scholarly journals Multidisciplinary Research as a Complex System

2021 ◽  
Vol 20 ◽  
pp. 160940692110384
Author(s):  
Amaris Dalton ◽  
Karin Wolff ◽  
Bernard Bekker

Collaborative research has become increasingly prominent since the mid-20th century. This article aspires to offer a fundamental ontology of a multidisciplinary research system. As a point of departure, we consider disciplinarity as a restricted language code as noted by Bernstein. The impetus for collaboration is found in a research problem’s transcendence of disciplinary bounds. This article makes several propositions that diverge from the consensus position regarding the formation and dynamics of a multidisciplinary system. Most notably that such a system adheres to the constituent elements of what could be regarded as a complex system, including an ensemble of elements, interactions between these elements, local disorder followed by the emergence of robust order and system memory. We propose that the internal communications and subsequent self-organization of such a system may be conceptualized as orientation signals, or ‘stigmergy’, analogous to those observed in swarms. System robustness, we argue, is a function of the individual researcher’s local autonomy and is, paradoxically, augmented by the weakness of communications across disciplinary bounds, along with the lack of central organization and the emphasis on research novelty. System memory, we argue, manifests itself in the ability of a researcher to change her/his route of inquiry, based on environmental feedback, whereby new information becomes incorporated into the adjusted research methodology. We propose that an emergent intelligence, at the level of the system, expresses itself in the unconcealment of the ‘form’ of the metaproblem. The theoretical model is empirically illustrated using, as an example, the contemporary field of renewable energy research, which is an area primed for collaborative research. It is anticipated that an improved understanding of multidisciplinary research systems provides insights into certain strengths particular to less integrated and self-organized forms of collaborative research along with a framework with which to improve the design and fostering of such systems.

mBio ◽  
2010 ◽  
Vol 1 (5) ◽  
Author(s):  
Christine A. Biron ◽  
Arturo Casadevall

ABSTRACT The individual disciplines of microbiology and immunology are exploding with new information necessary for understanding host-pathogen relationships, infectious diseases, cancer, and autoimmunity. Because of overlapping scientific interests, immunologists and microbiologists often share common academic affiliations. The coexistence is uneasy. Significant problems arise because the groups have evolved different intellectual traditions. Pressures are intensified by sporadic changes in perceptions of their relative worth. As the mixing of microbiologists and immunologists can be likened to ground zero in the fight for interdisciplinary knowledge, it is useful, at this time of escalating data acquisition and growing appreciation for multidisciplinary research, to examine their histories, the challenges to amalgamation, and the advantages of their association for the advancement of knowledge and the delivery of protection against disease. The exploration supports a recommitment to integration of the disciplines and a proposal to facilitate this by inclusion of expertise bridging the areas.


Entropy ◽  
2018 ◽  
Vol 20 (7) ◽  
pp. 540 ◽  
Author(s):  
Subhashis Hazarika ◽  
Ayan Biswas ◽  
Soumya Dutta ◽  
Han-Wei Shen

Uncertainty of scalar values in an ensemble dataset is often represented by the collection of their corresponding isocontours. Various techniques such as contour-boxplot, contour variability plot, glyphs and probabilistic marching-cubes have been proposed to analyze and visualize ensemble isocontours. All these techniques assume that a scalar value of interest is already known to the user. Not much work has been done in guiding users to select the scalar values for such uncertainty analysis. Moreover, analyzing and visualizing a large collection of ensemble isocontours for a selected scalar value has its own challenges. Interpreting the visualizations of such large collections of isocontours is also a difficult task. In this work, we propose a new information-theoretic approach towards addressing these issues. Using specific information measures that estimate the predictability and surprise of specific scalar values, we evaluate the overall uncertainty associated with all the scalar values in an ensemble system. This helps the scientist to understand the effects of uncertainty on different data features. To understand in finer details the contribution of individual members towards the uncertainty of the ensemble isocontours of a selected scalar value, we propose a conditional entropy based algorithm to quantify the individual contributions. This can help simplify analysis and visualization for systems with more members by identifying the members contributing the most towards overall uncertainty. We demonstrate the efficacy of our method by applying it on real-world datasets from material sciences, weather forecasting and ocean simulation experiments.


