This document introduces fractal social organizations, a novel class of socio-technical complex systems characterized by a distributed, hierarchical architecture. Key concepts are defined through a case study of an elderly woman's smart home. The smart home detects if she has fallen and alerts her general practitioner. This simple example demonstrates how roles are organized into communities that work together to address situations. The document also presents a model of collective behaviors within static socio-technical systems. Despite its simplicity, the model's dynamics produce complex emergent properties like hierarchical organization and fractal patterns. These properties correspond to the intended architecture of fractal social organizations.
The social networks and the new social order between the individualized socia...INFOGAIN PUBLICATION
The new Social Networks (SN) evolved very quickly. They conquered of wide population as well in the cities as in the campaigns. They pushed aside values, attitudes, behavior…; In countries with strong social culture, they modified these values and modified the social rules formerly considered as unchanging.In this paper, an empirical study concerned the case of the Moroccans and their behavior with regard to the social networks in numerous domains as those of society, economy, consumption, social and societal relationships, information and communication, politics, etc. The traditional conventional social order is today in deep transformation. This paper contributes to the understanding of behavior change currently facing Moroccan society at all levels.The designers of software or applications bound to the social networks have to integrate these new behavior in their strategies.
The conventional use of technology at an administrative level constitutes much more than its usage as
an engineered object. Factual evidence of this was established through a study conducted at LSE, to
analyze how the ultimate outcome of technology in practice is largely determined by the interactions
that technology has with its users coming from different institutionalized environments. To do so, the
popular technical deterministic approach is extended, by adopting a socio-political lens aimed at
understanding “technology in practice”. The social constructivist and the structurational stance, put
together, highlight the delicate intricacies that take place during the recursive interaction between the
user and technology, which shapes technology into a socially politicized object.
Designing Systems that Support Social BehaviorThomas Erickson
By looking at how people interact in face to face situations we can gain insights on how to better design online systems to support social behavior. In particular, this presentation argues that simple visualizations of the presence and activities of participants in online situations can be a valuable design approach.
The social networks and the new social order between the individualized socia...INFOGAIN PUBLICATION
The new Social Networks (SN) evolved very quickly. They conquered of wide population as well in the cities as in the campaigns. They pushed aside values, attitudes, behavior…; In countries with strong social culture, they modified these values and modified the social rules formerly considered as unchanging.In this paper, an empirical study concerned the case of the Moroccans and their behavior with regard to the social networks in numerous domains as those of society, economy, consumption, social and societal relationships, information and communication, politics, etc. The traditional conventional social order is today in deep transformation. This paper contributes to the understanding of behavior change currently facing Moroccan society at all levels.The designers of software or applications bound to the social networks have to integrate these new behavior in their strategies.
The conventional use of technology at an administrative level constitutes much more than its usage as
an engineered object. Factual evidence of this was established through a study conducted at LSE, to
analyze how the ultimate outcome of technology in practice is largely determined by the interactions
that technology has with its users coming from different institutionalized environments. To do so, the
popular technical deterministic approach is extended, by adopting a socio-political lens aimed at
understanding “technology in practice”. The social constructivist and the structurational stance, put
together, highlight the delicate intricacies that take place during the recursive interaction between the
user and technology, which shapes technology into a socially politicized object.
Designing Systems that Support Social BehaviorThomas Erickson
By looking at how people interact in face to face situations we can gain insights on how to better design online systems to support social behavior. In particular, this presentation argues that simple visualizations of the presence and activities of participants in online situations can be a valuable design approach.
Open communities of innovation pioneers: the Musigen case studyGiuseppe Naccarato
We call innovation pioneers the experts in a scientific or technical domain in the early stages
of its development. Advances in information technologies allow networks of organizations
and individuals to exchange ideas and knowledge. Not differently from what has happened in
communities of consumers with the emergence of the so called prosumers, ICT can support
communities of innovation pioneers.
However, the role of IT in this domain has not been studied extensively in the management
literature. Understanding the dynamics of communities of innovation pioneers, instead, can
provide companies with precious knowledge on future breakthrough innovations.
This paper means to deepen our understanding of communities of innovation pioneers and the
role of IT in supporting them.
To achieve this goal, we investigate the case of Musigen, a new web platform with the
purpose to support knowledge sharing in the generative music field.
A Perspective on Graph Theory and Network ScienceMarko Rodriguez
The graph/network domain has been driven by the creativity of numerous individuals from disparate areas of the academic and the commercial sector. Examples of contributing academic disciplines include mathematics, physics, sociology, and computer science. Given the interdisciplinary nature of the domain, it is difficult for any single individual to objectively realize and speak about the space as a whole. Any presentation of the ideas is ultimately biased by the formal training and expertise of the individual. For this reason, I will simply present on the domain from my perspective---from my personal experiences. More specifically, from my perspective biased by cognitive and computer science.
This is an autobiographical lecture on my life (so far) with graphs/networks.
Icwsm10 S MateiVisible Effort: A Social Entropy Methodology for Managing Com...guest803e6d
A theoretically-grounded learning feedback tool suite, the Visible Effort (VE) Mediawiki extension, is proposed for optimizing online group learning activities by measuring the amount of equality and the emergence of social structure in groups that participate in Computer-Mediated Collaboration (CMC). Building on social entropy theory, drawn from Shannon’s Mathematical Theory of Communication, VE captures levels of CMC unevenness and group structure and visualizes them on wiki Web pages through background colors, charts, and tabular data. Visual information provides users entropic feedback on how balanced and equitable collaboration is within their online group are, while helping them to maintain it within optimal levels. Finally, we present the theoretical and practical implications of VE and the measures behind it, as well as illustrate VE’s capabilities by describing a quasi-experimental teaching activity (use scenario) in tandem with a detailed discussion of theoretical justification, methodological underpinning, and technological capabilities of the approach.
"Society 2.0: designing an action research into the next civilization" is an updated version of the talk I gave at the "2gether08" unconference in London, July 3, 2008. A downloadable version (complete with clickable links), its context and related conversation can be found in the Jump Time Players blog, http://www.evolutionarynexus.org/jtp_blog .
2009 - Connected Action - Marc Smith - Social Media Network AnalysisMarc Smith
Review of social media network analysis of Internet social spaces like twitter, flickr, email, message boards, etc. Network analysis and visualization of social media collections of connections.
Open communities of innovation pioneers: the Musigen case studyGiuseppe Naccarato
We call innovation pioneers the experts in a scientific or technical domain in the early stages
of its development. Advances in information technologies allow networks of organizations
and individuals to exchange ideas and knowledge. Not differently from what has happened in
communities of consumers with the emergence of the so called prosumers, ICT can support
communities of innovation pioneers.
However, the role of IT in this domain has not been studied extensively in the management
literature. Understanding the dynamics of communities of innovation pioneers, instead, can
provide companies with precious knowledge on future breakthrough innovations.
This paper means to deepen our understanding of communities of innovation pioneers and the
role of IT in supporting them.
To achieve this goal, we investigate the case of Musigen, a new web platform with the
purpose to support knowledge sharing in the generative music field.
A Perspective on Graph Theory and Network ScienceMarko Rodriguez
The graph/network domain has been driven by the creativity of numerous individuals from disparate areas of the academic and the commercial sector. Examples of contributing academic disciplines include mathematics, physics, sociology, and computer science. Given the interdisciplinary nature of the domain, it is difficult for any single individual to objectively realize and speak about the space as a whole. Any presentation of the ideas is ultimately biased by the formal training and expertise of the individual. For this reason, I will simply present on the domain from my perspective---from my personal experiences. More specifically, from my perspective biased by cognitive and computer science.
This is an autobiographical lecture on my life (so far) with graphs/networks.
Icwsm10 S MateiVisible Effort: A Social Entropy Methodology for Managing Com...guest803e6d
A theoretically-grounded learning feedback tool suite, the Visible Effort (VE) Mediawiki extension, is proposed for optimizing online group learning activities by measuring the amount of equality and the emergence of social structure in groups that participate in Computer-Mediated Collaboration (CMC). Building on social entropy theory, drawn from Shannon’s Mathematical Theory of Communication, VE captures levels of CMC unevenness and group structure and visualizes them on wiki Web pages through background colors, charts, and tabular data. Visual information provides users entropic feedback on how balanced and equitable collaboration is within their online group are, while helping them to maintain it within optimal levels. Finally, we present the theoretical and practical implications of VE and the measures behind it, as well as illustrate VE’s capabilities by describing a quasi-experimental teaching activity (use scenario) in tandem with a detailed discussion of theoretical justification, methodological underpinning, and technological capabilities of the approach.
"Society 2.0: designing an action research into the next civilization" is an updated version of the talk I gave at the "2gether08" unconference in London, July 3, 2008. A downloadable version (complete with clickable links), its context and related conversation can be found in the Jump Time Players blog, http://www.evolutionarynexus.org/jtp_blog .
2009 - Connected Action - Marc Smith - Social Media Network AnalysisMarc Smith
Review of social media network analysis of Internet social spaces like twitter, flickr, email, message boards, etc. Network analysis and visualization of social media collections of connections.
Masses, Crowds, Communities, Movements. Collective Formations in the Digital ...University of Stuttgart
From prosumers to swarms, crowds, e-movements and e-communities, the Internet allows for new forms of collective behavior and action anywhere on the spectrum between individ- uals and organizations. In all of these cases, online technologies function as connectivity- enhancing tools and have prompted the search for novel or inherently different collective formations and actors on the web.
However, research to date on these new collective formations on the web lacks a sociologi- cally informed and theoretical focus. Instead, loosely defined terms such as “swarm”, “crowd” or “network” are readily used as a catch-all for any formation that cannot be charac- terized as a stable corporate actor. Such terms contribute little to an understanding of the vast range of collective activities on the Internet, namely because the various collective for- mations differ significantly from each other with regard to their size, internal structure, inter- action, institutional dynamics, stability and strategic capability.
