity. However, when confronted with alternative perspectives, they
were prompted to scrutinize their own proposals and rethink some of the assumptions they had earlier
taken for granted.
The confrontation process was facilitated by the eagerness of competing groups to justify the
superiority of their own proposals and was mediated by very experienced panel members who often
had a strong background in related ATLAS components. From this review process, a collective
knowledge structure began to emerge that provided scientists of one system with an understanding of
ways that related components, and ATLAS as a whole, worked. We label this partially overlapping
knowledge structure that emerged as ‘interlaced knowledge’, a knowledge structure that has both
individual and collective properties.
The knowledge that emerged from the review panels benefited not only the immediate
participants but also others involved in the collaboration as a whole. Part of the motivation behind the
panel sessions was to generate a consensus. Although a few private panel meetings took place, for the
most part, a group of scientists from each detector would be present, and some of the meetings were
completely public. In any case, the collaboration was marked by constant discourse and
communication, which were comprised of talk threads, emails, meeting presentations and transparency
exchanges. As Knorr-Cetina (1995) describes, HEP experiments were “mapped into a fine grid of
discourse spaces created by intersections between participants.” This narration and account of the
groups’ activities and experiences with equipment, data sets, physics calculations and the like rendered
the emergent interlaced knowledge both collective and dispersed.
18
The creation of interlaced knowledge throughout the collaboration, combined with the deferral
of decision-making to the dispersed yet collective knowledge structure, was characteristic of the
selection process of relevant options that regulated work at ATLAS. Rather than deliberate decision
making driving the emergence of the ATLAS architecture, it was left to emerge. Routinely, the
outcomes of review panels and other discourses pointed the system towards particular directions that
built upon the challenges and events that had already transpired, such as the problems that were
encountered in real time as well as future possibilities that were yet unknown. Through the constant
unraveling of the features of technical components, the proponents of competing technologies tried to
create an understanding throughout the collaboration as to the reasons that their design was the
solution for the overall detector in terms of performance, cost and risk. Decisions at ATLAS were left
to emerge as the obvious, reasonable or unavoidable options. As a senior scientist involved in the
muon spectrometer expressed, “When decision-making was an item on the agenda, this often meant
that something which was already agreed upon and clear for everyone in the collaboration was made
plausible and formally approved.”
This process, which deferred decision making and was based on interlaced knowledge,
minimized the dysfunctional facets of politics in the decision making process. Consequently, the
collaboration did not lose members, even those whose proposals had been turned down. If their
opponents had made a convincing argument, the scientists were usually willing to give in and even to
suggest that the better design should be implemented.
Changes in the Architecture as the Design Emerged
The properties of many of the technologies used for ATLAS components could only be
estimated due to the lack of sufficient prior experience. The performance of these technologies and
their impact on other parts of ATLAS could be determined only by educated guesses and complex
simulations. As a consequence, to determine an overall architecture that would remain stable during
the development of the overall experiment was extremely difficult. The design, therefore, was left
incomplete; many specifications remained preliminary on purpose (Garud, Jain, & Tuertscher, 2008) .
A specification of ATLAS that generated a considerable amount of uncertainty concerned the
size of the superconducting air core toroid and the related muon spectrometer. Originally designed to
19
consist of 12 coils and an inner radius of 5 meters, the costs and risks of designing and deploying this
gigantic magnet system turned out to be much greater than had been anticipated. While scientists were
already working on the designs of other ATLAS components based on the original specifications, the
ATLAS toroid was scaled down to have 8 coils with an inner radius of only 4.3 meters, a change in
specifications that triggered controversies over other components.
For instance, the downscaling of the magnet system benefited the muon spectrometer because
a smaller radius meant that the muon spectrometer had to cover a smaller area and, thus, required
fewer expensive muon chambers. The calorimeter could adapt to this change by also reducing its inner
radius, while maintaining the thickness required to effectively measure the energy of the particles.
