Hi, Howard. Answering your question hb: i'm a newcomer to these discussions. what is the fourth great domain of science? Might be useful also for who came in the FIS list after 2015 IS4IS Summit. The last discussion before the conference, was A Dialog on the Informational as the 4th Great Domain of Science. A copy of the post is in the end of this message. Based on a Pedros's paper and Rosenbloom's book we propose that all scientific disciplines could be a combination of 4 great scientific domains. We are looking for a method to verify that the informational is the 4th great domain. Maybe Loet's Maps of Science should be a good approach. Cheers Moisés -- Moisés André Nisenbaum Doutorando IBICT/UFRJ. Professor. Msc. Instituto Federal do Rio de Janeiro - IFRJ Campus Maracanã moises.nisenb...@ifrj.edu.br *A Dialog on the Informational as the 4th Great Domain of Science* *Moisés André Nisenbaum Ken Herold* *PART 1: **Informational as the 4th Great Domain of Science* (Moisés André Nisenbaum) To classify is human (BOWKER STAR 2000). The organization of scientific knowledge is concern of scientists long ago. It started as a matter of librarianship and has evolved over time using various tools like enumerative classification, faceted classification, universal classification, controlled vocabulary, thesaurus, ontologies, Semantic Web. But how Information Science should organize scientific knowledge taking into account the dynamic behavior of disciplines and multi, inter and trans-disciplinary science of the twenty-first century (Information Society)? Rosenbloom (2012) proposed a model in which four great Scientific Domains - Physical (P) Life (L), social (S) and Computing (C) - can becombined to form any discipline http://moisesandre.com.br/FIS/debate/images/rosembloom-figure-2.1-domains-composing-disciplines.jpg. The first three (P, L and S) are well known domains and he proposes that the 4th is Computing. The small number of domains (compared with 10 of DDC and UDC) is offset by dynamic http://moisesandre.com.br/FIS/debate/images/Rosenbloom-figure-2.9-relationships.jpg relationships http://moisesandre.com.br/FIS/debate/images/Rosenbloom-figure-2.2-domains-simple-relations.jpg between domains that can be written by Metascience Expression Language http://moisesandre.com.br/FIS/debate/images/Rosenbloom-table-2.1-ME-Language.jpg. Although the prerequisites of a Great Scientific Domain has been well developed, Rosenbloom does not explain why they are in number of four or why these specific four domains. NAVARRO, MORAL and Marijuan (2013) propose that the 4th Great Scientific Domain is the Informational (I) instead of Computing. However, the biggest proposal is that the Information Science needs to be rethought to support theoretically and methodologically this 4th Great Scientific Domain. At the end of the article, the authors propose the insertion of the four Great Scientific Domains http://moisesandre.com.br/FIS/debate/images/Map-Pedro.jpg in High-Resolution Map of Sciences (Bollen at all, 2009) http://moisesandre.com.br/FIS/debate/images/Map-Bollen.jpg The problem is that all this is still in its philosophical field and miss a more pragmatic approach. When I observed this map, I just thought about how to measure these four domains and, even without even knowing exactly how to do this, I asked Bollen the raw data of his research. My initial idea was to identify every scientific discipline by a mathematical entity, for example a digital 4x4 matrix representing quantitatively the four Great Scientific Domain components and their relationships. The problem how to establish the criteria (bibliometric) that would define the matrix elements. Once created, we can check if the matrices really come together as expected. Best, Moisés *References:* BOWKER, Geoffrey C.; STAR, Susan Leigh. Sorting things out: Classification and its consequences. MIT press, 2000. https://books.google.com.br/books?id=xHlP8WqzizYClpg=PR9ots=Mz3xtCt2nEdq=Sorting%20things%20out%3A%20Classification%20and%20its%20consequences.%20lrhl=pt-BRpg=PR9#v=onepageq=Sorting%20things%20out:%20Classification%20and%20its%20consequences.f=false ROSENBLOOM, Paul S. On computing: the fourth great scientific domain. MIT Press, 2012. https://books.google.com.br/books?id=WGfxkn8OkwAClpg=PP1dq=On%20computing%3A%20the%20fourth%20great%20scientific%20domain.%20google%20bookshl=pt-BRpg=PP1#v=onepageq=On%20computing:%20the%20fourth%20great%20scientific%20domain.%20google%20booksf=false NAVARRO, Jorge; MORAL, Raquel del; MARIJUÁN, Pedro C.. The uprising of informational: towards a new way of thinking Information Science. Presented at 1st International Conference in China on the Philosophy of Information, Xi’an, China, 18 October 2013. http://moisesandre.com.br/FIS/debate/articles/pedro-article.pdf BOLLEN, Johan et al. Clickstream data yields high-resolution maps of science. PLoS One, v. 4, n. 3, p. e4803, 2009.