In order to bridge this gap, this study investigates two questions: One, how might the very dif- ferently structured collectives on the Internet be classified and distinguished along actor- or action-centered theory? And two, what influence do the technological infrastructures in which they operate have on their formation, structure and activities? For this we distinguish between two main types of collectives: non-organized collectives, which exhibit loosely-coupled col- lective behavior, and collective actors with a separate identity and strategic capability. Further, we examine the newness, or distinctive traits, of online-based collectives, which we identify as being the strong and hitherto non-existent interplay between the technological infrastruc- tures that these collectives are embedded in and the social processes of coordination and insti- tutionalization they must engage in in order to maintain their viability over time. Convention- al patterns of social dynamics in the development and stabilization of collective action are now systematically intertwined with technology-induced processes of structuration.
a modified weight balanced algorithm for influential users community detectio...INFOGAIN PUBLICATION
In the modern era online users are increasing day by day. Different users are using various social networks in different forms. The behavior and attitude of the users of social networking sites varies U2U (User to User). In online social networking users join many groups and communities as per interests and according to the groups’/Communities’ influential user. This paper consist of 7 sections , first section emphasis on introduction to the community evelotion and community. Second section signify movement between communities ,third section involve related work about the research.. Fourth section includes Problem Definition and fifth section involve Methodology (Proposed Algorithm Process ,Get Community Matrix, Community detetcion).Sixth section involve Implementation. Furthermore implementation include Datasets ,Quantitative performance, Graphical Results, Enhancement in the existing work..Last section include Conclusion and then references. In this paper,we are implementing and proposing the community detection in social media .In the proposed we have deployed a Longest Chain Subsequence metric for finding the number of connections to the kernel community.
11Systems TheoryBRUCE D. FRIEDMAN AND KAREN NEUMAN ALL.docxmoggdede
11
Systems Theory
BRUCE D. FRIEDMAN AND KAREN NEUMAN ALLEN
3
Biopsychosocial assessment and the develop-ment of appropriate intervention strategies for
a particular client require consideration of the indi-
vidual in relation to a larger social context. To
accomplish this, we use principles and concepts
derived from systems theory. Systems theory is a
way of elaborating increasingly complex systems
across a continuum that encompasses the person-in-
environment (Anderson, Carter, & Lowe, 1999).
Systems theory also enables us to understand the
components and dynamics of client systems in order
to interpret problems and develop balanced inter-
vention strategies, with the goal of enhancing the
“goodness of fit” between individuals and their
environments. Systems theory does not specify par-
ticular theoretical frameworks for understanding
problems, and it does not direct the social worker to
specific intervention strategies. Rather, it serves as
an organizing conceptual framework or metatheory
for understanding (Meyer, 1983).
As a profession, social work has struggled to
identify an organizing framework for practice that
captures the nature of what we do. Many have iden-
tified systems theory as that organizing framework
(Goldstein, 1990; Hearn, 1958; Meyer, 1976, 1983;
Siporin, 1980). However, because of the complex
nature of the clinical enterprise, others have chal-
lenged the suitability of systems theory as an orga-
nizing framework for clinical practice (Fook, Ryan,
& Hawkins, 1997; Wakefield, 1996a, 1996b).
The term system emerged from Émile Durkheim’s
early study of social systems (Robbins, Chatterjee,
& Canda, 2006), as well as from the work of
Talcott Parsons. However, within social work, sys-
tems thinking has been more heavily influenced by
the work of the biologist Ludwig von Bertalanffy
and later adaptations by the social psychologist Uri
Bronfenbrenner, who examined human biological
systems within an ecological environment. With
its roots in von Bertalanffy’s systems theory and
Bronfenbrenner’s ecological environment, the
ecosys tems perspective provides a framework that
permits users to draw on theories from different dis-
ciplines in order to analyze the complex nature of
human interactions within a social environment.
RELEVANT HISTORY
Ludwig von Bertalanffy (1901–1972), as mentioned
above, is credited with being the originator of the
form of systems theory used in social work. Von
Bertalanffy, a theoretical biologist born and educated
in Austria, became dis satisfied with the way linear,
cause-and-effect theories explained growth and
change in living organisms. He felt that change might
occur because of the interac tions between the parts
of an organism, a point of view that represented a
dramatic change from the theories of his day.
Existing theories had tended to be reductionis t,
understanding the whole by breaking it into its parts.
Von Bertalanffy’s introduction of systems theory
changed that framework by looki ...
Networking | Social Circle Memberships and Sales Performance ImplicationsProfessional Capital
How important is it to have a social membership? How important is it to have a professional network. Social Circle Memberships and Sales Performance Implications.
Evaluating Platforms for Community Sensemaking: Using the Case of the Kenyan ...COMRADES project
Vittorio Nespeca
TU Delft
V.Nespeca@tudelft.nl
Kenny Meesters
TU Delft
K.J.M.G.Meesters@tudelft.nl
Tina Comes
TU Delft
T.Comes@tudelft.nl
WiPe Paper – T12 - Designing for Resilience
Proceedings of the 15th ISCRAM Conference – Rochester, NY, USA May 2018
https://www.researchgate.net/publication/324162897_Evaluating_Platforms_for_Community_Sensemaking_Using_the_Case_of_the_Kenyan_Elections_Vittorio_Nespeca
Complexity theory and public management a ‘becoming’ field LynellBull52
Complexity theory and public management: a ‘becoming’ field
Since the special edition of Public Management Review on ‘Complexity Theory and Public Management’
in 2008 (Volume 10 (3)), co-edited by Geert Teisman and Erik-Hans Klijn, academic interest in complexity
theory, and how it might be used to understand the world and inform design and intervention in the
public policy/public management field, has grown and matured. The inspiration for this special issue
arose out of intensive interactions among interested scholars in conference panels (at American Society
for Public Administration, International Research Society for Public Management, and the Challenges of
Making Public Administration and Complexity Theory group) over the past few years and the realization
that a ‘stock-taking’ was required. While many public management scholars knew a little bit about
complexity – and some knew a lot – there was still no consensus about the contribution complexity
theory could or could not make to theory and practice. While we did not achieve consensus this time
around, the papers selected for this edition provide a picture of where we are and where scholars in this
field think we should go, and some examples of the most promising routes to get there. Before
summarizing these findings, we provide a brief overview of where we have come from and why we are
still a ‘becoming’ field.
Challenging fundamental assumptions
Nineteenth- and twentieth-century sciences which developed beneath the umbra of Newtonian
theories, embedded some pervasive assumptions which might be crudely summarized as (1)
relationships between individual components of any system can be understood by isolating the
interacting parts, (2) there is a predictability to the relationship among the parts, and (3) the result of
interactions and the working whole might eventually be understood by simply summing the parts. So in
much the same way as the expert clockmaker might be able to design, build, disassemble, and modify a
clock, understanding the individual parts and how they fit together leads to understanding the
functioning whole and the capability to replicate it precisely as required. This paradigm is dominated by
mechanical metaphors and leads to an assumption that the sum of the parts equals the whole.
Dissatisfaction with the limitations of mechanical explanations led to more sophisticated models which
were better at explaining the observed behaviour, initially of the physical world, and then increasingly
the biological, ecological, and social worlds (e.g. Byrne 1998; Cilliers 1998; Holland 1995; Kauffman
1993; Prigogine 1978; Prigogine and Stengers 1984; Stacey 1993; Waldrop 1992). Such modelling offered
new ontological insights about the nature of our world and the way it behaves. This is summed up
briefly by saying that there are recursive, ongoing non-linear interactions between the elements that
make up the whole a ...
Thinking social media: analyzing the systemic contexts from phenomenological ...Cândida Almeida
Thispaperpresentsaconceptualanalysisstudyofthesocialmediasin its interactive communication context. The proposal starts from the systemic context of these mediatic processes and the proposition of the analysis parameters reasoned by the peircean phenomenology. Thus the objective is presenting a way of the systemic and phenomenological study to understand the modes of informational exchanges occurrence and the complex relationships that establishes in the dynamic contexts of social media, based on the analysis of three parameters: emergence, circumstance, movement. These parameters are therefore understood as essential conditions to clarify languages, contexts and processes inherent to digital social networks in the internet. The proposal is understanding under the phenomenological point of view, how signs in this context can be presented, how they behave in their different systemic contexts - socio-cultural, technological, graphics - and how the mediatics evolutionary processes in social networks tends to occur.
OntoSOC: S ociocultural K nowledge O ntology IJwest
This paper
present
s
a
sociocultural knowledge ontology (OntoSOC) modeling appro
a
ch. Ont
o-
SOC modeling appro
a
ch is based on Engeström‟s
Human Activity Theory (HAT)
.
That Theory allowed us
to identify fundamental concepts and rel
a
tionshi
ps between them. The top
-
down precess has been used to
d
efine differents sub
-
concepts. The
modeled vocabulary permits us to organise data, to facilitate in
form
a-
tion retrieval
by introducing a semantic layer in social web platform architec
ture,
we project t
o impl
e
ment.
This platform can be considered as a «
collective me
mory
»
and Participative and Distributed Info
r
mation
System
(PDIS) which will allow Cameroonian communities to share an co
-
construct knowledge on perm
a-
nent organi
z
ed activ
i
ties.
In the Fifties, Arnold Schönberg introduced a model for music composition that he called "Grundgestalt", the basic shape. In this seminar I show how I interpreted this concept as a generative music model that translates the orbits of dynamic systems into musical components. I also describe a family of experiments that led me to the creation of simple and not-so-simple musical compositions, which I call "my little Grundgestalten”. Excerpts from a selection of those compositions will be presented.
On the Role of Perception and Apperception in Ubiquitous and Pervasive Enviro...Vincenzo De Florio
Building on top of classic work on the perception of natural systems this paper addresses the role played by such quality in
environments where change is the rule rather than the exception. As in natural systems, perception in software systems takes two major forms: sensory perception and awareness (also known as apperception). For each of these forms we introduce semi-formal models that allow us to discuss and characterize perception and apperception failures in software systems evolving in environments subjected to rapid and sudden changes—such as those typical of ubiquitous and pervasive computing. Our models also provide us with two partial orders to compare such software systems with one another as well as with reference environments. When those
environments evolve or change, or when the software themselves evolve after their environments, the above partial orders may be used to compute new environmental fits and different strategic fits and gain insight on the degree of resilience achieved through the current adaptation steps.
Service-oriented Communities: A Novel Organizational Architecture for Smarter...Vincenzo De Florio
The seminar I shall present at Masaryk University in Brno on May 19, 2016. A video of this presentation is available at https://www.youtube.com/edit?video_id=Fu5kv0sFWG4
On codes, machines, and environments: reflections and experiencesVincenzo De Florio
Code explicitly refers to a reference machine and, implicitly, to a set of conditions often called the system model and the fault model.
If one wants to guarantee an agreed-upon quality of service, one needs to either make assumptions about those conditions or adapt to them.