However, the situation was different for the inner detector because surrounding components had
already squeezed its design. This further reduction in size meant that the space envisaged for the inner
detector electronics would no longer be available. Therefore, these components had to be housed
elsewhere, a step that required other components to sacrifice space in order to host the inner detector
electronics. As one person recounted:
What I negotiated with the muons was a gap at the end of the barrel calorimeter, so the services9 came out and went straight out, or 50 percent of them did, between the inner layer and the second layer of the muon chambers where there is more space to put a panel. And that has had an impact on the muons. They had to have a gap. We also have to cool the inner detector services in that region so that it does not warm up the muon electronics and the muon chambers themselves, which is quite critical. Moreover, cables to the inner detector electronics added additional materials which, in turn,
generated heat from their millions of readouts. Both of these were negative side effects for the liquid
argon calorimeter. To change the location of the electronics was not a trivial task; cables would have
to be routed next to power supplies and through strong magnetic fields. To protect the electronic
cables from picking up noise, effective shielding was required, which, in turn, required additional
space and material.
Eventually, the need for more space inside the inner detector triggered additional architectural
changes. For example, the gap between the barrel and the end-cap calorimeter was widened on two
occasions to allow for additional space for shielded cables and cooling. Although services such as
9 In ATLAS jargon, services are the pipes and cables for the various detector systems, such as power supplies, cooling lines, cryogenics and read-out cables.
20
cooling and cables posed less of a problem for peripheral components (as they could be routed outside
the detector), services for the inner detector began to invade the space of both the calorimeter and
muon spectrometer. However, it was not too difficult for the inner detector group to justify their need
for extra space for cables and cooling as the increased need for services was partly due to constraints
imposed by the outside detectors.
Besides space limitations, the goal to minimize materials led to controversy between members
working on the inner detector and those working on surrounding components. For example, whereas
the inner detector engineers preferred additional material for cooling and shielding, the calorimeter
group preferred less material in front of the calorimeter because the amount of material used in the
inner detector would determine particle reactions before they could enter the calorimeter, thereby
biasing measurements.
The calorimeter group, therefore, decided to lobby for an inner detector design with fewer
components. Specifically, there was discussion that the inner detector should have been built without a
transition radiation tracker (TRT). However, the inner detector scientists could demonstrate in
complex simulations that the TRT was critical for achieving the physics performance specified by
ATLAS and could convince members of the review panel that the amount of material was justified.
Consequently, it was decided to adapt the design of the calorimeter to account for the increased
amount of material. The design of the liquid argon calorimeter was changed to introduce an additional
measurement layer for the detection of electron and photon showers caused by material located in
front of the calorimeter.
The interlaced knowledge that was created and emerged through such justification processes
became more important as the architecture continued to change. Indeed, interlaced knowledge enabled
adaptive coordination when problems occurred that could not be solved locally by members of a
module but instead required changes across components. Interlaced knowledge enabled scientists of
the different components to interrelate carefully and with consideration and to anticipate interference
with other parts of ATLAS.
For example, it was a review of the cooling system that identified potential risks and
technological problems inherent to the inner detector. The cooling system was based on binary ice, a
21
coolant consisting of ice crystals in a cooling liquid, which was pumped through a complex system of
pipes. Scientists of other components, such as the liquid argon calorimeter, who tried to avoid large
amounts of binary ice, pointed to problems associated with water-based cooling, such as water
leakages that could destroy parts of the detector. Although this risk was highest for the inner detector,
it was not recognized as a threat by the inner detector team. Like all other ATLAS components, the
inner detector was designed by scientists and engineers who possessed local knowledge and
incentives. Of greater concern to these engineers working on the inner detector was the problem of
extricating heat from the densely packed inner detector. It is for this reason that they had focused on
the superior performance of binary ice cooling.
Interestingly, groups other than the inner detector designers perceived the risk of water
leakage more readily. The better choice from the perspective of those working on the inner detector
was considered to be an inferior choice from the perspective of those working on the calorimeter.