2017 ◽  
Vol 16 (1) ◽  
Author(s):  
Paula Sofia Castro-Acevedo ◽  
Luz Esperanza Bohórquez Arévalo

The hierarchical structure has been dominant in the business context because of the ease with which it exercises control and reduces the risks of the limited rationality of the individual. However, the precariousness of these structures in the processing of information has been evidenced, and by extension the difficulty to adapt to the change. These difficulties can lead organizations to business failure and chain effects that arise from it, for these reasons it is necessary to find alternative structural ways to overcome these problems. In this research, a literature review is made of the way in which the organizational structure is related to the performance of organizations from different theoretical perspectives. Subsequently, the failures of hierarchical control structures are identified, as the dominant structural form in the current economic system in terms of how they process information, learn and make decisions, and then contrast the way in which these characteristics are presented in systems self-organized natural and artificial. Because of the review of literature in natural and artificial self-organized systems, it was found that they are highly robust in the way they process information, since they manage to transform information from the environment into knowledge to make agile, fast and quality decisions. From this, it is necessary to transfer these properties of the self-organized systems to the business organizations by means of the design of structures that encourage self-organization to increase their performance and avoid the failure and chain effects that this causes. The implications of an organization of this type and the lines of research that originate from this work are also discussed.La estructura jerárquica ha sido dominante en el contexto empresarial por la facilidad que tiene para ejercer control y disminuir los riesgos de la racionalidad limitada del individuo. Sin embargo, se ha evidenciado la precariedad de estas estructuras en el procesamiento de información, y por extensión la dificultad para adaptarse al cambio. Estas dificultades pueden llevar a las organizaciones al fracaso empresarial y a los efectos en cadena que se desprenden de éste, por estas razones es necesario encontrar formas estructurales alternativas que superen estos problemas. En esta investigación se hace una revisión de literatura de la forma en que la estructura organizacional está relacionada con el desempeño de las organizaciones desde diferentes perspectivas teóricas. Posteriormente se identifican las fallas que presentan las estructuras jerárquicas de control, como la forma estructural dominante en el sistema económico actual en cuanto a la forma como procesan información, aprenden y toman decisiones, para luego contrastar la forma en que se presentan estas características en sistemas auto-organizados naturales y artificiales. Como resultado de la revisión de literatura en sistemas autoorganizados naturales y artificiales, se encontró que son altamente robustos en la forma como procesan información, ya que logran transformar la información del entorno en conocimiento para tomar decisiones ágiles, rápidas y de calidad. A partir de esto, es necesario trasladar estas propiedades de los sistemas autoorganizados a las organizaciones empresariales por medio del diseño de estructuras que fomenten la autoorganización para incrementar su desempeño y evitar el fracaso y los efectos en cadena que este origina. Se discuten también las implicaciones de una organización de este tipo y las líneas de investigación que se originan de este trabajo.A estrutura hierárquica foi desenvolvida no contexto empresarial pela facilidade que tem para controle e diminuição dos riscos da racionalidade limitada do indivíduo. Sim embargo, se há evidenciado a precariedade de estruturas no processamento de informação, e por extensão a dificuldade para adaptar-se ao câmbio. Estas dificuldades podem levar a as organizações ao mercado financeiro e aos efeitos em cadeia, se você está desesperado, por estas razões, é necessário encontrar formas estruturais alternativas que superarem esses problemas. Esta pesquisa tem uma revisão da literatura da forma em que é a estrutura organizacional está relacionada com o desempenho das organizações de diferentes perspectivas teóricas. Posteriormente se identifica as faltas que apresentam as estruturas de controle, como a forma estrutural dominante no sistema econômico real em como a forma como processamento de informações, aprender e tomar decisões, para depois contrastar a forma em que se apresentar estas características em sistemas autoorganizados naturales y artificiales. Como resultado da revisão de literatura em sistemas auto naturais e artificiais, encontrou-se que é altamente robusto na forma como a informática, que deseja transformar a informação do entorno em conhecimento para tomar decisões ágiles, rápidas e de qualidade. A partir disto, é necessário transferir estas propriedades dos sistemas autoorganizados às organizações empresariais por meio de projeto de estruturas que fomentam a auto-organização para incrementar o desempenho e evitar o fracasso e os efeitos em cadeia que este origina. Se discutem também as implicações de uma organização deste tipo e as linhas de pesquisa que se originam deste trabalho.