In this lecture I present this problem and a number of solutions, both practical and theoretical, that I have devised in the course of my career.
Although the main accent is on programming languages, here I provide links and references to other approaches that operate at algorithmic- and system-level.
Tapping Into the Wells of Social Energy: A Case Study Based on Falls Identifi...Vincenzo De Florio
Are purely technological solutions the best answer we can get to the shortcomings our organizations are often experiencing today? The results we gathered in this work lead us to giving a negative answer to such question. Science and technology are powerful boosters, though when they are applied to the “local, static organization of an obsolete yesterday” they fail to translate in the solutions we need to our problems. Our stance here is that those boosters should be applied to novel, distributed, and dynamic models able to allow us to escape from the local minima our societies are currently locked in. One such model is simulated in this paper to demonstrate how it may be possible to tap into the vast basins of social energy of our human societies to realize ubiquitous computing sociotechnical services for the identification and timely response to falls.
Accompanying paper available at https://arxiv.org/abs/1508.06655
How Resilient Are Our Societies?Analyses, Models, Preliminary ResultsVincenzo De Florio
Traditional social organizations such as those for the management of healthcare and civil defense are the result of designs and realizations that matched well with an operational
context considerably different from the one we are experiencing today: A simpler world, characterized by a greater amount of resources to match less users producing lower peaks of requests.
The new context reveals all the fragility of our societies: unmanageability is just around the corner unless we do not complement the “old recipes” with smarter forms of social organization.
Here we analyze this problem and propose a refinement to our fractal social organizations as a model for resilient cyber-physical societies. Evidence to our claims is provided by simulating our model in terms of multi-agent systems.
This course teaches engineering students how to program in C. I gave this course for several years in the framework of the "Advanced Technology Higher Education Network" / SOCRATES program.
A framework for trustworthiness assessment based on fidelity in cyber and phy...Vincenzo De Florio
We introduce a method for the assessment of trust for n-open systems based on a measurement of fidelity and present a prototypic implementation of a complaint architecture. We construct a MAPE loop which monitors the compliance between corresponding figures of interest in cyber- and physical domains; derive measures of the system’s trustworthiness; and use them to plan and execute actions aiming at guaranteeing system safety and resilience. We conclude with a view on our future work.
Presented at ANTIFRAGILE'15
Companion paper available at http://www.sciencedirect.com/science/article/pii/S1877050915008923
A behavioural model for the discussion of resilience, elasticity, and antifra...Vincenzo De Florio
Resilience is one of those "general systems attributes" that appear to play a central role in several disciplines - including ecology, business, psychology, industrial safety, microeconomics, computer networks, security, management science, cybernetics, control theory, crisis and disaster management. Resilience thus seems to be "needed" everywhere; and yet, even in the framework of a same discipline, it is not easy to define it precisely and consensually. To add to the confusion, other terms such as elasticity, change tolerance, and antifragility, although clearly related to resilience, cannot be easily differentiated.
In this talk I tackle this problem by introducing a behavioural model of resilience. I interpret resilience as the property emerging from the interaction of the behaviours produced by two "players": a system and a hosting environment. The outcome of said interaction depends on both intrinsic and extrinsic factors, including the systemic "traits" of the system but also how the system's endowment matches the requirements expressed by the behaviours of the environment. I show how the behavioural approach provides a unifying framework within which it is possible to express coherent definitions for elasticity, change tolerance, and antifragility.
A Behavioral Interpretation of Resilience and AntifragilityVincenzo De Florio
In this presentation I discuss resilience and antifragility as behaviors resulting from the coupling of a system and its environment(s). Depending on the interactions between these two "ends" and on the quality of the individual behaviors that they may exercise, different strategies may be chosen: elasticity (change masking); entelechism (change tolerance); and antifragility (adapting to & learning from change). When the environment is very simple and only capable of so-called "random behavior", often the only effective strategy towards resilience is off-line dimensioning of redundancy as a result of a worst-case assessment of disturbances and/or threats. Much more complex and variegated is the case when both systems and environments are "intelligent" -- or at least able to exercise complex teleological and extrapolatory behaviors. In this case both system and ambient may choose among a variety of strategies in what could be regarded as a complex evolutionary game theory setting.
Community Resilience: Challenges, Requirements, and Organizational ModelsVincenzo De Florio
An important challenge for human societies is that of mastering the complexity of Community Resilience, namely “the sustained ability of a community to utilize available resources to respond to, withstand, and recover from adverse situations”. The above concise definition puts the accent on an important requirement: a community’s ability to
make use in an intelligent way of the available resources, both institutional and spontaneous, in order to match the complex evolution of the “significant multi-hazard threats characterizing a crisis”. Failing to address such requirement exposes a community to extensive failures that are known to exacerbate the consequences of natural and human-induced crises. As a consequence, we experience today an urgent need to respond to the challenges of community resilience engineering. This problem, some reflections, and preliminary prototypical contributions constitute
the topics of this presentation.
A companion article is available at https://dl.dropboxusercontent.com/u/67040428/Articles/serene14.pdf
On the Behavioral Interpretation of System-Environment Fit and Auto-ResilienceVincenzo De Florio
Already 71 years ago Rosenblueth, Wiener, and Bigelow introduced the concept of the “behavioristic study of natural events” and proposed a classification of systems according to the quality of the behaviors they are able to exercise. In this presentation we consider the problem of the resilience of a system when deployed in a changing environment, which we tackle by considering the behaviors both the system organs and the environment mutually exercise. We then introduce a partial order and a metric space for those behaviors, and we use them to define a behavioral interpretation of the concept of system-environment fit. Moreover we suggest that behaviors based on the extrapolation of future environmental requirements would allow systems to proactively improve their own system-environment fit and optimally evolve their resilience. Finally we describe how we plan to express a complex optimization strategy in terms of the concepts introduced in this presentation.
The paper accompanying this presentation is available at https://dl.dropboxusercontent.com/u/67040428/Articles/DF14b_Wiener21stA.pdf
Antifragility = Elasticity + Resilience + Machine Learning. Models and Algori...Vincenzo De Florio
Presentation for the ANTIFRAGILE 2014 workshop, https://sites.google.com/site/resilience2antifragile/
Abstract: We introduce a model of the fidelity of open systems—fidelity being interpreted here as the compliance between corresponding
figures of interest in two separate but communicating domains. A special case of fidelity is given by real-timeliness and synchrony,
in which the figure of interest is the physical and the system’s notion of time. Our model covers two orthogonal aspects of fidelity,
the first one focusing on a system’s steady state and the second one capturing that system’s dynamic and behavioral characteristics.
We discuss how the two aspects correspond respectively to elasticity and resilience and we highlight each aspect’s qualities and
limitations. Finally we sketch the elements of a new model coupling both of the first model’s aspects and complementing them
with machine learning. Finally, a conjecture is put forward that the new model may represent a first step towards compositional
criteria for antifragile systems.
Service-oriented Communities and Fractal Social Organizations - Models and co...Vincenzo De Florio
Presentation given by Vincenzo De Florio at the Ceremony for the handing of the 2013 Faculty Awards.
Keywords: Fractal social organizations; service oriented communities; mutual assistance communities
Seminarie Computernetwerken 2012-2013: Lecture I, 26-02-2013Vincenzo De Florio
Seminarie Computernetwerken is a course given at Universiteit Antwerpen, Belgium
A series of seminars focusing on various themes changing from year to year.
This year's themes are: resilience, behaviour, evolvability; in systems, networks, and organizations
In what follows we describe:
themes of the course
view to the seminars
rules of the game
TOWARDS PARSIMONIOUS RESOURCE ALLOCATION IN CONTEXT-AWARE N-VERSION PROGRAMMINGVincenzo De Florio
Adopting classic redundancy-based fault-tolerant schemes in
highly dynamic distributed computing systems does not
necessarily result in the anticipated improvement in
dependability. This primarily stems from statically predefined
redundancy configurations employed within many classic
dependability strategies, which as well known may negatively
impact the schemes' overall effectiveness. In this paper, a
novel dependability strategy is introduced encompassing
advanced redundancy management, aiming to autonomously
tune its internal configuration in function of disturbances
observed. Policies for parsimonious resource allocation are
presented thereafter, intent upon increasing the scheme's cost
effectiveness without breaching its availability objective. Our
experimentation suggests that the suggested solution can
achieve a substantial improvement in availability, compared
to traditional, static redundancy strategies, and that tuning the
adopted degree of redundancy to the actual observed
disturbances allows unnecessary resource expenditure to be
reduced, therefore enhancing cost-effectiveness.
A Formal Model and an Algorithm for Generating the Permutations of a MultisetVincenzo De Florio
This paper may be considered as a mathematical divertissement as well as a didactical tool for
undergraduate students in a universitary course on algorithms and computation. The well-known problem of
generating the permutations of a multiset of marks is considered. We define a formal model and an abstract
machine (an extended Turing machine). Then we write an algorithm to compute on that machine the successor
of a given permutation in the lexicographically ordered set of permutations of a multiset. Within the model we
analyze the algorithm, prove its correctness, and show that the algorithm solves the above problem. Then we
describe a slight modification of the algorithm and we analyze in which cases it may result in an improvement of
execution times.
This paper, the ideas in it, and its realization are the work of the first author only.
A FAULT-TOLERANCE LINGUISTIC STRUCTURE FOR DISTRIBUTED APPLICATIONSVincenzo De Florio
The structures for the expression of fault-tolerance provisions into the application
software are the central topic of this dissertation.
Structuring techniques provide means to control complexity, the latter being a relevant factor
for the introduction of design faults. This fact and the ever increasing complexity of today’s dis-
tributed software justify the need for simple, coherent, and effective structures for the expression
of fault-tolerance in the application software. A first contribution of this dissertation is the defi-
nition of a base of structural attributes with which application-level fault-tolerance structures can
be qualitatively assessed and compared with each other and with respect to the above mentioned
need. This result is then used to provide an elaborated survey of the state-of-the-art of software
fault-tolerance structures.
The key contribution of this work is a novel structuring technique for the expression of the
fault-tolerance design concerns in the application layer of those distributed software systems
that are characterised by soft real-time requirements and with a number of processing nodes
known at compile-time. The main thesis of this dissertation is that this new structuring tech-
nique is capable of exhibiting satisfactory values of the structural attributes in the domain of soft
real-time, distributed and parallel applications. Following this novel approach, beside the con-
ventional programming language addressing the functional design concerns, a special-purpose
linguistic structure (the so-called “recovery language”) is available to address error recovery and
reconfiguration. This recovery language comes into play as soon as an error is detected by an
underlying error detection layer, or when some erroneous condition is signalled by the applica-
tion processes. Error recovery and reconfiguration are specified as a set of guarded actions, i.e.,
actions that require a pre-condition to be fulfilled in order to be executed. Recovery actions deal
with coarse-grained entities of the application and pre-conditions query the current state of those
entities.