Scientists and engineers working on other components were less focused on the cooling performance
of binary ice. Instead, they were concerned about the amount of material that was introduced by binary
ice cooling. This concern – and a difference in perspective – enabled this group to draw attention to
the risks involved in using binary ice, and prompted the group to propose an evaporative cooling
system instead. The resolution of this controversy resulted in a design that not only used less material
but also minimized the risk of water leaks in the inner detector.
The complex task of designing the inner detector, given difficult space and material
constraints, resulted in further changes in the ATLAS architecture. The pressure to use more efficient
electronics forced the inner detector group to change the design of the pixel system and adopt a new
type of semiconductor. Controversy arose over conflicting schedules due to this change; because this
technology was new, further testing and R&D work were required, thus resulting in a delay of the
pixel system of the inner detector. An inner detector scientist explained:
We thought having three systems, the pixels, the silicon strip detector and TRT, to have them all ready at the same time, it is going to be very difficult because the pixel changed…. Then we changed the system. We put the silicon strip detector together with the TRT and then also put in the end-cap. We then put in the pixel system in the end. This means that the schedule of the pixel system was decoupled from the schedule of the two other systems.
22
As this example illustrates, conflicting schedules resulted in the decoupling of elements of the
inner detector that were to be integrated into other components of ATLAS. To implement such a
change in the architecture of ATLAS, agreed-upon interfaces had to be renegotiated at a very late
stage of development. A change at this stage was only possible with the support of the other groups
who recognized that a delay of the inner detector development would create problems. Such an
awareness of the status of the various components was possible due to the reports and justifications
that had been presented in the numerous review panels, working groups and plenary meetings.
These negotiations occurred not only during early phases of ATLAS, but were ongoing across
the collaboration throughout development and construction phases as well. A fresh round of
negotiations was triggered when the collaboration encountered situations where earlier specifications
were found to be unfeasible. Even basic dimensions such as radii, lengths and allowances of materials
in each subsystem had to be adapted over time.
These observations suggest that coordination, rather than being generated by an architecture
that embeds pre-specified interfaces as proposed by the modularity literature, can nevertheless be
accomplished through a process of negotiations. Indeed, the need for managerial intervention is not
embedded in a clearly specified, stable modular architecture. Rather, self-coordination of the
collaboration is enabled by interlaced knowledge that allows for mutual adjustments of the
interdependent actors and groups involved in the ATLAS collaboration.
DISCUSSION
The longitudinal analysis of ATLAS suggests that during the development of complex
technological systems, architectures are neither clearly understood by participants nor are they stable.
For instance, in the case of ATLAS, although a very rudimentary architecture of the experiment
existed at the very beginning of the experiment, this structure was far from being understood by all
participants. Instead, this architecture experienced significant changes over time. Almost on a daily
basis, geometrical and functional boundaries of interdependent components were challenged, resulting
in a renegotiation of specifications that continued even during the construction phase.
Non-sequential Search for Design
23
Problem solving in the development of ATLAS did not progress sequentially from top level
problems to design problems at the lower levels of the architecture, an observation that is contrary to
predictions made by prior research (e.g., Clark, 1985; Murmann & Frenken, 2006; Tushman &
Murmann, 1998). Rather, early design tasks focused on medium and low level problems that were
solved in a decentralized manner, whereas integration and top level problem solving often became an
issue only later in the process. A bibliometric analysis of ATLAS publication data clearly visualizes
this pattern (please see Figure 2). The result of this analysis indicates when and where groups formed
and how they interacted. The locus of activity is seen at the periphery in the early design phase (blue
lines) and gradually shifted towards the center as the design of various components crystallized (green
lines). Most of the activity in the center, however, is represented by yellow and red lines, indicating
that activities regarding integration occurred mostly in the later phases of ATLAS development.
