AbstractWe have designed ontologies related to an investigation of changes in gouge porosity in small-displacement faults via 2D computer simulations and experimental deformation. These ontologies, built based on the state-of-the-art domain models, will facilitate efficient online interchange and reuse of the knowledge resulting from research of physical process and materials involved in the deformation. The groundwork consists of ontologies for brittle rock deformation that help the understanding of deformation along natural and artificial brittle fault zones. These ontologies are formal, controlled vocabularies reflecting domain theories, and are developed for shared use within and across domains. The vocabularies include terms that represent real world individual entities such as a particular fault, mylonite, or gouge zone, and formal relations (e.g., is-a, part-of, participate-in, location-of, agent-of) between these individuals. Instances (i.e., individuals) of these material (e.g., particle) and immaterial (e.g., pore) entities have all their spatial parts present at all times of their existence (i.e., occur as wholes), and occupy same or different spaces at different times. These entities, sampled by geologists at specific time instants and locations, may change their properties (e.g., a fault changing length; a gouge becoming weakened) and qualities (e.g., a gouge changing density or porosity, or becoming hot) without losing their identity (e.g., San Andreas Fault remaining the same fault over a period of time). Some entities evolve into new entities (with new identity) over time through transformation, for example, particular granite (e.g., a sample of the Westerly granite) becoming a mylonite, or a 2D surface becoming a fold. Process entities such as deformation, cataclasis, and slip localization lack spatial parts, and involve material entities as agents (e.g., water is agent during hydrolytic weakening and hydraulic fracturing) and participants (e.g., rocks participate in fracturing). While material entities do not have any temporal parts, the process entities have no spatial parts. Instead, the latter entities have temporal parts that unfold over time in phases. The spatial location of material entities (e.g., fault, rock, mineral) that participate in particular processes (e.g., faulting, cataclasis) define the location where these processes occur. Processes (e.g., cataclastic flow) may destroy or create material entities (e.g., foliated cataclasites) over different times, and under different conditions. Our ontologies are designed with a modular architecture, allowing integration, and a more realistic depiction, of the interaction of individual entities that are involved in connection with a computer simulation study of porosity of various regions of experimental and natural gouge. The ontologies include the following classes and their object properties (given in parentheses): fault, gouge (porosity), region, particle (shape, number, contact, sliding surface area), particle size (distribution, fractal), packing (density), and gouge texture. The process classes include: shear displacement, shear localization, comminution, weakening, friction, cataclastic flow, and fracture. We present the vocabulary (i.e., classes and relations) of each of these non-overlapping ontologies from processual and material perspectives.

Ontology of Experimental and Simulated Fault GougeHassan A. Babaie1 and Jafar Hadizadeh2

1 Department of Geosciences, Georgia State University, Atlanta, GA 30302‑4105 Email: (hbabaie@gsu.edu) 2 Department of Geography and Geosciences, University of Louisville, Louisville, KY 40292

Introduction Shear zones are tabular, spatial regions along which complex deformation and other related processes lead to the localization of deformation. These dynamic processes, which are caused by plate motions, involve a variety of one- to three-dimensional spatial entities, at all scales: microscopic to lithospheric. In general, processes bring about qualitative and spatial change to the spatial entities (e.g., rock, mineral) over time intervals that start with initial and terminal, instantaneous temporal boundaries (i.e., events).

Processes, for example, change the spatial location, distribution, and orientation of some objects through translation, rotation and strain. They also lead to the creation of new entities, e.g., new mineral, mylonite, fracture, or fault may form during deformation. Processes may also lead to the destruction of entities, for example, bedding, fossil, and an original texture or structure may be annihilated during deformation. In this presentation, we present an approach based on a perspective that combines both the endurants and perdurants components of reality in shear zones, and discuss a method to design dynamic ontologies for shear zones.

Geoinformatics 2006May 10-12, Reston, Virginia

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One- to three-dimensional SNAP entities (endurants) are divided into three categories (Fig. 1): (1) Independent SNAP (substantial) entities, (2) SNAP dependent entities, and (3) spatial regions. The independent entities include: (i) substances, such as fault, breccia, molecule, water, and sag pond; (ii) fiat parts; (iii) boundaries, such as the boundaries of a shear zone, and grain boundary; (iv) aggregates of substances, such as the sum of all components of a strike slip fault (e.g., all its segments, bends, and steps); and (vi) sites, such as cavities, pores, holes, and other empty spaces in rocks that could be occupied by substances (e.g., water, air). The SNAP dependent entities depend on other endurants for their existence, and include: (i) qualities such as density, rigidity, bulk modulus, shape, size, and temperature; (ii) function, such as function of water is to enable diffusion of ions; and (iii) roles, such as the role of water in hydrolytic weakening or hydraulic fracturing.