2021 ◽  
Author(s):  
Matthew J. Hasenjager ◽  
William Hoppitt ◽  
Ellouise Leadbeater

AbstractHoneybees famously use waggle dances to communicate foraging locations to nestmates in the hive, thereby recruiting them to those sites. The decision to dance is governed by rules that, when operating collectively, are assumed to direct foragers to the most profitable locations with little input from potential recruits, who are presumed to respond similarly to any dance regardless of its information content. Yet variation in receiver responses can qualitatively alter collective outcomes. Here, we use network-based diffusion analysis to compare the collective influence of dance information during recruitment to feeders at different distances. We further assess how any such effects might be achieved at the individual level by dance-followers either persisting with known sites when novel targets are distant and/or seeking more accurate spatial information to guide long-distance searches. Contrary to predictions, we found no evidence that dance-followers’ responses depended on target distance. While dance information was always key to feeder discovery, its importance did not vary with feeder distance, and bees were in fact quicker to abandon previously rewarding sites for distant alternatives. These findings provide empirical support for the longstanding assumption that self-organized foraging by honeybee colonies relies heavily on signal performance rules with limited input from recipients.


2021 ◽  
Vol 33 (1) ◽  
pp. 47-70
Author(s):  
Santhoshkumar Srinivasan ◽  
Dhinesh Babu L. D.

Online social networks (OSNs) are used to connect people and propagate information around the globe. Along with information propagation, rumors also penetrate across the OSNs in a massive order. Controlling the rumor propagation is utmost important to reduce the damage it causes to society. Educating the individual participants of OSNs is one of the effective ways to control the rumor faster. To educate people in OSNs, this paper proposes a defensive rumor control approach that spreads anti-rumors by the inspiration from the immunization strategies of social insects. In this approach, a new information propagation model is defined to study the defensive nature of true information against rumors. Then, an anti-rumor propagation method with a set of influential spreaders is employed to defend against the rumor. The proposed approach is compared with the existing rumor containment approaches and the results indicate that the proposed approach works well in controlling the rumors.


2001 ◽  
Vol 34 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Elisabeth Engels

Referring to Foulkes's thesis on `ego training in action' this article draws particular attention to the cultural and historical impacts on this self-organized learning process of the individual in group analysis. First, the reflections of Norbert Elias on configurations in German culture are presented. In a second step the conceptualization of early infant upbringing will be analysed in a way that is decentred from the mother-child relationship towards the configurations of the surrounding society. Third, it is suggested that the German habitus is reflected in early infant upbringing in the 1930s, in the pattern of detachment. Finally, by focusing on the individual, there will be a brief discussion of how understanding and attachment can prevent the development from pain to violence: by ego training in action in culture and history.


2010 ◽  
Vol 21 (4-5) ◽  
pp. 421-440 ◽  
Author(s):  
J.-P. NADAL ◽  
M. B. GORDON ◽  
J. R. IGLESIAS ◽  
V. SEMESHENKO

We introduce a general framework for modelling the dynamics of the propensity to offend in a population of (possibly interacting) agents. We consider that each agent has an ‘honesty index’ which parameterizes his probability of abiding by the law. This probability also depends on a composite parameter associated to the attractiveness of the crime outcome and of the crime setting (the context which makes a crime more or less likely to occur, such as the presence or not of a guardian). Within this framework we explore some consequences of the working hypothesis that punishment has a deterrent effect, assuming that, after a criminal act, an agent's honesty index may increase if he is caught and decrease otherwise. We provide both analytical and numerical results. We show that in the space of parameters characterizing the probability of punishment, there are two ‘phases’: one corresponding to a population with a low crime rate and the other to a population with a large crime rate. We speculate on the possible existence of a self-organized state in which, due to the society reaction against crime activities, the population dynamics would be stabilized on the critical line, leading to a wide distribution of propensities to offend in the population. In view of empirical works on the causes of the recent evolution of crime rates in developed countries, we discuss how changes of socio-economic conditions may affect the model parameters, and hence the crime rate in the population. We suggest possible extensions of the model that will allow us to take into account more realistic features.