--- Figure 2 here ---
As a consequence, the design of ATLAS emerged as a non-sequential search process in which
many choices were only preliminary. This decentralized approach, and its many iterations, gave rise to
technological controversy over the basic architecture, controversy among technologies in competition
for a subsystem, and controversy within a subsystem and across subsystems as unforeseen problems
required changes in the specified design. In sum, the coordination of the dispersed development and
construction work of the more than 150 institutions could not be provided by simply pre-specifying
system boundaries and interfaces.
Given the absence of a central organizational structure, the coordination of the decentralized
activities of 2,000 scientists and engineers to create a functional design required a different solution. A
striking facet of the ATLAS case, in this regard, was the presence of ongoing negotiations and the
creation of compromises and consensus. In ATLAS, political issues were harnessed to generate
collaboration. The architecture of the experiment to be built was not defined only by some scientists
and engineers (the actors in this case) ‘winning out’ or taking control, but through a process of
confrontation and justification of the positions held by the various scientists and engineers, including
physicists who had a big stake and interest in these matters. By the public summation of the
24
knowledge that emerged, the collaboration was able to overcome political strategies by pursuing a
strategy that allowed the obvious decisions to emerge.
Creation of interlaced knowledge
In particular, a process of justification was the hallmark of the negotiations associated with the
review process. Specifically, during negotiations, it was essential for proponents of a particular
technology to explain the reasons that their choice was the superior solution (see also Galison (1987)
for how demonstration plays an important role as to how experiments end). Figure 3 indicates that not
only were such justifications important during the initial specification of the architecture, but also
when controversies arose as the architecture emerged. If a group wanted to change a technological
path, it had to mobilize the support of other groups throughout the collaboration. In order to convince
the collaboration that the new proposal would result in a better outcome, it was essential to present
reasonable evidence to justify the group’s claims.
--- Figure 3 here ---
Because of the openness of the ATLAS collaboration and the involvement of individuals from
multiple groups, justifications were scrutinized and were always available for inspection. In this
interactive process, many different points of view and component-specific perspectives were
articulated. These observations are in line with current research on epistemology, which argues that
justification is a key process for creating organizational knowledge (Boltanski & Thévenot, 2006;
Garud, 1997; Nonaka, 1994). Justification essentially determines whether claims of individual groups
are rejected by others in the organization, or believed to be valid and incorporated into their
knowledge bases (von Krogh & Grand, 2000).
While negotiations can be seen as reaching a compromise, this process also contributes to the
building of consensus at the knowledge level. At ATLAS, such ongoing negotiations resulted in a
reconfiguration and recontextualization of available knowledge. By the time differences had been
resolved, competing groups had developed a shared understanding of each other’s components and the
roles that these components play within the overall technological architecture. As the various groups
created such overlap across their local knowledge bases, they developed interlaced knowledge across
interdependent components.
25
By choosing the term interlaced knowledge, we differentiate this concept from others, such as
common knowledge (Grant, 1996). We would like to emphasize that overlaps between and among the
various knowledge bases do not imply a common knowledge base shared by all members in the
collaboration. On the contrary, interlaced knowledge was created at various levels, reflecting a fine
“grid of discourse” (Knorr-Cetina, 1999) within the ATLAS collaboration. The content of the
knowledge and the degree to which it was shared varied throughout the collaboration, depending on
the controversies within local working groups, review panels and plenary meetings that involved the
collaboration at large. The three panels in Figure 4, for example, visualize the interlaced knowledge
structure of the ATLAS muon spectrometer community for the early design phase (1994), the
advanced stage of detailed development (1998) and the late stage of construction and installation of
the detector components (2006). Figure 5 suggests a similar temporal pattern for the interlaced
knowledge structure in all major ATLAS subsystems.