Components of a Dynamic Ontology Ontologies are designed to formally capture, and explicitly specify, domain theories and knowledge about the world. Traditionally, ontologies in the Earth sciences have focused solely on the static part of reality (e.g., fault, mineral, mylonite), by only formalizing the endurants, and completely ignoring the perdurants (e.g., processes). This approach misses the dynamic component of reality (e.g., faulting, fracturing, mylonitization), and cannot be useful if we intend to represent our knowledge in a useful form. Endurant entities such as fault and cataclasite only have spatial parts; for example, a fault has segments, bends, and steps as parts. Endurants have properties, both relational (fault displaces rock sequence) and qualitative (a fault’s width, thickness, temperature at specific points, extent). An endurant occupies (i.e., is located in) a spatial region as a mereological whole (i.e., its entirety), which may change over time as the entity changes, e.g., as a fault propagates, thereby changing its length. This is in contrast with perdurants (e.g., sliding) that have temporal parts (phases or stages) but no spatial part. Only temporal parts of perdurants occur at specific time slices, i.e., they can only be detected as a part, but not as a whole, at specific times. The whole can only be ‘observed’ over a time interval. For example, slip along a fault may start with an initial phase of hardening (within a finite time interval), followed by dilatation, cataclastic flow or mylonitization (depending on depth), or by frictional sliding. Only one of these processes occurs at specific regions at specific time instants (i.e., the present). Processes are said to occur within spatio-temporal regions, defined by both time intervals and space. This is in contrast with the endurants which occupy spatial regions (i.e., at x, y, z coordinates) at the same or different times (t).

SPAN entities are divided into three categories (Fig. 2): (1) processual entities, (2) temporal regions, and (3) spatiotemporal regions. The processual entities include (i) processes such as brecciation, shear localization, and slip; (ii) fiat parts, such as the ’stick’ or ‘slip’ part of a stick-slip cycle; (iii) aggregates, such as slip which can be an aggregate of frictional sliding, creep, and other processes; (iv) settings, which are spatiotemporal counterparts of SNAP sites, such as Hollywood during the 2001 West Hollywood earthquake; and (v) instantaneous temporal boundaries (events), such as the first foreshock and last aftershock detected for the 1994 Northridge earthquake.

We observe and measure an endurant entity as a mereological whole, at the ‘present’ instant of time, in the field or laboratory. In the following we describe two orthogonal perspectives, i.e., SNAP and SPAN (Smith and Grenon, 2004) that are required to completely capture both static and dynamic components of reality (Figs. 1 & 2). The SNAP perspective (Grenon, 2003; Grenon and Smith, 2003) provides ‘snapshots’ of endurants at specific time indexes, vs. the SPAN perspective which provides a ‘video-like’, continuous series of views of perdurants over a time interval. The SPAN perspective provides a measure of change over time.

Dynamic natural and experimental gouge ontologies We have applied the SNAP and SPAN to represent the knowledge about natural, experimental, and simulated brittle deformation. The UML package diagram (Fig. 4), shows three sets of packages covering the endurants and perdurants (processes and activities) in this these domains. Each package translates into a single ontology or database, and contains several classes that depict the SNAP or SPAN entities which exist or occur in the domain of deformation in a natural, experimental, or simulated shear zone. Three types of relations exists between the classes: (1) intra-ontological relations, which obtain between classes within the same package, (2) inter-ontological relations, that obtain between classes in different ontologies (packages) of the same category (SNAP or SPAN), and (3) trans-category relations that relate SPAN classes to the participating SNAP classes. The inter-ontological and trans-ontological relations lead to dependency relations among the relata of these relations. This means that the dependent package includes or imports the required classes from other packages. The dependencies are depicted in the package diagram by the dashed arrows that point from the dependent package (ontology) to other ontologies. This modular structure is an efficient way to maintain and curate the ontologies. This means that structural geologists who collect their data through field work, rock deformation experiments in the lab, or simulation using a computer, can develop their own ontologies and databases, and then share their data. The modular architecture will facilitate merging and integration of the ontologies developed by autonomous groups of researchers working on related aspects of the same problems.

 

Figure 1. Top-level SNAP entities

Entities in the Earth realm can be divided into two disjoint (i.e., non-overlapping) groups: (1) endurants (continuants) and perdurants (occurrents). In a shear zone, endurants include objects such as mylonite, gouge, fault, and fracture. These endurant entities (depicted by the SNAP entities in Fig. 1) occupy same or different spatial regions at different times, and acquire different properties by participating in processes such as deformation, weathering, and metamorphism. These entities are said to endure over time by maintaining their identity despite the changes that are realized through processes. For example, the San Andreas Fault remains the same fault even though it goes through continuous spatial and qualitative change. Geologists capture information about the endurants at different times and places while these entities are going through change.

The perduring entities (depicted by the SPAN entities in Fig. 2) include processes (e.g., cataclasis, frictional sliding, creep) that unfold over time intervals that start and end with instantaneous, or relatively short-duration, events (e.g., slip event, seismic event). These entities involve one or more endurant entities (e.g., rock, grain) that display different properties (qualities) under different ambient conditions (e.g., pressure, temperature) (Fig. 3)

Figure 2. Top-level SPAN entities

Figure 3. Class hierarchy in the Quality Package

Figure 5. Types of Activity (5A), Studies (5B), Modeling (5C), Simulation (5D), Experiment (5E), and Sample (5F) in the domain.

Figure 4. UML Class Diagram

Fig. 5B

Fig. 5DFig. 5C

Fig. 5A

Figure 5E Figure 5F

Fig. 6A

Fig. 6C

Fig. 6B

Figure 9. Fracturing (9A) and Brittle_Deformation (9B) processes importing the SPAN ontologies, and relating to endurants.

Figure 6. Class diagrams of few of the endurants in the domain: Discontinuities (6A), Geomaterial (6B), and Region (6C).

Fig. 9A

Fig. 8. Process importing SPAN event.

Fig. 9B

Fig. 7. Endurants using SNAP ontology