Organizational analysis of Open Data Aarhus

Urban planning over the last century has evolved from the idealism of a classical political utopia, to modern planning of “new towns,” to postmodern decentralization. Since the industrial revolution, urban centers have grown into sprawling metropolises as waves of people relocate from the countryside. As they grow and change, innumerable factors contribute to their growing complexity, from which emerges macroscopic phenomena like traffic jams. The difficulty in understanding this complex system in flux has been mollified since the advent of precise and ubiquitous information technology (IT), which can constantly monitor certain factors and record it as digital data. Analyzing this real-time, or near-real-time, data can allow city governments to make decisions more quickly and accurately, making the city more self-reflexive and, to use the more colloquial term, “smart.”

Since 2012, Denmark’s second-largest city, Aarhus, has partnered with public and private figures in the area as the organization “Smart Aarhus” to foster sustainable urban innovation and growth. To better ground that initiative in factual data, Smart Aarhus has established a working group called Open Data Aarhus (ODAA) to gather and host the city’s metrics publicly, using that to seek collaboration on new innovative services and data analyses.

From a postmodern perspective of urban planning, what is ODAA’s role in Aarhus’ organizational robustness and responsiveness? By reframing a city as an emergent phenomenon or process spanning more dimensions than just bricks and mortar, there must be a sense-making entity between the chaos of urban life and the body that governs it. ODAA is that sense-making entity, whose functions and organization this paper will delineate symbolically from the rest of the brain-like organization of a smart city government.

Theoretical background

The term “smart city” is often politicized or used loosely to fit technologically driven urban planning goals. For example, the European Commission’s “Smart City” is an approach to framing cities’ existing issues with techno-centric, often futuristic, criteria to address issues like globalization, energy usage, and sustainability (Vanolo, 2014). Being smart, in a more linguistic sense, refers to an entity’s faculties of thought, understanding, and responsiveness. Similarly, this paper uses the term according to Smart Aarhus secretariat member Martin Brynskov’s paper “Prototyping a Smart City,” which describes a smart city as a movement. Smart Aarhus formed outside the government, organically arising from the ideas of university academics, private businesspeople, and normal city residents. Their movement became a formal organization in 2012 and formed working groups to focus on specific needs and challenges. ODAA’s domain is the integration of data and IT systems across the city, including its government, citizens, and private shareholders. ODAA is a component of Aarhus’ smart city movement which acts like the city’s objective observer, trying to understand itself through sensory data collected constantly from networked devices throughout the city.

By applying organization theory of the last century, the concepts of modernity and postmodernity will be important. The modern perspective of an organization is of a closed system that functions efficiently with a preference for top-down control (Morgan, 2006). That is, an organization’s leaders make hierarchically more important and effective decisions than subordinates. In city planning, the modern city is organized as an industrialized system, which can be mastered in its totality by the planners (Harvey, 1989). This arose from Ford-inspired capitalism, where massive processes could be designed and managed to efficiently generate the desired output. Such a perspective has been applied as “garden cities,” “new towns,” or “planned communities” over the last century (Goodchild, 1990). However, just as the rise of IT has allowed more flexible, decentralized control over factory processes (i.e. postmodern capitalism), so could a postmodern perspective of organization theory be considered for cities.

For example, say a city faces an issue that affects a wide swath of the city, including many services, zones, and, of course, residents. Ebenezer Howard’s classicly idealistic “Garden Cities of To-morrow” would think they already have these issues figured out in the chapter “Some Difficulties Considered.” A modern garden city, or “new town,” inspired by Ford’s efficiency and a world war’s necessity would have all the social awareness and perspective of a lab of aerospace engineers as they force a rigorous scientific approach (Goodchild, 1990). Cities that take a postmodern approach, as many do currently, may have a government that is decentralized, enabling discourse and localized decision-making based on insight to their respective domains. Goodchild makes a strong argument for other ways that postmodern organization allows more flexibility and opportunity to adapt to challenges of contemporary cities.

However, since postmodernism seems to be as liberally defined as a “smart city” (Goodchild, 1990), it would be simpler—or at least less misleading and controversial—to evaluate ODAA from the perspective of metaphors with respect to certain postmodern concepts. Take for example a brain: a group of interconnected tissues specializing in exchanging and modifying electrical pulses. As brains have evolved from a simple nervous system, some groups of tissues have developed specialized roles, such as storage and communication. Eventually, a brain like a human’s can become so complex that phenomena like pattern recognition and imagination emerge, which can be difficult to model mechanically from the level of individual neurons. Instead, cognitive science can frame these phenomena as a neural network. Constructions such as the self emerge from apparent chaos of neurons firing based on external stimuli and internal states. Similarly, Aarhus’ government is a decentralized network of citizens, who comprise departments with specialized roles. The city could thus be considered more of an emergent concept than a physically definable place. It has a collective sentience, almost brain-like, which gain more consciousness with smart city organization. Faculties of perception, at least, could come from ODAA as it identifies, gathers, and analyzes live data. However, like our brain, a city and its components change significantly over time yet maintain their function and identity (Friedenberg & Silverman, 2011).