--- Figure 4, Figure 5 ---
Interlaced knowledge at ATLAS comprised various levels of detail. At the overall
collaboration level, interlaced knowledge included basic knowledge about the progress and status of
detector components. This knowledge gave individuals an appropriate representation of current issues,
the challenges facing related components, and pockets where controversy was likely to emerge. Such
discourse took place in plenary meetings, which played an important role as an attention-driving
mechanism. Regularly scheduled updates created an internal rhythm and an internal time pacing in the
development process (Brown & Eisenhardt, 1997). At this level, interlaced knowledge helped groups
of interdependent systems synchronize and schedule their work and keep track of changes in the
technological system.
The discourse that unfolded within the working groups and the review panels resulted in more
detailed knowledge. Differences usually involved justification across boundaries, for example, during
negotiations of interface specifications between two interdependent components. The interlaced
knowledge that emerged at this level offered the different groups a deeper understanding of each
other’s context and requirements. This understanding, in turn, enabled the developers of the
interdependent components to be mindful of each other’s positions and interrelate with one another
26
when unforeseen changes occurred. Differences over the materials budget could anticipate the
difficulties of the inner detector to build a TRT within the material constraints. The calorimeter
group’s decision to introduce an additional layer of detectors enabled the inner detector to develop a
working TRT, which exceeded the amount of material originally specified.
Interlaced knowledge that emerged from such controversies was articulated and shared in a
variety of documents, such as meeting minutes, technical reviews, and design reports. These
documents were presented on many occasions and circulated via electronic mailing lists. Overall
interaction was polymorphic, with every scientist or engineer enjoying free access to all the
information generated within ATLAS; thus, the knowledge percolated throughout the ATLAS
collaboration at large.
Coordination through interlaced knowledge
The modularity literature emphasizes the importance of black-boxing and information hiding
(Parnas, 1972). In contrast, the findings of this study suggest the importance of interlaced knowledge
that emerged from the resolution of controversies that helped the coordination of the development and
construction of ATLAS. Such interlaced knowledge provided redundancy through overlapping
knowledge, thus enabling the collaboration to employ a “shared division of labor” (Nonaka &
Takeuchi, 1995). This type of redundancy is not associated with inefficiency, which is the usual
meaning associated with this term. Rather, such redundancy allows an accommodation of irreducible
uncertainty associated with the emergence of complex technological systems and allows a system to
adapt to new contingencies.
Whereas the rigid information structure embedded in a modular architecture is likely to lock a
system into a pre-specified development path, interlaced knowledge enables collaborators to
renegotiate specifications and to shape the transformation of paths in real time. In this sense, interlaced
knowledge is generative in nature. That is, it enables developers to respond to emerging problems by
creating novel solutions rather than merely adhering to pre-determined specifications. We observed
that groups in ATLAS were able to coordinate their actions effectively even in the presence of
uncertainty when the architecture itself was not stable and when specifications were ambiguous. As
unforeseen events occurred, such as the delay of the ATLAS pixel detector, interlaced knowledge
27
enabled the participants to find a workaround in collaboration with interdependent groups. Some
solutions even involved the renegotiation of previously specified interfaces, as was the case with the
integration of the pixel detector into the end-cap, thus resulting in a change in the architecture.
Modular architecture as a boundary infrastructure
Similar to research on modularity (Baldwin & Clark, 2000; Sanchez & Mahoney, 1996; Ulrich
& Eppinger, 1995), we too found that the structures that facilitated coordination became embedded
into the ATLAS architecture. At the same time, the ATLAS case reveals a nuanced understanding of
the relationship between agency and structure. Specifically, we saw a process of adaptive structuration
(one where the rules built into structures and agency co-emerge) unfold (DeSanctis & Poole, 1994).
As we have explained earlier, it is important to preserve the rationale as to why particular
specifications were chosen in order for such interlaced knowledge to provide necessary coordination.