Dear Howard and FIS colleagues, Many thanks for your exciting comments; dealing first with Koichiro's intriguing point on action and probabilities, I think it links with the Quantum Bayesianism we discused last year in the list (von Baeyer's FIS New Year Lecture), and also with Karl Frinston's distributions / representations of probabilities in cerebral areas within an overarching entropy-minimization principle (it is not a physical entropy, and reminding Loet's comment, I think he was quite right with his contentious message of 15 June!). Action is but the forgotten other side the epistemic coin. Not to forget that a motor-centered epistemology has been recently discussed too. Responding to Howard's below, rather than making further interleaving, I will continue with a unitary text. In my view, the new informational thinking is slowly taking shape in a variety of fields, and the reference to Witzany's work on the viruses' social dynamics, is an excellent exponent on how carefully following the very dynamics of life, we may arrive at similar conceptual scenarios. My point is that biological communication (as well as human) does not occur in a vacuum where whatever combinatory game may be played. The life cycle of the entity is the big watcher of communication, not just passively waiting for some stimulus passing by, but actively deploying a series of molecular or supramolecular actions that for instance conduce to receive the appropriate information/communication or to engage in locomotor exploration. In general, action stemming out from the cycle --or propensity to action-- comes first, regarding the possible information gathered and the responses to be observed later on. Each life cycle has capability to deploy autonomously a very vast repertoire of adaptive actions / behaviors / communications that overall should conduce to its own advancement. So, the reliance on stimulus-response becomes a dubious way of lumping together the animate and the inanimate (a mere electromagnetic relay would also provide S-R behavior), leaving aside the most precious stuff of life: its informational organization in an autonomous, self-propelled life-cycle. It is a life-cycle that besides, has to take place in a highly complex and challenging ecological niche and within a tricky social environment. To reiterate the main point: the living is not S-R mechanistic, is informational. And what is information? I agree with Howard's relative approach to information. I think that, together with Marcin, we must organize a future discussion-session in the list to analyze this most integrative stance. I think that this view now is mature enough to be publicly discussed (and has already appeared in the literature occasionally). My personal contention is that a similar relative conceptualization may be extended to other informational entities (viruses, cells, organisms, brains, social groups and institutions, societies at large...) that also communicate in order to advance their self-production processes. Precisely in economy, we may understand that prices emerge as the information which connects and integrates the ACTIONS of producers and consumers allowing the self-organization of the whole. Obviously, the market information is exchanged in order to improve the condition of the individuals, and in aggregate to advance their own life cycles. Similarly, in physiological markets between cells, molecular signals --really an information flow-- would also be exchanged to coordinate the actions emerging from the ongoing life-cycles. If we consider that biological communication, and in general the communication of informational entities is tied to the maintenance and advancement of their self-production processes, the discussion of meaning follows quite naturally. Meaning becomes the impact of the information received upon the self-production process itself. In bio-molecular terms, meaning may be exactly enacted through a vastly used procedure, microarray experiments. By knocking down a particular receptor,or continuously keeping it on, we see the meaning effects that the specific signaling condition has on gene expression, on the whole cellular self-production. Meaningful communication begets relevant self-production changes. Then, lets generalize that informational entities are those that systematically intertwine the information (communication) flows and the energy (self-production) flows. The information derived from communication widely circulates and gets mixed with the inner self-production processes, adaptively changing the ongoing operations that constitute the metabolic life of the entity. That's the existential fate of all informational entities: they are adaptive, structurally always in the making, and in the dismantling. And the dismantling connects very nicely with the conditions that Howard establishes for the functioning of a collective learning