An important added value of this so-called “recovery language approach” is that the exe-
cutable code is structured so that the portion addressing fault-tolerance is distinct and separated
from the rest of the code. This allows for division of complexity into distinct blocks that can be
tackled independently of each other.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
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Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
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Models and Concepts for Socio-technical Complex Systems: Towards Fractal Social Organizations
1. SYSTEMS RESEARCH AND BEHAVIORAL SCIENCE
Syst. Res. Behav. Sci. 2013; 00:1–24
Models and Concepts for Socio-technical Complex Systems:
Towards Fractal Social Organizations
Vincenzo De Florio1
, Mohamed Bakhouya2
, Antonio Coronato3
,
and Giovanna Di Marzo4
1Performance Analysis of Telecommunication Systems research group
Universiteit Antwerpen and iMinds Interdisciplinary institute for Technology
Middelheimlaan 1, 2020 Antwerp, Belgium.
vincenzo.deflorio@uantwerpen.be
2School of Engineering, Aalto University
Otakaari 4, 00076 Aalto, Helsinki, Finland.
mohamed.bakhouya@aalto.fi
3Institute for High Performance Computing and Networking
National Research Council
Via P. Castellino, 111, 80131 Naples, Italy.
antonio.coronato@na.icar.cnr.it
4Institute of Services Science, Universit´e Gen`eve
Battelle–Bˆatiment A, Rte de Drize 7, 1227 Carouge, Switzerland.
giovanna.dimarzo@unige.ch
SUMMARY
We introduce fractal social organizations—a novel class of socio-technical complex systems characterized
by a distributed, bio-inspired, hierarchical architecture. Based on a same building block that is recursively
applied at different layers, said systems provide a homogeneous way to model collective behaviors of
different complexity and scale. Key concepts and principles are enunciated by means of a case study and a
simple formalism. As preliminary evidence of the adequacy of the assumptions underlying our systems here
we define and study an algebraic model for a simple class of social organizations. We show how despite its
generic formulation, geometric representations of said model exhibit the spontaneous emergence of complex
hierarchical and modular patterns characterized by structured addition of complexity and fractal nature—
which closely correspond to the distinctive architectural traits of our fractal social organizations. Some
reflections on the significance of these results and a view to the next steps of our research conclude this
contribution. Copyright c 2013 John Wiley & Sons, Ltd.
Received ...
KEY WORDS: Socio-technical systems; Social organizations; Collective adaptive systems; Distributed
organizations; Fractal organizations
1. INTRODUCTION AND RATIONALE
Societal and technological progress have brought to a widespread diffusion of Internet-backed
computer services characterized by an ever increasing complexity, pervasiveness, and social
meaning (Fleisch, 2010). Ever more often people make use of and are surrounded by devices
enabling the rapid establishment of communication channels on top of which people may socialize
and collaborate, supply or demand services, query and provide knowledge as it had never been
possible before. Such devices become our knowledge and social backbone by means of which
∗Correspondence to: Vincenzo De Florio, Middelheimlaan 1, 2020 Antwerp, Belgium.
Copyright c 2013 John Wiley & Sons, Ltd.
Prepared using speauthmodified.cls [Adapted by the authors from speauth.cls version 2010/05/13 v3.00]
2. 2 V. DE FLORIO ET AL.
new spontaneous forms of socialization and novel forms of self-organization may arise—as
demonstrated by knowledge ecosystems (Bray et al., 2008), cyber-physical societies (Zhuge, 2010),
and mutual assistance communities (Sun et al., 2006; Sun et al., 2010). The virtually instantaneous
diffusion of knowledge and awareness granted by such digital ecosystems is already producing
novel forms of collective intelligence and social interaction, with tremendous significance in terms
of marketing, economy, welfare, and social values (P´or, 2000).
The above mentioned novel forms of social organization and interaction are a promise of new
wealth and quality for all; at the same time, they also constitute a covenant of new solutions against
the many new problems our societies are experiencing. The overwhelming increase in the human
population and in particular of the elderly; the dissipation of valuable resources such as water,
energy, and clean air; the ill-considered management of waste are but a few examples that show
how the current social organizations are proving to be ineffective and unable to scale to the sizes
of our new “big world” (Hardin, 1968; Barabasi et al., 2013). Assistance of the elderly population
is a typical case in point: The share of the total population older than 65 is constantly increasing
worldwide (Anonymous, 2011; Anonymous, 2012), while the current organizations still provide
assistance in an inefficient and inflexible way. Though effective when the context was different
and a large amount of resources were available to manage a smaller demand, this approach is now
becoming too expensive and thus unacceptable. Merely expanding the current organizations without
properly restructuring them is simply not working anymore (De Florio & Blondia, 2008).
Promising solutions to this problem come from the domain of control systems. Such systems
have been traditionally crafted by using paradigms such as the centralized, the hierarchical, or the
heterarchical (Dilts et al., 1991). More recently additional classes of distributed control mechanisms
have been introduced so as to enhance efficiency and reduce the bottlenecks characterizing the
classical paradigms. The terms used in literature to refer to these classes is bionic, holonic,
and fractal organizations (Tharumarajah et al., 1996; Ryu, 2003). Said solutions have been
successfully applied in several domains in order to achieve “smarter organizations”, i.e. systems
characterized by greater scalability, robustness, and manageability with respect to their traditional
counterparts (Warnecke & H¨user, 1993; Tharumarajah et al., 1998; Ryu, 2003). Our conjecture and
major starting point in the current discussion is that the above distributed mechanisms may provide
us with promising paradigms for the design of socio-technical complex systems able to make full
use of the potential inherent in our societies so as to turn them into abundant sources of valuable
assets, complex collaborative behaviors, and massive redundancy. A major challenge then becomes
being able to master the complexity of said mechanisms and create models for the organization and
the management of massively distributed open socio-technical systems based on their paradigms.
1.1. Contributions and Structure
Section 2 presents our first contribution in the above stated framework of problems, namely the
definition of a class of socio-technical complex systems based on a distributed, bio-inspired,
hierarchical organization. Said organization is characterized by a same building block that is
repeated at different layers so as to manage both self-sufficient and inter-community collective
behaviors. Its building block, called service-oriented community, is “simultaneously a part and a
whole, a container and a contained, a controller and a controlled” (Sousa et al., 2000) in that it
represents the canon (Ryu, 2003) of a fractal organization (we refer the reader to Sect. 4.1 for more
information on fractal organizations). This fact led to the name of “fractal social organizations” for
systems compliant to our models (De Florio et al., 2012).
A second contribution of this paper is reported in Sect. 3. In that section we describe a model of the
collective behaviors within non-hierarchical and static socio-technical systems. A dynamic system is
introduced to express the life-cycle of active behaviors within said socio-technical systems. Despite
so simple a formulation, the resulting dynamics produce complex emerging properties. In particular,
• The geometrical representations of the orbits of the dynamic system exhibit a spontaneous
emergence of self-similar patterns, some of which likely to be characterized by a fractal
dimension.
Copyright c 2013 John Wiley & Sons, Ltd. Syst. Res. Behav. Sci. (2013)
Prepared using speauthmodified.cls DOI: 10.1002/srbs
3. TOWARDS FRACTAL SOCIAL ORGANIZATIONS 3
• A structured addition of complexity appears to emerge as complex structures reveal to be the
result of a regular composition of “prime” (i.e., no further decomposable) building blocks.
• A hierarchical organization spontaneously shapes up.
It is worth remarking how several of the above properties closely correspond to the distinctive traits
of our fractal social organizations. We conjecture that so pronounced a similarity may hint at the
emergence of scalability and robustness in future socio-technical complex systems designed after
our fractal social organizations.
This article is concluded by a discussion of related concepts and disciplines in Sect. 4 and by a
summary of our preliminary results as well as our plans for future research in Sect. 5.
2. FRACTAL SOCIAL ORGANIZATIONS
The starting point of our discussion is the definition of social organization provided by Boulding
in his classic General Systems Theory article (Boulding, 1956). In the cited renowned contribution
Boulding provides a classification of system behaviors and—to the best of our knowledge—he is
the first scholar to highlight explicitly the role and significance of socio-technical complex systems
and their behaviors. Social organizations correspond to said systems and are classified by Boulding
as the most complex system category. His definition for social organizations is “a set of roles tied
together with channels of communication”. We observe how even so concise a definition already
captures several important aspects of the dynamics of collective behavior:
A set...: Social organizations are selections of societal constituents.
...of roles...: Said selections are characterized not by the identities of their constituents, but rather
by their role: Quoting again from (Boulding, 1956), in social organisations “the unit [...] is
not perhaps the person but the role—that part of the person which is concerned with the
organisation or situation in question”. In algebraic terms this translates in modeling social
organizations as multisets of roles. One such model is introduced in Sect. 3.
...tied together...: Shared goals and common opportunities may lead individuals to join forces
and constitute a new “social” entity able to exert purposeful collective behavior. We refer
to such entity as a community. Reasons for individuals to tie together into a community
may be temporary or permanent; moreover, they may be the result of purposeful active
individual behaviors (Rosenblueth et al., 1943) as a response to the onset of an environmental
condition—for instance, a threat to survival or an opportunity for economical profit—or
simpler forms of individual behavior such as those typical of animal instinct. Moreover, the
resulting social entity may be a temporary or permanent one. All these factors influence
the dynamics of creation, operation, and destruction of the community as a new “greater
individual” able to exert purposeful active social behaviors—examples of which are the
collective strategies discussed in (Astley & Fombrun, 1983). In (De Florio & Blondia, 2010)
we used the term social energy to refer to the product of such collective behaviors. In the same
paper the term “community” was used to refer to social organizations.
...with channels of communication: Such channels represent the media by means of which
the constituents of social organizations timely share their individual goals, situations, and
states. Channels also induce concepts such as proximity and membership: Depending on the
characteristics of the communication channels members of the communities shall or shall not
be able to access shared knowledge and take part in social decisions.
