Three generations of Infoscapes

art is open source

infoscape: the virtual landscape of information

First Infoscape refers to the information and knowledge generated through the modalities of the pre-industrial city.

Second Infoscape refers to the information and knowledge generated in the industrial city (the second generation city, the city of infrastructures, transactions, sensors…)

The Third Infoscape refers to the information generated through the myriads of micro-histories, through the progressive, emergent and polyphonic sedimentation of the expressions of the daily lives of city dwellers (…) Casagrande uses the concept of the ruin to define the Third Generation City as the «ruin of the industrial city» and as the «industrial city ruined by people – human nature as part of nature.» (…) Uniting all of its elements, Human Ecology transforms the Third Infoscape into a commons, making it accessible, usable and performable, and opening up to the second stage of the working hypothesis, dedicated to creating a transparent, clear, trusted, high-quality relational environment dedicated to co-managing this novel form of public space.

The Third Landscape is the part of the natural environment that grows in-between bricks and stones, it is the grass that lives between train tracks, it is the natural space that finds its life in the cracks of the walls, or in the places of our cities to which we don’t pay much attentionIt is the natural space of our cities which has not yet been encoded. It is not found in the flowerbeds and hedges which our city administrations define through borders and limits: please keep off the grass, this is a bureaucratically instituted flowerbed.

Excerpts from Data and the city by Salvatore Iaconesi and Oriana Persico, published in Hybrid City 2015 Conference Proceedings. Quote taken from their Art is Open Source website 

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Intro to Rhizomatic learing


Cormier uses three paradigms of different approaches to learning; the first refers to Apollonius of Rhodes who taught Cicero and Juliuns Ceasar, the second regards the practices of the University of Toulouse in 1270 and finally, the third describes Johann Heinrich Pestalozzi’s efforts to train Swiss people how to read around 1800. In the first case, knowledge is created through attentive interaction; Cicero and Caesar -both of them Apollonius disciples- had to learn how to perform public speeches by practicing patience while trying out different arguments (one to one learning). In 1270 Toulouse, learning was perceived as “hearing” as University students were offered access not to books (as printing was not yet invented) but to listening the books’ content (upscaled catechetical approach where success is to repeat). In the case of Pestalozzi, mass scale education was possible through the textbook (trade of freedom to scale).

Cormier raises his eyebrow to the textbook approach:

Teaching in a graded environment is a true position of power. You get to decide, as a teacher, what someone needs to know and whether or not that person knows it. You get to set the measures of success (…) Who am I to be in a position to decide what someone else should know? What gave me the right to exercise the power that I had over my students? (…) My own academic path and that of my peers had already shown me that learners are not an homogenous group; did the literature really expect me to accept that a one size fits all approach would be successful? How could I know what a student needed to know before I met them? Was there some canon of knowledge that I could simply go to and pick the right topics off a shelf that would be applicable to everyone? How could I decide, ahead of time, what success was going to look like for a student?

while advocating for a rhizomatic approach where:

(…) My job as a teacher is to create smooth space. To create an uncertain space where students have a chance to be ready to create their own map. To build an ecology within which students can grow, wander, break off and reconnect. A place where they can access the voices of the past and present and use them to learn. If my students can learn when they are uncertain, they’ll be prepared to answer questions that I cannot. And, even better, ask questions that I might not think to ask. (emphasis is mine)

Full post available here

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Asimov’s prophecy


Excerpts from an interview at The Star, originally published Dec. 31, 1983

(…) Education, which must be revolutionized in the new world, will be revolutionized by the very agency that requires the revolution — the computer. Schools will undoubtedly still exist, but a good schoolteacher can do no better than to inspire curiosity which an interested student can then satisfy at home at the console of his computer outlet. There will be an opportunity finally for every youngster, and indeed, every person, to learn what he or she wants to learn,in his or her own time, at his or her own speed, in his or her own way.Education will become fun because it will bubble up from within and not be forced in from without.

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Resources for Community (E-Learning 3.0)

The term community here refers to the social context of students and their environs. A community is a group of people with a common purpose, shared values, and agreement on goals. It has powerful qualities that shape learning. A community has the power to motivate its members to exceptional performance. M. Scott Peck defined community as “a group whose members have made a commitment to communicating with one another on an ever more deep and authentic level.” It can set standards of expectation for the individual and provide the climate in which great things happen (…) A real community, however, exists only when its members interact in a meaningful way that deepens their understanding of each other and leads to learning. Many equate learning with the acquisition of facts and skills by students; in a community, the learners—including faculty—are enriched by collective meaning-making, mentorship, encouragement, and an understanding of the perspectives and unique qualities of an increasingly diverse membership

Bickford D.J., & Wright, D. (2006). Community: The Hidden Context for Learning. In D.G. Oblinger (Ed.), Learning Spaces, EDUCAUSE e-book. Full chapter available here 

In this paper I explore different ways to understand the idea of community. Using the work of Alphonso Lingis, I make a distinction between the rational community and the community of those who have nothing in common. The latter community is the community in which we are all strangers for each other. I argue that the language of the latter community is the language of responsibility. It is this language that enables us to speak with our own, unique and individual voice. I argue that education and educators should be concerned with the latter form of speaking.
Therefore, the community without community, which exists as the interruption of the rational community, is the most important, and ultimately the only relevant educational community.

Biesta, G. (2004). The community of those who have nothing in common: Education and the language of responsibility. In Interchange, 35(3), 307-324. / Full paper available here 

Distributed Consensus


A distributed system is a group of computers working together to achieve a unified goal (with laymen terminology, it is a group of computers working together as to appear as a single computer to the end-user or end-client). Every distributed system has a specific set of characteristics. These include:

  • Concurrency: meaning multiple events occur simultaneously
  • Lack of a global clock: in a set of computers operating concurrently, it is sometimes impossible to say that one of two events occurred first, as computers are spatially separated.By determining which event happens before another, we can get a partial ordering of events in the system (…) time and order of events are fundamental obstacles in a system of distributed computers that are spatially separated.
  • Independent failure of components: acknowledging that components in a distributed system are faulty. These include crash fail, omission, byzantin
  • Message passing: synchronous or asynchronous

The Consensus Problem, Defined

An algorithm achieves consensus if it satisfies the following conditions:

  • Agreement: All non-faulty nodes decide on the same output value.
  • Termination: All non-faulty nodes eventually decide on some output value.

Broadly speaking, consensus algorithms typically assume three types of actors in a system:

  1. Proposers, often called leaders or coordinators.
  2. Acceptors, processes that listen to requests from proposers and respond with values.
  3. Learners, other processes in the system which learn the final values that are decided upon

Notes from: How Does Distributed Consensus Work? by Preethi Kasireddy in Medium Blockchain, full article available here

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