2018 ◽  
Vol 6 (1) ◽  
pp. 19-29 ◽  
Author(s):  
Jeffrey H. Altschul ◽  
Keith W. Kintigh ◽  
Terry H. Klein ◽  
William H. Doelle ◽  
Kelley A. Hays-Gilpin ◽  
...  

ABSTRACTWhile our fascination with understanding the past is sufficient to warrant an increased focus on synthesis, solutions to important problems facing modern society require understandings based on data that only archaeology can provide. Yet, even as we use public monies to collect ever-greater amounts of data, modes of research that can stimulate emergent understandings of human behavior have lagged behind. Consequently, a substantial amount of archaeological inference remains at the level of the individual project. We can more effectively leverage these data and advance our understandings of the past in ways that contribute to solutions to contemporary problems if we adapt the model pioneered by the National Center for Ecological Analysis and Synthesis to foster synthetic collaborative research in archaeology. We propose the creation of the Coalition for Archaeological Synthesis coordinated through a U.S.-based National Center for Archaeological Synthesis. The coalition will be composed of established public and private organizations that provide essential scholarly, cultural heritage, computational, educational, and public engagement infrastructure. The center would seek and administer funding to support collaborative analysis and synthesis projects executed through coalition partners. This innovative structure will enable the discipline to address key challenges facing society through evidentially based, collaborative synthetic research.


2018 ◽  
Vol 40 (11) ◽  
pp. 1613-1629 ◽  
Author(s):  
Philippe Accard

Self-organizing systems are social systems which are immanently and constantly recreated by agents. In a self-organizing system, agents make changes while preserving stability. If they do not preserve stability, they push the system toward chaos and cannot recreate it. How changes preserve stability is thus a fundamental issue. In current works, changes preserve stability because agents’ ability to make changes is limited by interaction rules and power. However, how agents diffuse the changes throughout the system while preserving its stability has not been addressed in these works. We have addressed this issue by borrowing from a complex system theory neglected thus far in organization theories: self-organized criticality theory. We suggest that self-organizing systems are in critical states: agents have equivalent ability to make changes, and none are able to foresee or control how their changes diffuse throughout the system. Changes, then, diffuse unpredictably – they may diffuse to small or large parts of the system or not at all, and it is this unpredictable diffusion that preserves stability in the system over time. We call our theoretical framework self-organiz ing criticality theory. It presents a new treatment of change and stability and improves the understanding of self-organizing.


Author(s):  
Sydney Hopkins

Children’s conceptual development has been described as a process of“theory change.” Specifically, children begin with an idea and then iteratively update that idea by combining existing and new information, making and testing predictions and then revising their idea based on new data again. Similar processes have been postulated to account for adaptive phenomenon in perceptual psychology and motor control. The similarities between the two processes suggest that performance on tasks that measure conceptual and sensory‐motor “theory change”respectively may be related. The goal of the present study is to determine whether children’s development in a complex conceptual domain, theory of mind, is associated with children’s performance in a load force adaptation paradigm. Theory of mind is broadly defined as the ability to understand how mental states, such as beliefs and desires, motivate ourown and other people’s actions. In contrast, load force adaptation is the ability to gradually adjust the amount of force exerted on an object in order to smoothly lift it up, as experience with the weight of the object is gained. To explore the mechanisms underlying these two processes, children between the ages of 3.5 and 4.5 years participate in a load force adaptation task and a battery of theory of mind tasks. We predict that since the underlying processes appear to be theoretically similar, the individual differences in the ability to adapt load force and in theory of mind ability will be positively correlated.   


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