To cope with this flux, ODAA can be analyzed by four “logics of change.” First, I examine why the working group was organized: to observe data trends, themselves reflexive and self-producing closed systems, like electrical signals between neurons. Next I examine how the organization’s personnel make sense of the chaos of this data and how they recognize emergent patterns based on competing attractors and feedback loops. Finally, ODAA’s actions, or those taken by other departments based on its analyses, can cause reactions in the data it studies, resulting in ODAA itself changing and evolving based on that tension (Morgan, 2006).

Research method

Many cities have adopted a “smart city” mentality, earning thorough academic examination, as this paper references. Aarhus will likely be no exception, though being only two years old at the time of this writing, it has been examined in only a few European publications. Nevertheless, its working groups like ODAA have been reaching out from the city via events like hackathons, where people meet and quickly develop concepts in code, design, and analysis. Michelle Bak-Mikkelsen, project manager and one of three people working full-time for ODAA, attended one recently in Copenhagen. There she presented ODAA and earned several hackers’ attention, including mine, over the next few hours to develop concepts like traffic and air quality data visualizations and a commute planner based on pollution data. Mikkelsen invited me to continue my analysis with this paper as an external researcher.

One of ODAA’s primary goals is maintaining their online data platform, which hosts raw data, projects based on the data, and a discussion forum. Thanks to this wealth of information, as well as that provided by Smart Aarhus, I was able to collect enough general information to target my investigation and perform preliminary analysis on the overall organization. I also gained some insight by joining and observing a hackathon in Aarhus during the Internet Week Denmark festival, a prime opportunity to understand the internet culture, mostly among professionals. Following this, I contacted Mikkelsen again via Skype for a semi-structured interview to better understand ODAA from her perspective. She made an important point here that each member of the Smart Aarhus secretariat can have a very different perspective of its focus.

Analysis

Smart Aarhus’ website and documentation lend credence to Mikkelsen’s account of how the organization was originally formed as a citizen “coalition of the willing.” This social awareness fits with Goodchild’s assessment of a postmodern city as pluralistic and an expression of social diversity. Smart Aarhus’ use of working groups like ODAA also demonstrate the decentralized administrative approach and piecemeal decision-making as postmodern distinctions (Goodchild, 1990). If Smart Aarhus fully integrates into the city government while preserving these distinctions, then Aarhus could be said to be a postmodern city. Goodchild and Irving have substantiated the notion that postmodern city planning sheds the modernistic tendencies of government to pursue a metanarrative or achieve an overall unity to resolve its issues. Instead, it could fragment itself to pursue smaller, local narratives as they arise, embracing the “eddies and swirls of chaotic change” (Irving, 1993). However, extreme fragmentation and emphasis on pluralism would precipitate a total dissolution of government. Yet postmodernism’s embrace of otherness, which reinforces its notions of pluralism and social diversity, also contributes to citizens’ governmentality that subsumes the collective knowledge and perhaps even consciousness into a stable government (Vanolo, 2014). Extremity is therefore tempered by the collective, which begs the question of some metanarrative despite postmodern aversion. Though it may not be defined top-down from modernistic scientific management, it could arise bottom-up from the constituents.

This Foucauldian metanarrative would direct the governmental organization between and among more localized entities. Smart Aarhus refers to it as the “Scandinavian third way.” This perspective takes advantage of postmodern capitalism’s foundation on a knowledge economy, rather than a Fordian factory economy, by deriving power bottom-up from its underlying network. In a company, that power would be the collective knowledge of its individual employees seeking goals rather than following orders. In a city like Aarhus, that power is derived from its stakeholders. Rather than wresting control of a city to fit a unitary Fordist vision, as modern planning prescribed (Goodchild, 1990), a postmodern perspective invites a city to capitalize on its constituent parts and resources in response to environmental flux. The Scandinavian third way, taking from Foucault, invites an ascending analysis of power. Individual actions and interactions—the fundamental mechanisms of power—are utilized, transformed, and extended by ascendingly more general mechanisms of political power (Foucault & Bouchard, 1980), eventually by organizations like ODAA and Aarhus Magistraten.

