Enveloped_by — proposal definitions

April 18, 2008

I have been working towards proposing definition for my proposed spatial inclusion relation enveloped_by. After quite a lot of readings and discussions, the following two possible definitions are proposed. One is by using the tangential proper part relation and the other is by using covered by relation.

Spatial Inclusion Relation — Enveloped_by / envelopes :

Proposal definition 1:
enveloped_by(b,a) / envelopes(a,b) = TPP(a,b) and SCOINC(a,b)

enveloped_by(b,a)= a is tangentialproperpartof b and two boundaries of
a and b coincide at all points such that:
b is a closed material object (whether sphere, or cylindrical),
a is a material object,
the outer boundary of b and the inner boundary of a coincide with each
other at all points (i.e. the boundaries of b and a co-exist with each
other)

SCOINC(a,b) — if two (spatial) boundaries a and b coincide, a and b
cannot spatially exist independently or cannot be located farther from
each other

Proposal definition 2:
enveloped_by(b,a) / envelopes(a,b) = (bCOVERED_BYa) and (aSCOINCb)

enveloped_by(b,a)= b is coveredby a and two boundaries of a and b
coincide at all points such that:
b is a closed material object (whether sphere, or cylindrical),
a is a material object, and
the outer boundary of b and the inner boundary of a coincide with each
other (i.e. the boundaries of b and a co-exist with each other)

SCOINC(a,b) — if two (spatial) boundaries a and b coincide, a and b
cannot spatially exist independently or cannot be located farther from
each other

Properties: Intransitive and assymetric

Cardinality: one to one

Relations:
nucleus is enveloped_by nuclear membrane
mitochondria is enveloped_by double layered membrane
animal cell is enveloped_by cell membrane

Enveloped_by / envelopes = enclosed_by / encloses

Enveloped_by notequalto surrounded_by because in surrounded_by the boundaries of a and b do not coincide and a and b can spatially exist independently or can be located farther from each other.

References: RO, GFO, FMA, Point-Set Topological Relations, Region Connection Calculus

I have proposed these two definitions in the OBO-discuss and OBO-Relations mailing lists for further discussions and comment from the community. Let us see.


introducing spatial relations

April 5, 2008

I am discussing with the ontology communities OBO-relations, OBO, RO, GO, FMA about the relations that are used in the biology ontology. In RO, OBO there exists around 12 kinds of relations which are well defined under meronymy, class and spatial inclusion relations. With regard to the spatial inclusion relation I think that a few more relations needs to be introduced for connecting material spatial objects with materials. Because the relationships are require to create connections between a material with another material in relation to the manner in which they co-exist (nucleus enclosed_by nuclear membrane) and between a material and a material with respect to their arrangements (Histones wound_around DNA). With the existing set of spatial relations such as—located_in; contained_in; adjacent_to we cannot apply to the concepts such as nucleus and nuclear membrane; or mitochondria and double membrane. Inorder to connect these propositions, I propose the following:

nucleus enveloped_by/covered_by/enclosed_by/surrounded_by nuclear membrane

mitochondria enveloped_by/covered_by/enclosed_by/surrounded_by double membrane

However, which of the above is valid needs to be worked out by defining these relations. Well the community has invited proposals for such relations along with definitions.

Here is my proposal for such relationships:

encloses / enclosed_by
envelopes / enveloped_by
surrounds / surrounded_by
wound around
bounded_by
covers / covered_by
attaches / attached_to
connects / connected_to (RCC)

I am working on defining some of the above relations. I shall post later once the definitions are circulated in the community.


process modelling of cell biology

November 1, 2007

A part of my research work includes knowledge modelling of the cell structure and function. So far the modelling of structural aspects of cell has been managed quite well. The challenging task was to model the processes that occurs in a cell for example, mitosis, etc. We tried to apply some process modelling languages such as conceptual graphs, business modelling model, but the one that seemed to be applied appropriately as far as the functional aspects of cell are concerned, is the OPM model i.e. the Object Process Methodology proposed by Dov Dori.

The OPM model is indeed useful for modelling the process of cell division— mitosis (prophase, metaphase, anaphase, telophase). I am following the principles and notations described in the OPM model and have achieved quite good representations of the mitotic phases. The process modelling is really challenging and fun as a task. I intend to publish these representations as I complete the task.


conceptual analysis

May 9, 2007

My work in the area of knowledge representation essentially involves conceptual analysis (of biology domain in my case). While performing the task of elicitation of knowledge, I use concept maps (refined concept maps) to get the experts (and novices) to articulate their knowledge. While performing the task of formalization of knowledge, I play a role of knowledge engineer wherein i re-encode the knowledge of the subject matter (which is expressed in natural language) into AI language i.e. applying constraints, rules and facts.

My earlier post on my work on building the knowledge organizers deals with formalization part of conceptual analysis. I do know that this research work is just a beginning of a massive project, and I really intend to continue working on it.

knowledge acquisition involves elicitating, analyzing, and formalizing the subject matter. during knowledge elicitation, the knowledge engineer asks expert to articulate the tacit knowledge in natural language. during formalization the knowledge engineer encodes the knowledge that is elicited from experts in rules and facts of some AI language.

conceptual analysis is central to knowledge acquisition. conceptual analysis is the task of analysing concepts expressed in natural language and making the implicit relations into explicit relations.

understanding of logic and language and philosophy (ontology) are pre-requisite for working on conceputal analysis. in computer science field, it is also called as conceptual modelling. other than its application in computer sciences, conceptual analysis can also be applied in different contexts such as interviewing an experimenter, child; an automobile expert in manufacturing or designning.

conceptual analysis determines the general principles which constitutes of semantic and episodic memory for defining an expert system. while episodic memory deals with information related to facts, the semantic memory includes five kinds of information—taxonomy, definitions, constraints, schemata, behavior.

although it is possible to perform conceptual modelling by using automated tools, the basic tools of usage are paper and pencil. One can cite two different tools—concept maps (Novak), and conceptual graphs (Sowa)—as tools for conceptual modelling.

concept maps serve as a common notation for experts and knowledge engineer, since they are informally used, are flexible, simple, and yet because of these features they lack in formal structure for knowledge representation and cannot be used to express logic and semantics. however, concept maps can be formalized by applying constraints.

conceptual graphs follows the version of semantic networks designed involving logic. they can be mapped directly to and from natural language; they can be translated to and from other AI formalisms; they can support automated knowledge acquisition tools.

Reference: John Sowa (1992), Conceptual Analysis as a basis for knowledge acquisition.