Agreed-upon specifications were merely the tip of the iceberg of interlaced knowledge that emerged
from ongoing processes of negotiation and ordering. While mere specifications – a reduced form of
knowledge – may be sufficient to coordinate a stable system, the origins of this knowledge as well as
important interdependencies are often forgotten or overlooked. Consequently, pre-specified interfaces
are not sufficient to coordinate the development of an emergent architecture; they may even result in
dysfunctional actions among the groups.
A preliminary specification of the architecture nevertheless plays an important role,
specifically that of a boundary infrastructure that connects heterogeneous components (Bowker &
Stars, 1999) rather than a role that predetermines the development of interrelated components. As a
boundary infrastructure, a modular architecture can be interpreted from different perspectives, yet
many points of connections enable the different groups to structure their conversations when
negotiating the design (Star & Griesemer, 1989). Different groups can use the architecture as a “means
of representing, learning about, and transforming knowledge to resolve the consequences that exist at
a given boundary” (Carlile, 2002: 442).
The predominant view on modularity underestimates the architecture’s role as serving as the
boundary infrastructures by assuming that specifications of components and interfaces are clearly
28
articulated and understood.10 Indeed, recent research suggests that justifications across boundaries
decrease as standards become taken for granted (Green, 2004). When this happens, a system may
begin to lose some of its emergent properties. In this regard, research on high reliability organizations
suggests that justification processes are required on an ongoing basis in order to create ongoing rich
representations of the overall system so that mindful interrelationships can unfold when organizations
confront novel situations (Weick & Roberts, 1993; Weick & Sutcliffe, 2001).
Similarly, studies on organizational learning have found that, under conditions of uncertainty,
organizations create more knowledge about the complex interdependencies when people from
different perspectives engage in sense-making processes to generate representations of ways that the
overall system works (March, Sproull, & Tamuz, 1991). An openness to a variety of possibly
interpretations is often more valuable than a predefined model, however clearly the model might be
defined ex ante (March, 1987).
Of course, interlaced knowledge may be a luxury if such flexibility is not required. From an
information processing perspective, coordination is more efficient if people can rely on taken-for-
granted specifications. This is the perspective that modularity research offers: a pre-specified
architecture that has evolved historically or by convention, allowing for distributed information
processing to occur (Baldwin & Clark, 2003). The architecture provides embedded coordination by
splitting up complex tasks and then integrating them into an overall solution. This perspective seems
appropriate if a mature architecture already exists. However, other mechanisms come into play when
uncertainty is involved during the emergence of architectures.
To the extent that specifications are perceived as boundary architectures that can be
interpreted from different perspectives, architectures do provide adaptive coordination in dynamic
contexts. The interlaced knowledge that is created through ongoing negotiations across boundaries
provides a deeper understanding of other perspectives including the requirements for other
components. Groups can anticipate latent interdependencies and mindfully interrelate with one another
as they encounter novel events; this enables dispersed groups to coordinate their actions, even as the
architectures and specifications are still emerging.
10 A notable exception is recent work by Brusoni, Prencipe and Pavitt (2001) that challenges mainstream scholars of modularity by suggesting that systems integrators may need to know more than they do.
29
CONCLUSION
We have explored the ATLAS case to sketch out the processes that are involved in the
emergence of technological architectures. Prior negotiations and the codification of specifications into
a modular architecture can result in a situation where complex interdependencies are hidden behind a
small number of pre-specified interfaces. Such a process supports a division of cognitive labor among
the different component developers. However, whereas designers in established technological systems
can take for granted a common definition of interfaces, actors in emergent systems such as ATLAS
cannot build on standards and conventions that have been institutionalized. For emergent
technological systems, an architecture needs to be created in the first place.
The ATLAS case illustrates that there is ambiguity around specifications surrounding the
emergence of architectures and that these specifications are interpreted differently by different groups
that are involved. Of particular interest is the way in which controversies that result from conflicting
interpretations are resolved as the different technological components and groups confront one
another. Our analysis suggests that justifications across boundaries create interlaced knowledge – a
structure of local knowledge bases that overlap. Such interlaced knowledge provides a collective yet
distributed understanding and appreciation of the requirements posed by advocates of other
components, thereby allowing multiple groups to anticipate latent interdependencies and to mindfully
interrelate with one another. As a consequence, distributed groups are able to coordinate their
activities effectively, even as the architecture and specifications emerge.