If a city of several hundred thousand is politically powered from infinitesimal human action, each having its own self-determined trajectory, then how could that give rise to a metanarrative that effectively designs a city? A similar situation exists in cognitive science and chaos theory, which both study emergent phenomena of self-organizing systems. A city knows what it wants, thus constructing a metanarrative of organization, via collective cognition from emergent phenomena of the swirling eddies of chaos on its lowest scales. For example, Aarhus has a huge number of cars, and on any particular day, there is no way to accurately model the totality of traffic flow in a city from a high-level perspective. Rather, data from a low-level perceptual direction could be extrapolated from to yield a rough high-level view. ODAA has done that by installing Bluetooth sensors on the roadside, picking up how often someone with a Bluetooth device passes it and hosting that data on ODAA’s public data platform (Bloksgaard). Applying some basic statistical modeling, certain trends may arise from the raw data. For example, by comparing car speed to business opening hours, it can be understood that certain roads are busier in a narrow time window as people drive to their jobs. Applying the general notion that traffic is undesirable and increases pollution rates, Aarhus’ transportation department may decide on days where this is particularly bad to take measures to spread the traffic across parallel roads and improve the flow.

This connection between bottom-up perception and top-down direction very closely mimics cognition in the human brain, organizing signals of both via neural synchrony (Friedenberg & Silverman, 2011). Relying too heavily on either decontextualized bottom-up or scientific modernism’s top-down city planning would lose that synchrony. For example, with a city’s innumerable individual interrelated events and problems, it would simply be impossible to efficiently govern based on only the anarchic chaos of bottom-up perception. Similarly, an entirely top-down perspective would discount the effects on its constituents and ignore perceptual data. Therefore, there must be some agency that works between and among a city’s faculties of perception and direction.

This is the reason for decentralized administrative units, such as magistrates, departments of transportation, and public relations offices; however, this alone does not go far enough to bridge the gap from citizen to city planning. ODAA is a smart city module that directly plugs into the city, collecting and generalizing raw city data via ubiquitous sensors and observers. It is akin to the human brainstem, which directs the raw sensory data from nerves throughout the body to other parts of the brain that can make sense of it. And like a part of the brain, it does not keep all its work to itself. A connectionist model of cognition describes the paths and nodes activated around the brain as an action is perceived, conceptualized, and directed (Friedenberg & Silverman, 2011). ODAA takes advantage of this distributed cognition in a smart city context by engaging with civic hackers who use their programming skills to parse the city’s data, contextualize it within their own knowledge and perspective, and share their findings. Not only is the city both perceiving and directing more, but it is also more self-aware, sentient, and reflexive overall. A smarter city has more myelinated connections between its gray matter, so to speak, allowing it to function faster and more in-sync (Fields, 2008). By adopting a smart city mentality, it can continue to evolve like a brain.

In order to evolve, it’s important to understand how the city and ODAA may preserve its identity in flux. A human brain maintains its identity and functions through massive changes in its synaptic connections, size, orientation, and structure (Fields, 2008), so some logics of change must be understood to delineate how ODAA may be organized from such radical flux. First, to maintain its organizational identity, it must distinguish itself from other organizations and the context it studies. Despite being a closed subsystem of Smart Aarhus, its autopoietic nature allows it to reproduce itself in its own likeness. Like a ribosome, ODAA was created in the nucleolus of Smart Aarhus’ strategic goals, joining programming and media experts when information is found and catalyzing the synthesis of raw information into functional components for a smarter city. Animal cells can have many ribosomes working on the same data (i.e. DNA). Similarly, ODAA’s engagement with hackathons and aiding individual civic hackers with its open data platform allows many similar spin-off organizations to work on the city’s data.

As that data and how it is used changes, ODAA as well as other elements of a smarter Aarhus must adapt itself in the image of that reality. In fact, as those other elements evolve, they may want to adapt some aspects of ODAA. For example, why would the department of transportation wait on ODAA to synthesize and collect traffic data when they run the roads? It is only a working group, meaning it was created to accomplish specific, immediate goals, so it may not last long enough to see Smart Aarhus through its entire lifetime. If ODAA accomplishes its primary goals—developing an ideal technical platform for hosting its data and establishing an optimal network with the community—it will likely need to reevaluate its role. At that point, perhaps it will turn to the organizations within its network: government departments, public institutions, and private companies. By working more closely with them, ODAA could leverage their individual strengths to better integrate data collection devices or use their own personnel to analyze data in more contexts.

These organizations may over time find a special need for data or release a large amount of its own data to be cleaned and analyzed. ODAA may shift its focus from one attractor to the other depending on what most demands its perception. Similarly, as city-wide events like festivals or disasters unfold, ODAA’s daily focus may shift to that event in order to understand the situation as it unfolds as quickly as possible. With more external influence on ODAA’s domain and more work being published publicly, ODAA even might start to see its own efforts reflected in its data in a feedback loop. As ODAA publishes live traffic data, and people on the road monitor it in real time, they may all decide to take the next best route, which then becomes the worst route as everyone else joins.

