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Abstract:
The most influential work in the application of ontology to conceptual modeling is that of Wand and Weber (1990, 1995) who used the ontology posed by Mario Bunge (1977). However, Bunge's ontology is concerned with representing the material world - the world of material objects that possess physical properties existing independently from human perception. It has no place for human intentions, interpretations, creations, or meaning. It is unconcerned about institutional reality - the world of conceptual objects and attributes created by human intentions and for human purposes. Examples of such conceptual objects are corporations, government agencies, money, educational institutions, contracts, and transactions. None of these are material objects about which Bunge's ontology is concerned yet they are at the core of what business organizations are. Lacking constructs for such objects, Bunge's ontology is an inappropriate foundation for conceptual modeling in the context of organizational information systems.

conceptual modeling, ontology, concrete object, conceptual object

Abstract:
Organizations and the information systems that support them are artificial and intentionally designed artifacts. Policies and procedures created by an organization define how specific events affect the states of things about which the organization is concerned. Active information systems are designed to participate in the operation and management of organizational processes. They calculate and ascribe state to material and artificial things according to rules designed by the organization and activated when identified events occur. The ontological definition of an event as a state-transition proscribes the representation of events as entities. The resultant conceptualization of an information system as a state-tracking mechanism obscures the critical role that events play in active information systems. Effective analysis and design of such systems requires a more substantive ontological definition of an event as an entity having both identity and properties. Included in an event's properties are the rules that govern state transitions caused by the event. The resultant conceptualization of an information system is an event-processing mechanism, actively interpreting and re-interpreting events with respect to extant and posed rules. This ontological definition treats things and events uniformly as entities enabling them to have appropriate representations at the conceptual level. It provides a context in which learning can be represented through the definition, identification, and classification of critical events and the evaluation and evolution of rules governing their effects. Additional research is needed to develop and evaluate conceptual modeling grammars and methods that implement this event conceptualization within an information system development methodology.

Data modeling, event construct, ontology

Abstract:
Information systems are integral to the management of business and organizational processes. They perform calculations and ascribe values to material and artificial things according to rules designed by the organization and activated when identified events occur. The ontological definition of an event as a state-transition results in the conceptualization of an information system as a state-tracking mechanism. It precludes the representation of events as entities at the conceptual level. Hence, the rules which are often central to the operations of the organization have no conceptual representation. A more substantive ontological definition of an event as an entity having identity and properties results in the conceptualization of an information system as an event-tracking mechanism, giving events and the rules that govern state-transitions the appropriate, central representation at the conceptual level.

Conceptual data modeling, event construct, ontology

Abstract:
Academic researchers access commercial websites to collect research data. This research practice is likely to increase. Is this appropriate? Is this legal? Such commercial websites are maintained to achieve business objectives; research access uses site resources for other purposes. Website administrators may, therefore, deem academic data collection inappropriate. Is there a process to make research access more open and acceptable to website owners and administrators? These are significant issues. This article clarifies the problems and suggests possible approaches to handle the issues with sensitivity and openness.

Research access to commercial websites may be manual (using a standard web browser) or automated (using automated data collection agents). These approaches have different effects on websites. Researchers using manual access tend to make a limited number of page requests because manual access is costly to perform. Researchers using automated access methods can request large numbers of pages at a low cost. Therefore, website administrators tend to view manual access and automated access very differently.

Because of the number of accesses and nonbusiness purpose, automated research requests for data are sometimes blocked by site administration using a variety of means (both technological and legal). This paper details the pertinent legal issues including trespass, copyright violation, and breach of contract. It also explains the nature of express and implied consent by site administration for research access.

Based on the issues presented, guidelines for researchers are proposed to reduce objections to research activities, to facilitate communication with website administration, and to achieve express or implied consent. These include notification to website administration of intended automated research activity, description of the research project posted as a web page, and clear identification of automated requests for web pages. In order to encourage good research practices with respect to automated data collection, suggestions are made with respect to disclosing methods used in research papers and for self regulation by academic associations.

Internet, research, automated data collection, trespass, ethics