The Evolution of the Linnaean Hierarchy

The Linnaean system of classification is a threefold system of theoretical assumptions, sorting rules, and rules of nomenclature. Over time, that system has lost its theoretical assumptions as well as its sorting rules. Cladistic revisions have left it less and less Linnaean. And what remains of the system is flawed on pragmatic grounds. Taking all of this into account, it is time to consider alternative systems of classification.     

Beyond the sentence given

A central and influential idea among researchers of language is that our language faculty is organized according to Fregean compositionality, which states that the meaning of an utterance is a function of the meaning of its parts and of the syntactic rules by which these parts are combined. Since the domain of syntactic rules is the sentence, the implication of this idea is that language interpretation takes place in a two-step fashion. First, the meaning of a sentence is computed. In a second step, the sentence meaning is integrated with information from prior discourse, world knowledge, information about the speaker and semantic information from extra-linguistic domains such as co-speech gestures or the visual world. Here, we present results from recordings of event-related brain potentials that are inconsistent with this classical two-step model of language interpretation. Our data support a one-step model in which knowledge about the context and the world, concomitant information from other modalities, and the speaker are brought to bear immediately, by the same fast-acting brain system that combines the meanings of individual words into a message-level representation. Underlying the one-step model is the immediacy assumption, according to which all available information will immediately be used to co-determine the interpretation of the speaker's message. Functional magnetic resonance imaging data that we collected indicate that Broca's area plays an important role in semantic unification. Language comprehension involves the rapid incorporation of information in a 'single unification space', coming from a broader range of cognitive domains than presupposed in the standard two-step model of interpretation.     

Knowledge extraction: a comparison between symbolic and connectionist methods

The use of a linguistic representation for expressing knowledge acquired by learning systems is an important issue as regards to user understanding. Under this assumption, and to make sure that these systems will be welcome and used, several techniques have been developed by the artificial intelligence community, under both the symbolic and the connectionist approaches. This work discusses and investigates three knowledge extraction techniques based on these approaches. The first two techniques, the C4.5 and CN2 symbolic learning algorithms, extract knowledge directly from the data set. The last technique, the TREPAN algorithm extracts knowledge from a previously trained neural network. The CN2 algorithm induces if...then rules from a given data set. The C4.5 algorithm extracts decision trees, although it can also extract ordered rules, from the data set. Decision trees are also the knowledge representation used by the TREPAN algorithm.     

Fishers' Knowledge of Marine Species Assemblages: Bridging between Scientific and Local Ecological Knowledge in Southeastern Puerto Rico

Increasingly, local ecological knowledge (LEK) held by groups of people engaging directly with their ecosystems for food production is recognized as a valuable tool for understanding environmental change, as well as for ecosystem management and conservation. However, the acceptance of LEK for resource management has been partly hindered by difficulties in translating local knowledge into a form that can be applied directly to Western scientific endeavors. Anthropology's focus on cultural meaning makes its practitioners uniquely qualified to find common ground between different systems of knowledge. Here, I report the use of ethnographic methods to represent Puerto Rican small-scale fishers' knowledge about tropical coastal habitat connectivity and the composition of species assemblages by underwater habitats. These two topics are of current interest for tropical fishery science and their study can benefit from fishers' extensive experience with the coastal environments on which they depend.     

Applications of a formal approach to decipher discrete genetic networks

Background  

A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant and applicable to address questions raised by biologists about such networks. The behaviour of these systems being complex, it is essential to exploit efficiently every bit of experimental information. In our approach, both the evolution rules and the partial knowledge about the structure and the behaviour of the network are formalized using a common constraint-based language.     

Expert systems in histopathology. II. Knowledge representation and rule-based systems

Two aspects of expert systems for use in diagnostic histopathology and cytopathology are examined: knowledge representation and the structure and operation of rule-based systems. Knowledge may be represented, e.g., in semantic networks, frames, multiple contexts and model-based structures; the choice of structure should be matched to the type of information to create an efficient and logically adequate expert system. In a rule-based system, knowledge is represented as "rules," often in the form of "IF (condition)-THEN (conclusion)" rules. The anatomy of such rules and their operation is explored via the use of examples. Uncertainty in rules is briefly addressed, and their processing by the symbolic reasoning of the "inference engine" of the expert system is described, including both "forward-chaining" ("data-driven") operations and "backward-chaining" ("goal-driven") operations.     