As trends naturally arise from chaos, so may the trends affect the chaos, such as the traffic situation previously described, creating a dialectic of change. ODAA’s organization may be integrated into other departments, tightening this feedback loop as it can collect and publish finer-grain data more quickly than ever before. As ODAA evolves while Aarhus integrates more smart city planning methods and modules, its own identity may be lost as it blends into the fabric of the smart city itself. Perhaps this may also yield new data, as it compares its data to something else, such as other cities’ data. Perhaps a Smart Denmark organization will form, prompting each city to set up a working group to synthesize their data in relation to other cities. And thus  ODAA would arise again as a working group of this external organization, yet maintaining its exact same functionality and identity in this different context. But is it the same thing? Would that ODAA, as a working group of Smart Denmark , be interchangeable with or transformationally equivalent to its predecessor in Smart Aarhus? The same could be asked of anyone whose brain evolved since they were an infant and still retained their personal identity.

Conclusion

ODAA’s organizational flux over time preserves its identity in new contexts, finding new ways to network within the city’s own brain-like organization. Its ability to perceive improves as its higher faculties of cognition find new ways of interacting with its environment. According to a recent report by the Open Government Partnership, Smart Aarhus’ initiatives would benefit from more verifiable milestones and indicators of progress (Eberholst, 2014). This should not be hard in a more advanced smart city, as the city itself becomes more quantifiable and verifiable through data collection and analysis. As a smart city evolves, its ability to perceive improves its responsiveness, and its ability to direct from this data improves its robustness.

As certain parts of a city can be thoroughly monitored, perhaps changes to it could conceivably be simulated in a computational model. A new avenue of research would be to port a smart city to a simulated world and model its organization via artificially intelligent (AI) agents (Friedenberg & Silverman, 2011). By subsuming the organization, rules, and structure of a real city under an agent-based AI and feeding it ODAA’s actual live data, could new aspects of the city come to light? Perhaps it is akin to an evil genius submerging a brain in a vat, connecting it to a computer, and fooling it into thinking it’s actually in a body walking outside in the sunlight. Would it have experienced the same flux and evolved in the same way as the real city? Would the state of the simulated city’s organization be necessarily truthful so that it could be applied to the real city?

 

Appendix

Logical equivalences used in different contexts:

Brain context	City context	Aarhus context
Electrical signals	Events	Traffic speed data
Neuron	Personnel	Michelle Bak Mikkelsen
Brain region	Department	ODAA*
Brain / Neural network	Government	Aarhus Magistraten
Whole organism	City	Aarhus

* At this time, ODAA is only a potential, not an official, component of Aarhus Magistraten.

 

References

About Smart Aarhus. [Online]. Available from: http://www.smartaarhus.eu/about-smart-aarhus/. [Accessed: 5 September 2014].

Bloksgaard, M. (n.d.). Realtids trafikdata. [Online]. Aarhus, Denmark: Aarhus Municipality, Traffic and Roads. Available from: http://odaa.dk/dataset/realtids-trafikdata.

Eberholst, M.K. (2014). Independent Reporting Mechanism Denmark: Progress Report 2012–13 : Open Government Partnership. p.p. 12.

Fields, R.D. (2008). White matter in learning, cognition and psychiatric disorders. Trends in Neurosciences. 31 (7). p.pp. 363–364.

Foucault, M., & Bouchard, D. F. (Eds.). (1980). Language, counter-memory, practice: Selected essays and interviews. Cornell University Press. p.p. 99.

Friedenberg, J. & Silverman, G. (2011). Cognitive science: an introduction to the study of mind. Sage. p.p. 100, 202, 210, 353–357.

Goodchild, B. (1990). Planning and the modern/postmodern debate. Town Planning Review. 61 (2). p.pp. 120–126, 128, 131.

Harvey, D. (1989). The condition of postmodernity: an enquiry into the origins of cultural change. Basil Blackwell.  p.p. 44.

Howard, E. (1902). Garden Cities of To-morrow / Ebenezer Howard. Garden Cities of To-morrow. Sonnenschein & Co., Ltd.

Irving, A. (1993). The Modern/Postmodern Divide and Urban Planning. University of Toronto Quarterly. 62 (4). p.p. 482.

Korsgaard, H. & Brynskov, M. (2013). Prototyping a Smart City. In: [Online]. 2013, Munich, Germany: Centre for Participatory IT. Available from: http://pure.au.dk/portal/files/70459732/DC8_6_Korsgaard_Brynskov.pdf.

Morgan, G. (2006). Images of Organization. SAGE Publications. p.pp. 22, 241–290.
Vanolo, A. (2014). Smartmentality: The Smart City as Disciplinary Strategy. Urban Studies. 51. p.pp. 885, 894.