Dynamic Knowledge Representation as a Formalization Conveyor for Manmade Systems With Useful Impulse

Many manmade systems, from tea clippers to banking database management tools, exhibit an important common feature that a useful impulse is produced and functionates in them, being affected by favorable or unfavorable circumstances. While some of these systems are highly formalized, others remain operated or investigated quite intuitively. Their structural similarity urges one to think of conveying of experience of formalization from most to least formalized systems, but this process itself needs formal grounds to avoid the errors of inadequate formalization. In this chapter, a solution in the dynamic knowledge representation method and underlying theory of multitudes are sought.

Biography as Scenario

Purely descriptive knowledge appears to have a structure that can be formalized using the newly developed tool of dynamic knowledge representation, the event bush. In its framework, a singular biography can be transformed into a knowledge-based system with an opportunity of creation of a database. However, the very approach to the database design may undergo quite a change thereafter. This change may concern the concept of primary key, composition of data scheme, and other fundamental issues of database design.

Modeling Spatial Evolution

Geographic features in the real world are represented by spatial entities such as point, line, and area in two-dimensional surfaces. These features tend to evolve in time, thereby characterizing change in their physical identity, evolution into new species, thus describing geomorphological change of geographic features. These phenomena can be formalized using spatio-temporal relations. Formal representation of changing geographic (spatial) features is the interest of this chapter. Formal methods for representing the event and process that causes geomorphological change are presented. The formalization of geographic entities that are temporally and spatially related in a two-dimensional plane using the interval logic and spatial logic would facilitate the understanding of how modeling of space-time using spatio-temporal relations represents spatial evolution over time. Representation of temporal dynamism can be accomplished using various models. Modeling using spatio-temporal graph is more apt as it contributes to the cause-effect analysis.

An Approach to Improve Bayesian Inference in Assessment of Coast Evolution

The chapter reports the state of the art in the modeling of coastal environments by the method of event bush. This method appears to be an efficient alternative to highly subjective conceptualizations used in the databases that provide data for probabilistic assessment of evolution of the coast. The event bushes themselves may be used for Bayesian computation, but there emerge complications that pose intriguing theoretical tasks. Still, their application requires deep conceptual rethinking of the field of knowledge including both the terminology and concepts traditionally accepted in it.

Formation of Faden Quartz Druses in Mid-Carboniferous Sandstones of the Donetsk Basin

The chapter addresses the mechanism of growth of druses of faden quartz in a tectonically deformed sandstone. A peculiar feature of this type of quartz, the so-called “white tape” represented by fine subparallel cracks with fluid inclusions, appears highly informative about the genesis of the mineral and tectonic regime of its growth. Two stages of formation of druses of faden quartz are recognized. The suggested mechanism is checked for contradictions by means of the event bush method. The proposed event bush model appears to describe a wider range of quartz formation environments and therefore may serve as a conceptual framework for various models of quartz growth in sedimentary rocks.

The Event Bush Method in the Light of Typed Graphs Illustrated by Common Sense Reasoning

The event bush method being an efficient tool for representation and engineering of dynamic knowledge still lacks a strict mathematical foundation. Many of the syntactic properties of event bushes, however, seem compliant with directed graphs and can be described by typed graphs (i.e., by homomorphisms between directed graphs). This chapter explores an opportunity to formalize the syntactic structure of event bushes by means of typed graphs and shows useful implications of this approach for knowledge engineering and representation.

Qualitative Modeling of Ice Sheet Accumulation for Identification of Mass Balance Variation

Formation and evolution of ice sheets is one of the “hot” problems of modern geosciences, as it has direct implication on the issues of climate change and sea level rise. Different methods of measurement or computing the mass balance of modern ice sheets based on various physical models sometimes give conflicting results. To understand them, one should first reconcile the models they are based on. This, in turn, requires one to decipher the vision different researchers have on the generation and evolution of ice sheets. This vision is initially qualitative. Hence, a qualitative model is desired that would reconcile various, and sometimes conflicting, physical models. This chapter proposes this model.

Qualitative and Quantitative Formalisms for Knowledge Representation in the Theory of Multitudes

The theory of multitudes pretends to be an alternative to virtually all existing versions of the set theory and claims to better handle the knowledge about changing and evolving world. Then, by analogy, one may expect an original logical system based on the theory of multitudes, and within this logic, an authentic calculus. This chapter presents such calculus. Moreover, a new mathematical methodology can be developed on top of it, which together with the underlying logic, should clearly separate qualitative and quantitative, static and dynamic concerns and offer a formal method to proceed from representation of expert knowledge to modeling the world this knowledge is about.

Petri Net vs. Event Bush in Description of Environments of Alternative Directed Changes

Two alternative methods of knowledge representation, Petri net and event bush, have been applied to represent the same environments of alternative directed changes. The chapter examines the interrelation between the two methods and considers the ways of their mutual optimization and co-application. It discusses the balance between conceptual thoroughness and formal transparency from one side and readability, representation power, and common-sense clarity from the other. The interrelation and interplay of these two methods may bring fruitful revelations about how to treat dynamic knowledge, what strategy to choose to represent scenarios depending on the task in mind. This is seen as an important contribution to a new field of research, representation of dynamic knowledge, which may have wide application in a variety of fields, from history to technical design.

On Formalization and Representation in Collaborative Research

The aim of this chapter is to delve into the issues related to the formalization and transmission of knowledge within the scope of collaborative scientific research and to propose a new approach to address such difficulties. Analyzing methods and practices of collaborative research, the authors highlight that observation and reasoning are systematically prone to flaws, so that theorization is made highly conjectural. To gain reliability, points of views and visions need then a support from a community; in other words, they become public. To allow convergence to take place, conceptualizations need to be understood by people with possibly different cognitive models. Therefore, the authors propose using artifacts that can be strongly structured in individual use while weakly structured in common use. These artifacts take place generally as graphic representations, and as in the case of the arts, they can be realistic or abstract, they can emphasize, hide, or allow different, contrasting and concurrent interpretations of the exposed knowledge. Keywords: Collaborative Research, Scientific reasoning, Knowledge Representation, Knowledge Formalization, Boundary objects.