Fantasies about Quantum Mechanics aside, Probability and Information are distinct. Both are ways of speaking about the world. You may speak of alternatives probabilistically, but you cannot say that “information is probabilistic. Any truth based system is necessarily flawed (Godel) and dualist. The great disadvantage of mathematics grounded upon first-order logic is also exactly what you say because it can lead to over-confidence. This is not to say that logical proof systems are not useful for checking syntactic and semantic reasoning, they are. But they cannot provide the certainty desired. Mathematical proofs are not logical proofs. Reasoning about motion and degrees of freedom in dynamic structure, be it falling bodies or social graces, is not greatly helped by first-order logic. FOL is only concerned with certain types of thinking. Arbitrary axioms are no basis for rigor. In my view, at least, only the general covariance of premises can provide a basis of scientific argument. Constructive methods are flawed if they do not consider the action of premises together. Arbitrary axioms only represent the abductions that may lead us to this. Existence is before essence, remember the prime principle of existentialism. Regards, Steven On Jun 17, 2015, at 6:04 PM, Koichiro Matsuno cxq02...@nifty.com wrote: At 9:36 PM 06/17/2015, Pedro wrote: ... What if information belongs to action, [KM] This is a good remark suggesting that information may go beyond the standard stipulation of first-order logic. A great advantage of mathematics grounded upon first-order logic is to enjoy the provability or computability of an inductive judgement with use of the few axiomatic primitives. This scheme, however, does not work for information at large, though notably except for Shannon's information bits. If one faces a statement like information is probabilistic, it would go beyond first-order logic when the predicate to be probabilistic admits its quantification as revealed in the context-dependent probabilities in QM. Once we enter the higher stage of second-order logic, it could be possible to form an opinion of course while its provability may be out of reach in most cases. Nonetheless, if one wants to save something good with saying information is probabilistic, a likely makeshift might be to relate information to action, for instance, as appealing to conditiona! l probabilities which are quite at home with the action of setting and detecting such conditions. Koichiro ___ Fis mailing list Fis@listas.unizar.es http://listas.unizar.es/cgi-bin/mailman/listinfo/fis ___ Fis mailing list Fis@listas.unizar.es http://listas.unizar.es/cgi-bin/mailman/listinfo/fis
At 9:36 PM 06/17/2015, Pedro wrote: ... What if information belongs to action, [KM] This is a good remark suggesting that information may go beyond the standard stipulation of first-order logic. A great advantage of mathematics grounded upon first-order logic is to enjoy the provability or computability of an inductive judgement with use of the few axiomatic primitives. This scheme, however, does not work for information at large, though notably except for Shannon's information bits. If one faces a statement like information is probabilistic, it would go beyond first-order logic when the predicate to be probabilistic admits its quantification as revealed in the context-dependent probabilities in QM. Once we enter the higher stage of second-order logic, it could be possible to form an opinion of course while its provability may be out of reach in most cases. Nonetheless, if one wants to save something good with saying information is probabilistic, a likely makeshift might be to relate information to action, for instance, as appealing to conditiona! l probabilities which are quite at home with the action of setting and detecting such conditions. Koichiro ___ Fis mailing list Fis@listas.unizar.es http://listas.unizar.es/cgi-bin/mailman/listinfo/fis