The interface between spoken and written language: developmental disorders

We review current knowledge about reading development and the origins of difficulties in learning to read. We distinguish between the processes involved in learning to decode print, and the processes involved in reading for meaning (reading comprehension). At a cognitive level, difficulties in learning to read appear to be predominantly caused by deficits in underlying oral language skills. The development of decoding skills appears to depend critically upon phonological language skills, and variations in phoneme awareness, letter–sound knowledge and rapid automatized naming each appear to be causally related to problems in learning to read. Reading comprehension difficulties in contrast appear to be critically dependent on a range of oral language comprehension skills (including vocabulary knowledge and grammatical, morphological and pragmatic skills).     

Folk Food Webs and the Role of Praxis in Substantive Ecological Knowledge

In the second half of the 20th century, investigations of indigenous environmental knowledge have been the subject of broader anthropological debates over how knowledge and experience are formed. Many such approaches have focused on environmental nomenclature and taxonomy, or what Roy Ellen has called “formal lexical knowledge” (1999). Such knowledge is readily available to an ethnographer and also more easily transmitted through language between subjects. These characteristics of formal lexical knowledge have led to considerable attention given to differences in environmental knowledge between cultures and have possibly resulted in the inflation of the efficacy of language in forming knowledge. However, if a different form of environmental knowledge is examined are there differences that emerge within communities and other processes beyond symbolic systems that shape knowledge? To address these questions, individuals in two Balinese agricultural communities were asked to construct food webs by linking photos of plant and animal species according to ecological interaction. The results showed significant variation in subjects’ knowledge by gender, which corresponds to labor experience in Balinese wet rice agricultural systems. By shifting attention toward emic models of ecological interactions, this article attempts to demonstrate (1) that environmental knowledge differs within a single community; and, (2) the role of labor experience or praxis has in forming environmental knowledge.     

Ethical Know-how and Traditional Ecological Knowledge in Small Scale Fisheries on the Eastern Black Sea Coast of Turkey

In the context of development and changes in two small-boat fisheries on the eastern Black Sea coast of Turkey, this article discusses how institutions are embedded in tradition, and what is “traditional” in “traditional knowledge”. Taking new institutional economics’ focus on institutions and approaches to traditional ecological knowledge as vantage points for discussion I compare systems of informal management in one discontinued and one new fishery to address questions such as: What kinds of knowledges and rules are involved in these kinds of fishing? What constitutes a tradition of knowledge? What is the role of tradition in working out new rules? I couple theories of situated knowledge (Ingold) and embeddedness of rules (Varela), both of which are inspired by Merleau-Ponty’s phenomenological approach, to show how institutions and traditional ecological knowledge are embedded and come together in practice.     

Geographic and Temporal Trends in Amazonian Knowledge Production

The presence of researchers from Western (i.e., developed world) institutions in Amazonia has frequently been contentious due to fears of ‘scientific imperialism’ or suspicions that they may be exerting undue influence over research agendas and knowledge production to the detriment of local researchers. Such negative perceptions are widespread, but not well substantiated. A more nuanced understanding of these issues requires information on who is conducting research in Amazonia and how knowledge production has changed over time. We performed a bibliometric analysis on Thomson Reuters'ISI Web of Science of all research articles about the Amazon published in three time periods: 1986–1989, 1996–1999, and 2006–2009. We found that the number of articles published and the diversity of countries involved in Amazonian research increased dramatically over the three time periods. The representation of several Amazonian countries—especially Brazil—increased, while the proportion of articles without a single author from an Amazonian country also increased. The results indicate that the research capacity of Amazonian countries has increased, but that leadership of high‐impact projects may still largely reside with researchers from developed countries.     

A Projection and Density Estimation Method for Knowledge Discovery

A key ingredient to modern data analysis is probability density estimation. However, it is well known that the curse of dimensionality prevents a proper estimation of densities in high dimensions. The problem is typically circumvented by using a fixed set of assumptions about the data, e.g., by assuming partial independence of features, data on a manifold or a customized kernel. These fixed assumptions limit the applicability of a method. In this paper we propose a framework that uses a flexible set of assumptions instead. It allows to tailor a model to various problems by means of 1d-decompositions. The approach achieves a fast runtime and is not limited by the curse of dimensionality as all estimations are performed in 1d-space. The wide range of applications is demonstrated at two very different real world examples. The first is a data mining software that allows the fully automatic discovery of patterns. The software is publicly available for evaluation. As a second example an image segmentation method is realized. It achieves state of the art performance on a benchmark dataset although it uses only a fraction of the training data and very simple features.     