The just mentioned aspects all play an important role in a specialization of Boulding’s social
organization that we called Fractal Social Organizations (FSO). In order to present the specific
aspects characterizing FSO with respect to its genus proximum in what follows we first introduce,
in Sect. 2.1, a number of preliminary concepts by means of a case study. Secondly, in Sect. 2.2,
we enunciate a number of architectural elements underlying those preliminary concepts. Finally, in
Copyright c 2013 John Wiley & Sons, Ltd. Syst. Res. Behav. Sci. (2013)
Prepared using speauthmodified.cls DOI: 10.1002/srbs
4. 4 V. DE FLORIO ET AL.
Sect. 2.3 and Sect. 2.4, we make use of the above concepts and elements to define respectively the
building block and the control architecture of our FSO.
2.1. Case Study
Let us suppose that Jane, an elderly woman, is living in her smart house. Jane’s smart house includes
several devices, among which an accelerometer that is used to assess situations such as “Jane has
fallen”. The smart house service includes also a general practitioner (GP) who is timely informed
of situations such as the above one through some communication channel. Let us consider the
following set of roles:
S1 = {δ0, δ1, δ2, . . . , δd, GP, Channel, Jane},
in which δ0 is the above mentioned accelerometer, δ1 is an alarm module (to be introduced later on),
Channel is a communication channel to transfer information between δ1 and GP, and δ2, . . . , δd are
devices that though available are not relevant to the current case. We shall refer to sets of roles as to
societies.
Let us now suppose that situation s = “Jane has fallen” takes place. Let us assume that δ0 operates
according to its specifications and correctly assesses the situation at hand. We shall then say that δ0
becomes active. According to Boulding’s definition of a social organization this implies that S1 is
now partitioned into two running components:
1. The running selection of roles appointed to deal with s (let us refer to this series of selections
as R1
1, R2
1, . . .)
2. The remaining roles (namely, the set of merbers that are inactive with respect to s, identified
by sets L1
1, L2
1, . . .).
In the case at hand the initial partition is given by
L1
1 = S1 {δ0}, R1
1 = {δ0}.
As δ0 is part of the current set R we shall say that δ0 is currently active. Becoming active means
that δ0 starts looking for pertinent activities—activities that is that are relevant to s. Activities are
interpreted here as well-defined protocols to deal with the situation at hand. In what follows we
shall not consider the nature of these protocols and just assume that they are formal descriptions of
common practice, specifications, or regulations, that have been associated to the roles of S1 through
some mechanism (for instance, meta-data).
In what follows we shall assume that one or more “reference domains” (RD) are semantically
associated to activities and societies, and that selections of societies inherit the RD of their superset.
In what follows we shall refer to selections of a society S that are active with respect to a given
situation s as the communities of S with respect to s. S and s will not be mentioned when obvious
from the context.
In the rest of this section we shall denote activities as follows:
¾situation : action¿.
Actions shall take the form:
( role → step ) ,
where “ ” stands for “one or more occurrence”. Occurrences are separated by either “;” (for
sequential execution) or by “//” (for parallel execution). Parentheses may be used to group
occurrences.
We now assume the presence of the following activity among those pertaining to role δ0:
¾fallen : (δ1 → alarm(fallen))¿. (1)
Activity (1) states that, once δ0 “fallen” is detected, δ1 is to execute a single action step and raise
an alarm. It is assumed in what follows that for said activity RD is equal to string “Healthcare”.
Copyright c 2013 John Wiley & Sons, Ltd. Syst. Res. Behav. Sci. (2013)
Prepared using speauthmodified.cls DOI: 10.1002/srbs
5. TOWARDS FRACTAL SOCIAL ORGANIZATIONS 5
It is worth remarking here how action steps call for roles to be played by some actants. If a
corresponding role can be found in community R1
1, that role is associated with the execution of the
corresponding step. On the contrary a restructuring takes place. As an example, if “alarm(fallen)”
calls for a communication channel, then this will lead to the following new selections:
L2
1 = S1 {δ1, Channel}, R2
1 = {δ1, Channel}.
The resulting new community R2
1 can now execute (1). After doing so, R2
1 dissolves back into the
original society: L3
1 = S1, R3
1 = ∅.
We now suppose that activity (1) injects the following new situation: “Alarm has been triggered”.
The corresponding activity is assumed to be the following one:
¾alarm(fallen): ( ( GP → fallenGP(fallen) )
// ( neighbor → fallenNeighbor(fallen) )
// ( relative → fallenRelative(fallen) ) )¿.
The first step of said activity implies updating the L and R selections as follows:
L4
1 = S1 {GP, Jane}, R4
1 = {GP, Jane}.
The treatment of this case is similar to what discussed above and therefore it will not be
repeated. What we now focus our attention on is the fact that action steps such as “(neighbor →
fallenNeighbor(fallen))” can not be resolved within the current society: In fact S1 does not include
a “neighbor” role. When a society finds itself short of a role, a new “meta-situation” occurs and
triggers the following default activity:
¾∅ : (S1 → up(neighbor, alarm(fallen)))¿. (2)
Situation “∅” may be interpreted as an exception that either forwards the request to any superset
societies that include the current one (if at least one such society exists) or it fails (if no superset
societies can be found). It is assumed that said selection is operated by creating a ranked list of
the superset societies and selecting the top “best matching” candidates. Ranking is operated by
considering a metric function measuring a “distance”, i.e., a compatibility degree, between the RD
of the activity and those associated to superset societies. Mission requirements, e.g. geographical
proximity, may also be used to operate said ranking.
Now let us suppose that at least one compatible superset society does exist and be equal to
S2 = {S1, Neighbor, Something else}. (3)
Through the onset of the meta-situation in S1, roles Neighbor and S1 become active. As usual this
translates into a partitioning of S2 into the following two blocks:
L1
2 = {Something else} and R1
2 = {S1, Neighbor}.
As a consequence, Neighbor now can become active within R1
2 and deal with the situation
inherited from S1. We remark how this mechanism correspond to a change of scale. Note also
how the life span of community R1
2 is defined by the duration of the action step “neighbor →
fallenNeighbor(fallen)”.
Intra- and inter-community social activities—we conjecture—may be useful to express autonomic
collaboration services among organizations. A distinctive advantage of such services would be,
e.g., the intelligent and timely resource sharing among care departments and institutions (Waring
et al., 2006). An interesting system based on such principles is SHINE (Secured Health Information
Network and Exchange), a web and mobile-based system for inter-facility health e-referrals†
.
†SHINE enables “health care providers and facilities to efficiently operate and communicate individual or aggregated
referral and case records to the right people in a timely, accurate, and interactive manner” (Anonymous, 2013b). Operating
in the Philippine, SHINE for instance eliminated “the long hours that a pregnant mother spends while looking for a
hospital on a trial-and-error basis” (Valmero, 2011).
Copyright c 2013 John Wiley & Sons, Ltd. Syst. Res. Behav. Sci. (2013)
Prepared using speauthmodified.cls DOI: 10.1002/srbs
6. 6 V. DE FLORIO ET AL.
Lessons learned from the above simple case study allow us to identify already the following
preliminary list of system requirements to the management of complex collective behaviors:
• Services and policies are required to associate social actants to roles.
• Actions and protocols are required to express and communicate situations, activities, and
actions.
• Services are required to manage the dynamic life-cycle of communities.
• A hierarchical organization of societies and communities as well as services for managing
exceptions and the ensuing propagation of situations are required.
The above requirements are complemented in what follows with a number of architectural
elements and assumptions.
2.2. Architectural Elements and Assumptions
In previous section we introduced the concepts of exceptions and of hierarchies of societies and
we identified a number of system requirements. Here we go one step further and sketch the basic
elements and assumptions of an architecture based on the principles and requirements discussed so
far. In what follows we shall purposely not distinguish between individual and social entities‡
.
Element 1 (Permanent and transient communities)
Let us consider two classes of communities: Permanent and transient communities. A community
is permanent when it is to respond to a persistent situation; an example is given by hospitals, which
answer the persistent necessity to provide medical care to people in need. Another example is S1 in
Sect. 2.1. On the contrary a community is said to be transient when it is dynamically constructed so
as to respond to the onset of a new situation; subsets R1
1–R4
1 in Sect. 2.1 are all examples of transient
communities.
Element 2 (Permanent and transient roles)
Let us consider two classes of roles: Permanent and transient roles. A permanent role is one
constitutionally assigned to a permanent community—e.g., the logistics department of a hospital
or the hospital itself. A role is said to be transient when it is played by a transient community or
when it is different from those constitutionally assigned to a permanent community.
Element 3 (Hierarchical structure)
Societies and communities shall be structured as the blocks of a Russian nested doll (also known as
“matryoshka doll”), with the following peculiar differences:
• Blocks may belong to more than one doll at the same time. This assumption corresponds to
the hypothesis that actants may play at the same time different roles in different communities.
• Blocks may contain more than one other block.
• Permanent blocks are semantically annotated so as to publish one or more of their RD
(reference context domains) as well as other information. As an example, through this
mechanism a hospital block may publish its nature of “care organization” and for instance
its policies of intervention.
Element 4 (Roles as references)
Blocks shall be represented as multisets of references to roles. Creating a new block from the roles
in an existing block does not subtract the roles from the latter—it only copies their associated
references.
Transient communities dynamically create new temporary blocks (i.e., new active R subsets)
whose lifespan is the amount of time required to deal with their associated situations—e.g. “fallen”
in (1). As mentioned in Sect. 2.1 such processing may result in two cases:
‡As well known, e.g., a human being may be regarded as either an individual entity or a social “body” of specialized
modules— the organ systems. In turn, each organ system may be considered as either an individual—that is, non-
dividable—module or another example of social organizations.
Copyright c 2013 John Wiley & Sons, Ltd. Syst. Res. Behav. Sci. (2013)
Prepared using speauthmodified.cls DOI: 10.1002/srbs
7. TOWARDS FRACTAL SOCIAL ORGANIZATIONS 7
1. The temporary block can be created making use exclusively of roles available within the
parent block. In this case the temporary block becomes a new sub-block of the parent block
until it concludes processing its situation.
2. The temporary block requires roles that are available without the parent block. Through the
exception mechanism discussed in Sect. 2.1 the situation and the call for roles is forwarded
to the parent of the parent block. If the parent block has more than one parent, a selection
is carried out by considering the reference context domains as well as possible constraints at
individual, collective, and mission level. At the current, still abstract level of specification, we
shall not discuss in detail how the selection is carried out and how the missing role is actually
sought.
