Do process modelling techniques get better? A comparative ontological analysis of BPMN

Current initiatives in the field of Business Process Management (BPM) strive for the development of a BPM standard notation by pushing the Business Process Modeling Notation (BPMN). However, such a proposed standard notation needs to be carefully examined. Ontological analysis is an established theoretical approach to evaluating modelling techniques. This paper reports on the outcomes of an ontological analysis of BPMN and explores identified issues by reporting on interviews conducted with BPMN users in Australia. Complementing this analysis we consolidate our findings with previous ontological analyses of process modelling notations to deliver a comprehensive assessment of BPMN.

Context obfuscation for privacy via ontological descriptions

Context information is used by pervasive networking and context-aware programs to adapt intelligently to different environments and user tasks. As the context information is potentially sensitive, it is often necessary to provide privacy protection mechanisms for users. These mechanisms are intended to prevent breaches of user privacy through unauthorised context disclosure. To be effective, such mechanisms should not only support user specified context disclosure rules, but also the disclosure of context at different granularities. In this paper we describe a new obfuscation mechanism that can adjust the granularity of different types of context information to meet disclosure requirements stated by the owner of the context information. These requirements are specified using a preference model we developed previously and have since extended to provide granularity control. The obfuscation process is supported by our novel use of ontological descriptions that capture the granularity relationship between instances of an object type.

The production of male of-only offspring in beef cattle - a proof of principle project

The Australian beef industry places the greatest value in bulls, in comparison to cows, for prime beef production. Male carcasses can be sold for a larger profit due to their increased muscle mass. This project aims to demonstrate the feasibility of producing male animals that can sire male only offspring, through a transgenic approach in mice that could later be translated into livestock production systems. The mouse Sry (Sex determining region on the Y) gene has been shown to provide the initiating molecular signal leading to male sex determination in mammals. Sry has also been shown to cause sex reversal in XX mice transgenic for the gene. In this project Sry will be targeted to a locus not subject to X-inactivation on the X chromosome of XY mice. These mice will be bred to determine how the transgene is passed on, to determine expression of the transgene, and to assess its activity in causing XX sex reversal. The male mice transgenic for the Sry gene on their X chromosome will be produced using tetraploid aggregation, which in a single step produces 100% ES cell derived embryos. The same target locus can later be used to introduce the bovine SRY gene onto the X chromosome of bovidae species and using germ cell transplantation produce sex reversed animals. This would bypass the need for expensive chimera crosses and provide farmers with a stud bull capable of producing only sons.

Dissecting query performance in logical data models: Parsimony vs. greater ontological clarity

Even when data repositories exhibit near perfect data quality, users may formulate queries that do not correspond to the information requested. Users’ poor information retrieval performance may arise from either problems understanding of the data models that represent the real world systems, or their query skills. This research focuses on users’ understanding of the data structures, i.e., their ability to map the information request and the data model. The Bunge-Wand-Weber ontology was used to formulate three sets of hypotheses. Two laboratory experiments (one using a small data model and one using a larger data model) tested the effect of ontological clarity on users’ performance when undertaking component, record, and aggregate level tasks. The results indicate for the hypotheses associated with different representations but equivalent semantics that parsimonious data model participants performed better for component level tasks but that ontologically clearer data model participants performed better for record and aggregate level tasks.