Knowledge representation of signal transduction pathways

MOTIVATIONS: Signal transduction is the common term used to define a diverse topic that encompasses a large body of knowledge about the biochemical mechanisms. Since most of the knowledge of signal transduction resides in scientific articles and is represented by texts in natural language or by diagrams, there is the need of a knowledge representation model for signal transduction pathways that can be as readily processed by a computer as it is easily understood by humans. RESULTS: A signal transduction pathway representation model is presented. It is based on a compound graph structure and is designed to handle the diversity and hierarchical structure of pathways. A prototype knowledge base was implemented on a deductive database and a number of biological queries are demonstrated on it.     

"Nature" and "environment" in German and Portuguese sustainable development strategies for Johannesburg 2002

The recent Johannesburg Summit on Sustainable Development was an important symbolic moment, in spite of the poor results some people claim to have emerged from it. The very fact that official written texts were produced for a wide discussion in many participating countries is a positive side-effect, as it enables the almost unique possibility of using parallel corpora for the analysis of the respective language and underlying assumptions. This could lead to the identification of some potential causes for conflicts and misunderstandings. Both texts were produced according to a (supposedly, at least) common intention, so they may be seen as functionally equivalent. In spite of that, there are obviously huge differences, not only in extension, but also in the type of lexical combinations and stylistic features used. Words like ambiente, in the Portuguese language, and Umwelt, in German, as well as natureza/Natur, appear in very different lexical environments, so that one can, by means of a distributive methodology, obtain a picture of what might be intended with their use in the two countries. Another issue brought about by this analysis was a reflection on the concept of "foreign" language. This raises the question not only of knowing whether, or to what extent, written texts like these are really intended to have an effect on (local) people's minds, but also about pragmatic/cultural constraints that have influenced their very shaping.     

Knowledge extraction from evolving spiking neural networks with rank order population coding

This paper demonstrates how knowledge can be extracted from evolving spiking neural networks with rank order population coding. Knowledge discovery is a very important feature of intelligent systems. Yet, a disproportionally small amount of research is centered on the issue of knowledge extraction from spiking neural networks which are considered to be the third generation of artificial neural networks. The lack of knowledge representation compatibility is becoming a major detriment to end users of these networks. We show that a high-level knowledge can be obtained from evolving spiking neural networks. More specifically, we propose a method for fuzzy rule extraction from an evolving spiking network with rank order population coding. The proposed method was used for knowledge discovery on two benchmark taste recognition problems where the knowledge learnt by an evolving spiking neural network was extracted in the form of zero-order Takagi-Sugeno fuzzy IF-THEN rules.     

Buyer beware: robustness analyses in economics and biology

Theoretical biology and economics are remarkably similar in their reliance on mathematical models, which attempt to represent real world systems using many idealized assumptions. They are also similar in placing a great emphasis on derivational robustness of modeling results. Recently philosophers of biology and economics have argued that robustness analysis can be a method for confirmation of claims about causal mechanisms, despite the significant reliance of these models on patently false assumptions. We argue that the power of robustness analysis has been greatly exaggerated. It is best regarded as a method of discovery rather than confirmation.     