30
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34
Table 1: R&D projects with ATLAS involvement
ATLAS Subsystem R&D Project Comments on Progress of R&D
Inner detector • Vertexing and
innermost tracking • Outer tracking and
electron identif.
RD19 Si pixel detectors RD20 Si micro strip detectors RD8 GaAs detectors RD2 Si strip and pad detectors RD6 TRD straw detectors RD7 scintillating fibers
All part of baseline design; R&D was needed to integrate concepts All part of baseline design; R&D was needed to integrate concepts Alternative option; R&D was needed to confirm feasibility of concept
EM calorimeter and preshower detector
RD3 liquid argon accordion P44 liquid argon TGT RD1 scintillating fibers
Baseline for barrel, baseline end-cap; R&D was needed to optimize design Alternative for barrel, baseline end-cap; R&D needed to demonstrate feasibility Alternative; only limited R&D was required
Hadronic calorimeter RD1 scintillating fibers RD3 liquid argon accordion P44 liqud argon TGT Scintillating tiles pre-prototype
All considered baseline options; R&D required for decision before Technical Proposal
Forward calorimeter Liquid scintillator and high pressure gas pre-prototypes
Both baseline options, R&D required for decision before Technical Proposal
Muon system • Tracking detectors
• Trigger detectors • General aspects
RD5 honeycomb strip chambers High pressure drift tubes Jet cell drift chambers RD5 resistive plate chambers RD5 punch through, em showers, etc.
All considered baseline options; R&D required for decision before Technical Proposal
Trigger • Level 1
• Level 2 • Level 3
RD5 muon triggers RD27 calorimeter triggers, system aspects RD2 and RD6 electron track triggers RD11 EAST general architectures RD13 general architectures
Front end electronics RD12 general read-out systems RD16 FERMI digital calorimeter FE RD29 DMILL radiation hard electronics
Detector-specific FE electronics; R&D was included in the corresponding R&D projects
DAQ system RD13 general DAQ and readout RD23 optoelectronic signal transfer
35
Table 2: Description of Major ATLAS subsystems
Subsystems Description
Inner detector • Pixel detector • Semi-conductor
tracker (SCT) • Transition radiation
tracker (TRT)
• The ATLAS inner detector combines high-resolution detectors at the inner radii with continuous tracking elements at the outer radii, all contained in the central solenoid magnet. The outer radius of the inner detector is 1.15 m, and the total length is 7 m.
• The pixel detector provides a high precision set of three measurements as close to the interaction point as possible, and mostly determines the impact parameter resolution and the ability of the inner detector to find short-lived particles such as B-Hadrons.
• The SCT system is designed to provide a set of eight precision measurements per track in the intermediate radial range, contributing to the measurement of momentum, impact parameter and vertex position
• At larger radii, typically 36 tracking points are provided by the TRT. The Transition radiation Tracker (TRT) is based on the use of straw detectors, which can operate at the expected high rates due to their small diameter and the isolation of the sense wires within individual gas volumes. Electron identification capability is added by employing Xenon gas to detect transition radiation photons created in a radiator between the straws.
Calorimeter system • Liquid argon
calorimeter • Tile calorimeter
• The calorimeter measures the energy of charged and neutral particles. It consists of metal plates (absorbers) and sensing elements. Interactions in the absorbers transform the incident energy into a "shower" of particles that are detected by the sensing elements.
• In the inner sections of the calorimeter, the liquid argon calorimeter, the sensing element is liquid argon. The showers in the argon liberate electrons that are collected and recorded.