Once all required roles are found, a new block is constructed.
Element 5 (Role templates)
Some mechanism may be foreseen such that, though transient in nature, temporary blocks leave
a “trace” in the system—thus becoming new known “templates of roles”. If a certain complex
situation regularly repeats itself then a corresponding role template may be recalled and considered
as a more compact (and thus, efficient) way to deal with it.
Role templates result in an elementary form of learning through experience, which corresponds to
the ability to respond more rapidly and efficiently to challenging environmental situations. Instinct
(innate behaviour) may also be based on predefined and genetically encoded role templates. We also
conjecture that the adoption of mechanisms similar to our templates of roles may be associated to
the widespread emergence of modularity in nature (Clune et al., 2013).
More complex learning solutions may involve “scoring” the templates of roles with respect
to their effectiveness while servicing a given recurring situation. By choosing the currently best
matching candidate and by updating the templates’ scores systems based on such strategy may
autonomously improve their environment fit. A similar scoring mechanism may be applied when
appointing the actants to be associated to sought roles—as it was done, e.g. in (Buys et al.,
2011; Buys et al., 2012), to self-select the best software versions for an N-version programming
composite (Avi˘zienis, 1995).
Element 6 (Template roles)
A template of roles shall be considered as a special case of role. Similarly to the concept of
subroutines in programming languages, template of roles may provide a way to refer concisely
to complex roles and their corresponding activities.
Through the above assumption templates of roles allow complexity to build up into more and
more “high level” roles (templates of templates, and so forth), which correspond to more and more
abstract activities. Intuitively, such activities may be interpreted as the tokens of the higher level
“languages” used by complex communities to play their roles.
Element 7 (Role permanentification)
When a template of roles (or of other templates) is repeatedly selected as an answer to a recurring
situation, the corresponding role shall become permanent. A corresponding set of actants that
specializes to play the template role may then be labeled as a new permanent community.
We now go one step further and make use of a subset of the just discussed requirements and
architectural elements to sketch the elements of the societal “building block” of our FSO as well as
its hierarchical organization.
2.3. Service-oriented Communities
Service-oriented Community (SoC) is the name we use to refer to the architectural element
corresponding to the concepts of “community” and “block” introduced in previous sections. As
described in (De Florio & Blondia, 2010), a SoC is a collective socio-technical system coupling
services provided by smart cyber-physical “things” with services supplied by human beings. Actants
that agree to join a SoC become their “members”. Members of a SoC are diverse, which translates
into a rich variety of services. By focusing for instance on human members only, diversity implies
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8. 8 V. DE FLORIO ET AL.
• different know-hows (e.g. those of a general practitioner, or those of a gardener);
• different policies for providing services (e.g. well-defined time schedules and fares, or
dynamically varying availability to provide free-of-charge services as occasional informal
carers);
• different location, in that members may be mobile, thus able to get dynamically closer to or
farther from other members;
• different value systems,
and so on. Such attributes are called in what follows features. Finally, members may have different
goals—for instance being able to reach a given location within a certain amount of time with a
certain budget of travelling costs and with at least a given quality of experience.
We shall call viewpoints any well-defined and agreed representation of a member’s features and
goals.
The operational model of the SoC is represented in Fig. 1, in which members publish their
viewpoints to other members in logical or physical proximity. Viewpoints may be issued, e.g., by
an elderly member in need of assistance—such as Jane in Sect. 2.1,—by a bystander posting their
tweets to describe an accident, by a monitoring device notifying the occurrence of some critical
event, by the acceptance service of a hospital, and so forth. Control and adaptation are achieved by
sharing viewpoints, unravelling semantic analogies among them and creating transient “networks
of relations” (Latour, 1996) among members. A way to enact the above semantic processes is
described, e.g., in (Sun et al., 2007).
Following some strategy (e.g., the one described in (De Florio et al., 2000)) one or more members
are given the responsibility to host a viewpoint registry and act as temporary coordinator. The
coordinators then become “collective members,” namely members representing a whole community
of other societal actants. Among their duties, the coordinators are to identify whether the viewpoints
currently stored in the registry correspond to a known situation such as those discussed in Sect. 2.1.
Analyses are performed by semantically matching new viewpoints with those already stored in the
registry (De Florio & Blondia, 2010). Analogies between viewpoints are identified as shown in (Sun
et al., 2007) by making use of ontologies associated with the reference domains. Once a similarity
is discovered the coordinator notifies the corresponding members. The shared knowledge enables
the creation of “bindings”, which may be spontaneous or mandatory depending on the context and
the policies in use. A practical way to implement said bindings in a flat (that is, non-hierarchical)
community was the so-called “Participant mode” described in (Sun et al., 2007).
Through bindings, members create a new temporary community. In conformity with what
assumed in Sect. 2.1 and Sect. 2.2 the coordinators also register the association between members
and roles and appoint the execution of activities. Coordinators may also keep track of the
effectiveness of the enacted communities in dealing with experienced situations through the “role
templates” of Sect. 2.2, which could be labeled with a running “score” tag. As already suggested, the
same principle could be applied in the selection of the actants to be enrolled for a new community
derived from a role template.
An example of a Service-oriented Community specifically targeting Ambient Assistance Living
services is given by the Mutual Assistance Community (Sun et al., 2010; Sun et al., 2007; Gui et al.,
2007). We refer the reader to the just cited references for more information on the technical design
of a SoC.
2.4. Fractal Social Organizations
A FSO may be concisely described as a fractal organization whose building block, or canon, is a
Service-oriented Community. The rest of this section in fact may be considered as an explanation
of the just given definition. More information about fractal organizations and the concept of canon
may be found in Sect. 4.1.
Fractal organizations are bio-inspired hierarchical distributed control architectures whose
components are simultaneously an individual and a social entity, “a part and a whole, a container and
a contained, a controller and a controlled” (Sousa et al., 2000). Said components are autonomous
entities corresponding to the communities exemplified in Sect. 2.1 and Sect. 2.2 and implemented
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9. TOWARDS FRACTAL SOCIAL ORGANIZATIONS 9
Figure 1. Representation of the canon of the Service-oriented Community.
as service-oriented communities as sketched in Sect. 2.3. By allowing SoC to become members
of other SoC we come up with an architecture with the “matryoshka doll” structure suggested in
Sect. 2.2, Element 3. Through the coordinator role the SoC assume a twin nature: They are at the
same time social collectives and social individualities, as exemplified by S1 in (3). This process is
known as “personization” in Actor-Network Theory (Latour, 1996).
The coordinators are also responsible for declaring the onset of exceptions (see (2)) and for
propagating the corresponding unresolved situations. This means forwarding the event to all
superset communities the current community is a member of, and possibly to other nearest
neighboring “higher-level” SoC. The “reference domain” meta-data may be used to define a metric
function as suggested in Sect. 2.1. This is represented in Fig. 2.
An important aspect of adopting SoC as building block for our fractal social organizations is that,
coherently with what discussed in Sect. 2.1, it allows multiple redundant responses to be considered
and arranged at the same time. As an example, a request from an elderly man in need of assistance
may be answered by (a) professional practitioners, (b) informal carers, (c) his relatives, (d) his
neighbours, and so forth. These multiple, redundant “planes” of assistance supply independent
service routes, which may be complemented by traditional (consolidated) service providers—e.g.
social insurance companies or other healthcare bodies. Furthermore, this approach makes it possible
to select a Pareto-optimal “plane” of assistance corresponding to the solution which provides the
expected quality of services with minimal resource consumption. Evidence to this second statement
has been obtained by simulating the social interactions of a single, non-hierarchical community (Sun
et al., 2007). In the same reference we showed how unraveling analogies via semantic reasoning
promotes both a higher level of resource utilisation and a stronger quality of experience.
An exemplary FSO is depicted in Fig. 2, which portrays service-oriented communities at different
scales—here identified as Layer 0, Layer 1, and Layer 2 members. A second representation is shown
in Fig. 3. In this case the FSO layers include individuals, smart houses, hospitals, and inter-facilities
of care. The same triangle-shaped pattern of the SoC repeats itself at each scale. The right-hand side
of Fig. 2 provides a representation of this phenomenon in terms of a well-known fractal structure
whose dimension is approximately equal to 1.5849625.
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Figure 2. The top picture represents the SoC architecture. Resemblance with a known fractal is shown in the
bottom picture.
We have just sketched the main characteristics of FSO, a socio-technical system with a complex
fractal organization. As a preliminary way to evaluate the effectiveness of our architectural
choices we now introduce a formal model based on Boulding’s definition of social organization
(see Sect. 2). A remarkable ensuing result is that several of the architectural elements of our
Fractal Social Organization—including, e.g., self-similarity, the appearance of modular structures,
and a hierarchical structure resulting from the recursive application of building blocks—emerge
spontaneously.
3. ALGEBRAIC MODEL FOR SOCIAL ORGANIZATIONS
As we mentioned in Sect. 2, Fractal Social Organizations may be considered as a specialization
of Boulding’s social organizations, which in turn are defined as “a set of roles tied together with
channels of communication”. Inspired by the algebraic nature of Boulding’s definition and by
previous work on the dynamics of multisets (De Florio, 1995; De Florio, 2005) we introduce in
what follows a formal model for the dynamics of the behaviors originating in social organizations.
Said model is presented in Sect. 3.1 while its properties are discussed in Sect. 3.2.
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11. TOWARDS FRACTAL SOCIAL ORGANIZATIONS 11
Figure 3. Exemplification of SoC social organizations.
3.1. Formal Model
Let us assume we have a set of roles, uniquely identified by integer numbers, as well as a set of
actants, each of which is associated with exactly one of the above roles. In what follows for the sake
of simplicity of treatise we shall assume this association to be static. As an example, let us say we
have
2 GPs, 2 nurses, and 8 patients,
collectively identified by multiset
S = {0, 0, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2}. (4)
In accordance with what discussed in Sect. 2.1 we shall refer to multiset (4) as to a society.
Furthermore, let us consider a concatenation operator, ·, to build ordered sequences of roles from
a society. In what follows we shall refer to any such ordered sequence as to an organization. An
example of organization is the following sequence:
0 · 1 · 1 · 2 · 2 · 2 · 2 · 0 · 2 · 2 · 2 · 2.
We shall also refer to the above sequence as “0 · 12
· 24
· 0 · 24
”, or simply as “011222202222”.
No specific meaning is given in what follows to organizations, their purpose, or their behavior.