Universal Principles in the Repair of Communication Problems

There would be little adaptive value in a complex communication system like human language if there were no ways to detect and correct problems. A systematic comparison of conversation in a broad sample of the world’s languages reveals a universal system for the real-time resolution of frequent breakdowns in communication. In a sample of 12 languages of 8 language families of varied typological profiles we find a system of ‘other-initiated repair’, where the recipient of an unclear message can signal trouble and the sender can repair the original message. We find that this system is frequently used (on average about once per 1.4 minutes in any language), and that it has detailed common properties, contrary to assumptions of radical cultural variation. Unrelated languages share the same three functionally distinct types of repair initiator for signalling problems and use them in the same kinds of contexts. People prefer to choose the type that is the most specific possible, a principle that minimizes cost both for the sender being asked to fix the problem and for the dyad as a social unit. Disruption to the conversation is kept to a minimum, with the two-utterance repair sequence being on average no longer that the single utterance which is being fixed. The findings, controlled for historical relationships, situation types and other dependencies, reveal the fundamentally cooperative nature of human communication and offer support for the pragmatic universals hypothesis: while languages may vary in the organization of grammar and meaning, key systems of language use may be largely similar across cultural groups. They also provide a fresh perspective on controversies about the core properties of language, by revealing a common infrastructure for social interaction which may be the universal bedrock upon which linguistic diversity rests.     

On the Neurobiology of Truth

The concept of truth arises from puzzling over distinctions between the real and the apparent, while the origin of these distinctions lies in the neurobiology of mammalian cerebral lateralization, that is, in the evolution of brains that can address the world both indicatively and subjunctively; brains that represent the world both categorically and hypothetically. After some 2,500 years of thinking about it, the Western philosophical tradition has come up with three major theories of truth: correspondence, coherence, and pragmatist. Traditional philosophy has nevertheless failed to arbitrate much among these views; certainly no clear winner has emerged. I argue, however, that contemporary neuroscience provides adequate theoretical grounds for a unified theory of truth. More specifically, I contend that the correspondence, the coherence, and the pragmatic utility of symbols are each biological features of our neurophysiological information processing systems—that is to say, our brains. On my view, the traditional trifurcation of philosophical accounts of the predicate, “is true”, stems from a trifurcation of focus on the information latent in sensory, motor, and somatosensory cortices of the human brain.     

Community Intelligence in Knowledge Curation: An Application to Managing Scientific Nomenclature

Harnessing community intelligence in knowledge curation bears significant promise in dealing with communication and education in the flood of scientific knowledge. As knowledge is accumulated at ever-faster rates, scientific nomenclature, a particular kind of knowledge, is concurrently generated in all kinds of fields. Since nomenclature is a system of terms used to name things in a particular discipline, accurate translation of scientific nomenclature in different languages is of critical importance, not only for communications and collaborations with English-speaking people, but also for knowledge dissemination among people in the non-English-speaking world, particularly young students and researchers. However, it lacks of accuracy and standardization when translating scientific nomenclature from English to other languages, especially for those languages that do not belong to the same language family as English. To address this issue, here we propose for the first time the application of community intelligence in scientific nomenclature management, namely, harnessing collective intelligence for translation of scientific nomenclature from English to other languages. As community intelligence applied to knowledge curation is primarily aided by wiki and Chinese is the native language for about one-fifth of the world’s population, we put the proposed application into practice, by developing a wiki-based English-to-Chinese Scientific Nomenclature Dictionary (ESND; http://esnd.big.ac.cn). ESND is a wiki-based, publicly editable and open-content platform, exploiting the whole power of the scientific community in collectively and collaboratively managing scientific nomenclature. Based on community curation, ESND is capable of achieving accurate, standard, and comprehensive scientific nomenclature, demonstrating a valuable application of community intelligence in knowledge curation.     

Recognising and Translating Knowledge: Navigating the Political,Epistemological, Legal and Ontological

What does it mean to call something ‘knowledge’ today? What does this recognition or translation require? And what does it entrain? This introduction makes a novel synthesis of contributions to the Special Issue and advances observations regarding the ‘mythic’ qualities of intellectual property law, the precipitation of ‘nature’, and the importance of attending to what is lost when things and practices are also called ‘knowledge’. The papers cohere around a timely set of observations and critiques: critiques of the way the knowledge economy makes demands and defines expectations about value; of how intellectual property law lies behind and shapes exclusions, inclusions, and inequalities; of the ‘mythic’ status of assumptions informing laws about ownership; and the implicit hierarchy contained within types of knowledge as understood through the categories of western epistemology. By taking up effect rather than veracity and certainty, contributors leave the definition of knowledge to ethnographic subjects. That is, they attend to where and how things come to be called knowledge, and for what reasons, noticing how equivalences across practices, made for the purpose of creating the possibility of exchange value (and thus of encouraging circulation) does its work at the expense of multiple aspects, values, and relations that are also discernable in social processes that produce ‘knowledge’.