• In the outer sections, the sensors are tiles of scintillating plastic, i.e., the tile calorimeter. The showers cause the plastic to emit light that is detected and recorded.
Muon spectrometer • Precision chambers • Trigger chambers
• Muons are particles, like electrons, but 200 times heavier. They are the only detectable particles that can traverse all the calorimeter absorbers without being stopped. The muon spectrometer surrounds the calorimeter and measures muon paths to determine their momentum with high precision.
• In precision chambers, gas-filled metal tubes with wires running down their axes are used as sensors. High voltage between the wire and the tube wall allows detection of the traversing muons by the electrical pulses they produce. With careful timing of the pulses, muon positions can be measured to an accuracy of 0.1 mm. The reconstructed muon path determines its momentum and sign of charge.
• Trigger chambers are based on a similar principle; however, high time resolution rather than precision is the key feature of trigger chambers. Using thin plates or multiple wires as sensors, trigger chambers have a time resolution better than 25 ns.
Magnet system • Toroid magnet • Solenoid magnet
• The ATLAS toroid magnet system consists of eight barrel coils housed in separate cryostats and eight coils housed in each of two end-cap cryostats. The end-cap coil systems are rotated by 22.5° with respect to the barrel toroids in order to provide radial overlap and to optimize the bending power in the interface regions of both coil systems.
• The central ATLAS solenoid has a length of 5.3 m with a bore of 2.4 m. The conductor is a composite that consists of a flat superconducting cable located in the center of an aluminum stabilizer with a rectangular cross-section. The solenoid is designed to provide a field of 2 T with a peak magnetic field of 2.6 T. The total assembly weight is 5.7 tons.
36
Table 3: Institutions Participating in Subsystems, by Country of origin
Inner detector Liquid argon calorimeter
Tile calorimeter Muon spectrometer
Armenia 1
Australia 2
Belarus 2
Brazil 1
Canada 9
China 1 1
Czech Republic 3 2
Denmark 1
France 1 6 1 1
Georgia 1
Germany 6 4 2
Greece 1
Italy 3 1 1
Japan 5 7
Morocco 1
Netherlands 1 2
Norway 2
Poland 2
Portugal 1
Romania 1
Russia 6 3
Slovenia 1
Spain 1
Sweden 2 1 1
Switzerland 1 1
Taipei 1 1
Turkey 1
United Kingdom 11
USA 17 6 5 12
CERN 1 1 1 1
68 32 19 29
37
Figure 1: Overview of the Atlas Detector
38
Figure 2: ATLAS Co-Authorship Network over Time
1990 2006
This figure indicates when and where groups formed and how they interacted. The locus of activity is seen at the periphery in the early design phase (blue lines) and gradually shifted towards the center as the design of various components crystallized (green lines). Most of the activity in the center, however, is represented by yellow and red lines, indicating that activities regarding integration occurred mostly in the later phases of ATLAS development.
39
Figure 3: Justification in Three Subsystems
This figure plots the justification factor for the 3 major subsystem groups of the ATLAS detector over time. The justification factor was obtained as a result from the latent semantic analysis and indicates to what extent the subsystem groups engaged in justification. Figure 3 clearly indicates that the level of justification increased during the early design phase and reached the highest level during the detailed development phase between 1996 and 1998. The level of justification decreased as the designs of the various components materialized the subsystem groups started to construct components in the late 1990s.
0
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40
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41
Figure 5: Closeness Centrality of Interlaced Knowledge in Three Sub-systems
This figure plots the closeness centrality of the three subsystem communities’ knowledge structures over time. Closeness centrality is a measure of how densely interlaced a community’s knowledge structure is. The green line for the muon spectrometer, for example, indicates how the knowledge structures shown in Figure 4.a-c became more interlaced first and decayed during the construction and installation phase.
0
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1990 1993 1996 1999 2002 2005 2008
Closeness of Interlaced Knowledge
Calorimeter
Muon
Inner Detector