The only aspect that is highlighted in the above definition is the order and role of its constituents,
as it is the case e.g. in DNA sequences of nucleotides. Another exemplification is an assembly line
or a construction pipeline, where “something is done” by moving objects through a string of actants
identified by their role (i.e., their peculiar function).
Now, as we did in Sect. 2.1, we shall consider the onset of some situation (Ye et al., 2012)
(endogenous or exogenous to S) such that some reaction is triggered by or through some of the
actants in that society. Said situations may be interpreted as opportunities (e.g., the onset of some
competitive economic advantage), threats (e.g., the outbreak of an infectious disease), crises (as a
result, e.g., of a stock market crash), or other circumstances or changes.
Consistently with what we have discussed in Sect. 2.1 here we assume the onset of s, namely
situation “one of the patients has fallen”. Through some communication channel we further assume
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12. 12 V. DE FLORIO ET AL.
that situation s triggers the intervention of 1 GP and 1 nurse. As a consequence of said intervention,
society (4) gets now partitioned into the following two blocks:
subset L = {0, 1, 2, 2, 2, 2, 2, 2, 2} and subset R = {0, 1, 2}, (5)
in which block L is inactive with respect to s, while R is active with respect to s. In what follows we
shall use the same terminology we introduced in Sect. 2.1 and refer to an active subset of a society
as to a community. When obvious from the context the firing situation will be omitted. Being active
means that the actants in R shall need to organize themselves (in some sense and here not specified
way) so as to deal with the situation at hand. Summarizing, multiset S is partitioned with respect
to s into an inert subset L and some organization of community R—that is, some ordering of the
active actants in S.
In what follows we shall model the dynamics of multisets L and organizations R. We shall assume
that events occur at discrete time steps and are modeled as either processing events or perturbations:
The former case stands for functional events corresponding to the processing of some workflow
internal to the organizations, the latter is the onset of new situations leading to
1. either a reorganization of the elements within a community
2. or a repartitioning of the society into two new blocks L and R .
In what follows we model the reorganization in step 1 as a permutation of R—that is, a new
ordering for its constituents. The rationale of this is that in this case the community responds to the
onset of s by finding resources within itself, possibly reshaping the flow of activities, but keeping
the same roles. In mathematical terms we say that R is closed with respect to s.
The repartitioning in step 2 means that the community calls for external resources—resources
that were inactive (i.e., they correspond to roles in L) but now need to be enacted (entering R and
thus constituting a new R ).
Let us assume that a given society consists of r roles, identified by numbers 0, . . . , r − 1, and that
role i is played by ni actants, 0 ≤ i < r. Let us call “First” a function defined as follows:
First : P(S) → O(P(S)), such that
∀X ⊂ S : ∃n0, n1, . . . , nr−1 : First(X) = 0n0
· 1n1
· (r − 1)nr−1
, (6)
where P(S) is the powerset of S (i.e., the set of all the subsets of S) and O maps sets onto
organizations. Note that First generates the organization corresponding to the “smallest” number
whose digits are the role identifiers. Let us refer to First(X) as to the “first organization” of X.
Similarly we define dual function “Last” and refer to Last(X) as to the “last organization” of X.
We now recall the definition of function “Succ” (adapted from (De Florio, 2005)). Succ takes as
input sequence
First(L) · R (7)
and returns the sequence corresponding to the next organization in the lexicographically ordered set
of all organizations of the input sequence. Applying Succ to the last organization returns the first
one. Dually, we define Succ−1
as the function returning the previous organization. If applied to the
first organization, Succ−1
returns the last one.
In principle any function producing all the organizations from a reference society could have been
used instead of Succ, but making use of the lexicographic order has the advantage that it makes it
easy to produce numerical representations that are all positive and monotonically increasing. Some
of the geometrical representations introduced in Sect. 3.2 require the latter property.
We now can model both cases of perturbations by “tossing a coin” corresponding to a non-zero
relative integer number, say z, and applying (Succ)z
if z > 0 and (Succ−1
)−z
if z < 0§
.
§In fact, due to the “wrap around” of functions Succ and Succ−1, z may be substituted with z mod pS, where pS is the
number of permutations of multiset S. This number also represent the amount of distinct orbits of Succ and Succ−1, i.e.
the length of their only cycle.
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13. TOWARDS FRACTAL SOCIAL ORGANIZATIONS 13
Figure 4. Exemplary life-cycle for the organizations of S = {0, 0, 1, 2, 3}.
.
If we toss a coin and apply the above process at each time step t, the following series
L(t), R(t) t≥0
(8)
defines a dynamic system corresponding to the dynamic life-cycle of all the possible organizations
originating from a given reference society of roles. Figure 4 shows all the orbits of (8) for society
{0, 0, 1, 2, 3} as well an exemplary life-cycle of a community from that society.
It is also possible to define RS as a relation between the organizations from a given society S
such that, for any two organizations of S, say a and b,
a RS b iff Succ(a) = b. (9)
When doing so, the series of orbits in Fig. 4 represent the transitive closure of RS. Note also how (8)
may be described as a “random walk” through that series. Figure 4 depicts one such exemplary
random walk.
3.2. Representations and Properties
The just described model considerably extends the deterministic combinatorial model introduced
in (De Florio, 2005). As it was done in the cited paper, here we can provide geometrical
representations for the evolution of the dynamic system in (8). In what follows we introduce some
of said representations.
• A first representation is obtained by mapping successive orbits of Succ onto integer numbers.
This is done by interpreting roles as digits and using the number of available roles, r, as base.
We call the obtained integers “organization numbers”. We shall use ν to represent the just
introduced mapping. Figure 5 shows this representation for society S = {03
, 112
}.
• A second geometrical representation is derived by taking the difference between two
consecutive organization numbers:
∀o ∈ O(S) : δ(o) = ν(Succ(o)) − ν(o).
We refer to the obtained integers as to “delta steps”. Figure 6 shows the delta steps of
society (4).
• Figure 7 shows the logarithms of delta steps.
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Figure 5. Organization numbers of society S = {03
, 112
}. Abscissa correspond to the successive orbits of
Succ (no wrap around is shown). Ordinates are the corresponding organization numbers. Note how dynamics
such as these are self-similar in that they include the dynamics of smaller societies.
• Finally, a family of geometrical representations is obtained by breaking down organizations
into m consecutive “chunks” of roles and by interpreting each of them as a base-r integer. In
turn, these numbers are used to identify points in m-dimensional space. Figure 8 shows this
representation for m = 2 and society (4) while two examples for m = 3 are depicted in Fig. 9
and Fig. 10.
As evident from the just referenced figures, several of the above representations are characterized
by some degree of self-similarity and by the emergence of modularity. This is particularly
meaningful in view of the results of other researchers. Johns, for instance, remarked in (Johns,
2011) how self-similarity is a necessary condition to self-organization, while the widespread degree
of modularity in the natural world has been associated by many with the emergence of evolvability—
the ability to rapidly adapt to a turbulent environment (Clune et al., 2013).
A second property of some of the just introduced geometrical representations is the fact that they
are factorisable: Their structure can be shown to be governed by well defined rules reproducing
the dynamics of simpler and simpler organizations, down to some atomic or “prime” organizations
that cannot be further simplified. This is shown for instance in Fig. 11. An interpretation of this
phenomenon is that factorization represents a change of scale: Prime organizations unite into a
coherent and self-similar hierarchical organization. The higher we go in the scale the more complex
is the organization. Such complexity though is not introduced arbitrarily but according to a well-
defined general rule. Remarkably, the above behaviors and the resulting “structured addition” of
complexity characterizing factorisable organizations are at the core of the concepts of Fractal Social
Organization and Service-oriented Community introduced in previous sections. It is our conjecture
that the above emerging traits and properties may hint at the emergence of scalability and robustness
in future socio-technical complex systems designed after our Fractal Social Organizations.
A third noteworthy property of some of our geometrical representations is revealed when
estimating their fractal dimension. For this we found a useful tool in Fractalyse (Vuidel, 2013), a
software package that provides several classical methods to measure the fractal dimension of black-
and-white images such as the one shown in Fig. 8. Available methods include box counting, radius
mass, correlation, dilation, and others. Fractalyse was successfully applied to estimate, e.g., the
fractal dimension of urban areas in Europe and China (Ma et al., 2008). Figures 12–15 show some
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15. TOWARDS FRACTAL SOCIAL ORGANIZATIONS 15
0
5000
10000
15000
20000
25000
30000
35000
0 500 1000 1500 2000 2500 3000
DeltastepsofS={0,0,1,1,2,2,2,2,2,2,2,2}
Figure 6. Delta steps of society S = {02
, 12
, 28
}. Also in this case self-similarity can be observed.
Figure 7. Logarithms of delta steps for society {0, 1, 2, 3, 4, 5}. Self-similarity is highlighted by emphasizing
the representations corresponding to society {0, 1, 2, 3} (small-sized region) and society {0, 1, 2, 3, 4}
(medium-sized region).
of the results we obtained with Fractalyse. As an example, the Box counting method with parameters
y = a × xd
+ c and exponential box size set to 2, applied to the bidimensional representations
of society S = {0, 1, 2, 3, 4, 5, 6, 7}, estimates with nearly perfect correlation a fractal dimension
d ≈ 1.792 with a = 9.5377 × 10−3
and c = 4.5496 (Fig. 14).
4. RELATED CONCEPTS
Three major concepts related to FSO are the focus of this section, namely (1) organizational aspects,
and in particular their nature being bio-inspired distributed organizations; (2) knowledge-related
aspects, namely their relation with so-called knowledge ecosystems; (3) the FSO social dynamics,
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16. 16 V. DE FLORIO ET AL.
Figure 8. Bi-dimensional representation of the organizations in S = {04
, 12
, 24
} (equal sized chunks).
whose closest inspiration comes from the social theory known as Actor-Network Theory (Latour,
1996). In what follows we highlight very concisely the relationships between FSO and the above
mentioned disciplines and subjects.
4.1. Organizations
A fundamental aspect for the effective emergence of desirable properties and behaviors—e.g.
scalability, manageability, robustness, and resilience—is “the way a social union is structured and
organized” (De Florio, 2013). Common terms to refer to such concept are “Partnership”, “reference
architecture”, “organizational structure”, “control structure”, and simply “organization”—the latter
being the term we shall use in what follows.
Commonly employed organizations include:
• Centralized control organizations, characterized by a single point-of-control-and-maintenance
(PCM). The PCM is the “personization” of the whole organization. Simplicity is the main
advantage of centralization, which is paid back by the introduction of a single-point-of-failure
as well as a structural bottleneck.
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Figure 9. POV-ray (Froehlich, 2012) rendition of society (4) (equal sized chunks).
Figure 10. POV-ray picture of S = {0, 1, 27
} (equal sized chunks). Note how the depicted structure is one
of the recurring patterns in Fig. 9. Note also how this closely corresponds to the concept of role template
introduced in Sect. 2.2. This is because S is in fact a subset of society (4) (as shown e.g. in (5)).
Copyright c 2013 John Wiley & Sons, Ltd. Syst. Res. Behav. Sci. (2013)
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Figure 11. Society {08
, 16
}, when represented bi-dimensionally, can be factorized into several instances of
atomic societal nuclei, or “prime communities”. Note how this closely correspond to the concept of canonical
“building blocks” such as the Service-oriented Community introduced in Sect. 2.3. (Picture from (De Florio,
1995)—copyright by Wolfram Research Inc. Used by permission.)
Figure 12. The Correlation method of Fractalyse applied to the bidimensional representation of society S =
{0, 1, 2, 3, 4, 5}. The analysis reveals a fractal dimension of 1.704 with a correlation coefficient c ≈ 0.9999.
• Hierarchical control organizations are characterized by a top-down flow of commands
and a bottom-up flow of feedback information. These flows are limited to the immediate
lower/upper level. Hierarchies scale better than centralized organizations though are not free
of shortcomings; in particular information must flow throughout the hierarchy to reach the top
control level, which translates in propagation delays and possibly propagation failures (viz.
loss or corruption of commands and feedbacks).
• Heterarchical control organizations are those in which autonomous agents coexist in a flat
structure with no predefined relationships. Information is distributed and there is no global
knowledge nor fixed points of control. Such “heterarchies” (Stark, 1999) are characterized
by the emergence of adaptability, by structural adoption of diversity, as well as by the
ability to overcome so-called “lock-ins” (local minima of the system-environment fit).
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Figure 13. The Radius Mass method of Fractalyse applied to the bidimensional representation of society
S = {0, 1, 1, 2, 2, 3, 3, 4}. A fractal dimension of 1.506 is suggested with a correlation coefficient c ≈ 0.993.
Figure 14. The Box Counting method of Fractalyse applied to society S = {0, 1, 2, 3, 4, 5, 6, 7}. Results
suggest a fractal dimension of 1.792 with a correlation coefficient c ≈ 0.9999.
A major shortcoming of heterarchies is that “central scheduling or resource planning is
impossible” (Ryu, 2003).
Other organizations emerged as an attempt to reduce the shortcomings of the above mentioned
ones. The main characteristics of said organizations are their bio-inspired origin and their distributed
nature. Such class of mechanisms is particularly interesting in the context of this paper as it has
been successfully applied to design of systems exhibiting resilience and robustness in the face of
changes and failures. In particular here we shall briefly recall the characteristics of three classes
of distributed control mechanisms—bionic, holonic, and fractal architectures (Tharumarajah et al.,
1996; Ryu, 2003).
Bionic organizations are based on a hierarchical composition of autonomous building blocks
characterized by spontaneous behavior and local interaction called cells or modelons. Biologically
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Figure 15. Scaling behavior and error curve produced by Fractalyse with the method of Fig. 14.
inspired concepts such as enzymes and hormones are used to model conflict resolution schemes.
Attraction and repulsion fields are used to model collaborative tasks.
Holonic organizations are compositions of building blocks, called holons, which “are
simultaneously a part and a whole, a container and a contained, a controller and a controlled” (Ryu,
2003). A same structure and a same set of configuration rules (the already mentioned called “canon”)
is repeated at different granularity scales producing so called holarchies. Holons are autonomous
entities that establish cooperative relationships and are characterized by the emergence of stability,
flexibility, and efficient use of the available resources. An example of said holarchies is given by
so-called holonic manufacturing systems (Ryu, 2003).
Fractal organizations are similar to holarchies, but the canon is not statically defined in that it may
freely evolve and differentiate. Local interaction and experience produce custom restructuring and
regrouping as exemplified, e.g., in the Fractal Company (Warnecke & H¨user, 1993) and the Fractal
Factory (Tharumarajah et al., 1998).
4.2. Knowledge Ecosystems
Knowledge ecosystems (KE) are social organizations that aim at the emergence of collective
intelligence through the mutual promotion of the individual and the social dimension. KE are based
on the principle of social constructivism—the hypothesis that learning is a social process that takes
place through the interactions in a society. In order to consolidate knowledge and produce wisdom,
it is key that “information, ideas, insights, and inspiration cross-fertilize and feed one another
free from the constraints of geography and schedule¶
”. KE comprise three overlapping layers
or networks: (1) A social network whose members’ “productive conversations” and collaborative
behaviors create (2) “a knowledge network of ideas, information, and inspiration”, sustained by (3)
a technology network to communicate and persist ideas, knowledge, and lessons learned through
experience. In order to function, KE must enable the quick sharing of the above ideas, information,
and inspiration owned by the participating people, which is done through the technology network.
This process is called by P`or “electrification” of the knowledge network. Through such process
the social network becomes a “web of distributed intelligence”—a sort of collective “nervous
system” that is to enhance an organization’s ability to tap into its own collective intelligence and
thus formulate the most appropriate responses to turbulent environmental conditions. Said nervous
¶Here and in the rest of Sect. 4.2 quotes are from (P´or, 2000).
Copyright c 2013 John Wiley & Sons, Ltd. Syst. Res. Behav. Sci. (2013)
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21. TOWARDS FRACTAL SOCIAL ORGANIZATIONS 21
system is “embedded not in computers and hardware, but in the interactions among people that bring
the organization into existence day after day”.
4.3. Actor-Network Theory
Actor-Network Theory (ANT) is a complex social theory based on the above mentioned hypothesis
of social constructivism and the central idea that “essences” (viz., individuals and societies) are to
be interpreted not as “containers” characterized by a physical dimension, e.g., a surface or a sphere,
but rather as networks of nodes that have as many dimensions as they have “ties” (i.e., connections) .
Such ties are “weak by themselves”, though they achieve robustness (“material resistance”) through
their social nature: “Each tie, no matter how strong, is itself woven out of still weaker threads [..]
Strength does not come from concentration, purity and unity, but from dissemination, heterogeneity
and the careful plaiting of weak ties”. “Strength” here refers to the ability of the “essences” to
retain their identity in spite of environmental conditions affecting their ties and nodes. A fragile
essence is one characterized by one or more points-of-diffusion-failures—as it is the case for the
centralized and the hierarchical organizations discussed in Sect. 4.1; conversely, an essence is robust
if it tolerates discontinuities and other information diffusion failures.
Be it an individual or a society, an ANT essence is not a static, immutable entity: It “starts
from irreducible, incommensurable, unconnected localities, which [..] sometimes end [up] into
provisionally commensurable connections”. Strength is sought by conserving identity despite the
changes of scale that are necessary to counterbalance turbulent environmental conditions. The above
mentioned “careful plaiting of weak ties” is meant to guarantee that a network “is the same”, though
“stronger”. The structured addition of complexity that we observed in the organizations discussed in
Sect. 3 may provide—we conjecture—a geometrical interpretation to the ANT concept of strength.
5. CONCLUSIONS AND NEXT STEPS
We sketched the main design elements of fractal social organizations—a class of socio-technical
complex systems structured as fractal organizations and based on the recursive application of a
same building block, the service-oriented community. Self-similar, modular, and fractal-like “by
construction”, our solution—we argue—may provide our societies with a scalable and robust
system structure able to match effectively the dynamically varying requirements and the turbulent
environmental conditions that more and more threaten the manageability of traditional human
organizations (Barabasi et al., 2013).
As a preliminary way to prove the meaningfulness of our design choices we introduced a formal
model for the dynamics of simple, non-hierarchical social structures organized as permutations of
multisets of roles. Remarkably enough, we observed how the simple assumptions in our model
resulted in the spontaneous emergence of a hierarchical and modular organization characterized
by a structured addition of complexity and a fractal nature closely resembling the design traits of
our organizations. By virtue of said resemblance and building on top of past results (Johns, 2011;
Clune et al., 2013) we conjecture that the concepts presented in this paper may be used to capture
and conquer the complexity of traditional organizations that address vital services of our societies
including, e.g., care, crisis management, goods and energy distribution, and civil protection. In
the long run, should our conjecture prove correct, this may help fulfilling the visions of “smarter
organizations” such as those expressed in (Anonymous, 2013a).
Considerable new challenges will need to be addressed in our future work. This will include
investigating the effectiveness of FSO as a system structure for the intelligent sharing of resources,
competences, knowledge, and goods. Moreover, scientific evidence shall be sought to verify the
robustness, resilience, and self-management capability of socio-technical complex systems based
on our models. We are already working in this direction by making use of Alchemist (Pianini et al.,
Here and in the rest of Sect. 4.3 quotes are from (Latour, 1996).
Copyright c 2013 John Wiley & Sons, Ltd. Syst. Res. Behav. Sci. (2013)
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22. 22 V. DE FLORIO ET AL.
2013)—a powerful tool for the simulation and verification of pervasive service ecosystems. Formal
methods such as bi-graphical reactive systems (Milner, 2008) are also being used (Coronato et al.,
2012) to describe the behaviors of fractal social organizations.
Another “grand challenge” we plan to tackle is the design of knowledge ecosystems based
on our models. Here the major property we shall investigate will be the emergence of forms
of collective intelligence as well as advanced collective behaviors including, e.g., collaboration,
collective strategies (Astley & Fombrun, 1983), co-opetition (Brandenburger & Nalebuff, 1998),
and co-evolution (Adner & Kapoor, 2010).
Last but not the least, the current work provides us with a novel interpretation of the phenomenon
of modularization as a spontaneous process governed by simple mathematical rules and initial
assumptions. Further investigation shall be required to verify the relation between our results—and
our “systems based on numbers” (Wolfram, 2002)—and the emergence of evolvability in natural
organisms and biologically inspired artificial organizations (Clune et al., 2013).
ACKNOWLEDGEMENTS
This work was partially supported by iMinds—the Interdisciplinary institute for Technology, a research
institute funded by the Flemish Government—as well as by the Flemish Government Agency for Innovation
by Science and Technology (IWT).
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