Transforming enterprise ontologies into SBVR formalizations

In 2007 the Object Management Group (OMG) adopted the Se- mantics of Business Vocabulary and Business Rules (SBVR) specification. The languages specified by this specification must be used to create business vocab- ularies and business rules of all kinds of business activities of all kinds of or- ganizations. This paper describes and demonstrates how enterprise ontologies can be transformed into SBVR formalizations

Querying Instances – A Protocol Analysis Study

The instance-based paradigm – introduced as an alternative to traditional class-based database management methods – does not require imposing a well-defined schema over data, nor does it entail central control and planning. As a consequence, it supports information requirements agility, enables collection of higher quality data, and reduces the schema and database operation problems associated with traditional methods. This study investigates the ability of content-consumers to use instance-based representations effectively for information retrieval purposes. A visual representation of the instance-based data was created and empirically evaluated with 12 subjects using protocol analysis. Results show that instance-based users were able to retrieve the required information more accurately compared to users of the traditional representation. From a cognitive point of view, instance-based users were more efficient than class-based users – they experienced fewer breakdowns in their problem solving process and, when breakdowns occurred, were more successful in recovering from them

There were Times it was Needed to Motivate Knowledge Sharing, is it now Time to Protect?

What will be the point of equilibrium between sharing and protecting? This essay analyzes the motivations to share knowledge and the protection needs of this knowledge from the analysis of 28 articles published in the periodical MIS Quarterly between 2005 and 2017. The barriers and motivations for sharing the knowledge have been studied to then encourage sharing. Factors such as technology development, dissemination of social media, among others, have influenced the sharing behavior of people. However, more recent studies show organizations’ concerns about protecting knowledge because of the risk of strategic losses. The results presented in this study suggest that the sharing of knowledge and its protection are equally critical and that the effective management of this knowledge is necessary

Effectiveness of Domain Ontologies to Facilitate Shared Understanding and Cross-Understanding

Shared cognition constructs such as shared understanding and cross-understanding are important factors in team performance. Although research has focused on understanding the effects of these constructs, little emphasis has been placed on improving their development. In Information Systems and related fields shared understanding of a domain is said to be facilitated by the use of a domain ontology, however there is a lack of empirical evidence to support this claim. Accordingly, in this research-in-progress paper, we report our efforts to develop a deep understanding of the benefits of domain ontology use at the group level. Specifically, we propose a model that theorizes the relationships between domain ontology use and the development of shared understanding and cross-understanding of domains. Additionally, we provide details of operationalization and empirical validation of our model, and the current state of this research

Customising agent based analysis towards analysis of disaster management knowledge

© 2016 Dedi Iskandar Inan, Ghassan Beydoun and Simon Opper. In developed countries such as Australia, for recurring disasters (e.g. floods), there are dedicated document repositories of Disaster Management Plans (DISPLANs), and supporting doctrine and processes that are used to prepare organisations and communities for disasters. They are maintained on an ongoing cyclical basis and form a key information source for community education, engagement and awareness programme in the preparation for and mitigation of disasters. DISPLANS, generally in semi-structured text document format, are then accessed and activated during the response and recovery to incidents to coordinate emergency service and community safety actions. However, accessing the appropriate plan and the specific knowledge within the text document from across its conceptual areas in a timely manner and sharing activities between stakeholders requires intimate domain knowledge of the plan contents and its development. This paper describes progress on an ongoing project with NSW State Emergency Service (NSW SES) to convert DISPLANs into a collection of knowledge units that can be stored in a unified repository with the goal to form the basis of a future knowledge sharing capability. All Australian emergency services covering a wide range of hazards develop DISPLANs of various structure and intent, in general the plans are created as instances of a template, for example those which are developed centrally by the NSW and Victorian SES’s State planning policies. In this paper, we illustrate how by using selected templates as part of an elaborate agent-based process, we can apply agent-oriented analysis more efficiently to convert extant DISPLANs into a centralised repository. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). The work is illustrated using DISPLANs along the flood-prone Murrumbidgee River in central NSW

ARTIFACT EVALUATION IN INFORMATION SYSTEMS DESIGN-SCIENCE RESEARCH – A HOLISTIC VIEW

Design science in Information Systems (IS) research pertains to the creation of artifacts to solve reallife problems. Research on IS artifact evaluation remains at an early stage. In the design-science research literature, evaluation criteria are presented in a fragmented or incomplete manner. This paper addresses the following research questions: which criteria are proposed in the literature to evaluate IS artifacts? Which ones are actually used in published research? How can we structure these criteria? Finally, which evaluation methods emerge as generic means to assess IS artifacts? The artifact resulting from our research comprises three main components: a hierarchy of evaluation criteria for IS artifacts organized according to the dimensions of a system (goal, environment, structure, activity, and evolution), a model providing a high-level abstraction of evaluation methods, and finally, a set of generic evaluation methods which are instantiations of this model. These methods result from an inductive study of twenty-six recently published papers

Towards knowledge sharing in disaster management: An agent oriented knowledge analysis framework

Disaster Management (DM) is a complex set of interrelated activities. The activities are often knowledge intensive and time sensitive. Sharing the required knowledge timely is critical for DM. In developed countries, for recurring disasters (e.g. floods), there are dedicated document repositories of Disaster Management Plans (DMP) that can be accessed as needs arise. However, accessing the appropriate plan in a timely manner and sharing activities between plans often requires domain knowledge and intimate knowledge of the plans in the first place. In this paper, we introduce an agent-based knowledge analysis method to convert DMPs into a collection of knowledge units that can be stored into a unified repository. The repository of DM actions then enables the mixing and matching knowledge between different plans. The repository is structured as a layered abstraction according to Meta Object Facility (MOF). We use the flood management plans used by SES (State Emergency Service), an authoritative DM agency in NSW (New State Wales) State of Australia to illustrate and give a preliminary validation of the approach. It is illustrated using DMPs along the flood prone Murrumbidgee River in central NSW

How quickly do we learn conceptual models?

In organizations, conceptual models are used for understanding domain concepts. Learning the domain from models is crucial for the analysis and design of information systems that are intended to support the domain. Past research has proposed theories to structure conceptual models in order to improve learning. It has, however, never been investigated how quickly domain knowledge is acquired when using theory-guided conceptual models. Based on theoretical arguments, we hypothesize that theory-guided conceptual models expedite the initial stages of learning. Using the REA ontology pattern as an example of theoretical guidance, we show in a laboratory experiment how an eye-tracking procedure can be used to investigate the effect of using theory-guided models on the speed of learning. Whereas our experiment shows positive effects on both outcome and speed of learning in the initial stages of learning, the real contribution of our paper is methodological, i.e. an eye-tracking procedure to observe the process of learning from conceptual models

A Novel Design Science Approach for Integrating Chinese User-Generated Content in Non-Chinese Market Intelligence

Market research has long relied on reactive means of data gathering, such as questionnaires or focus groups. With the wide-spread use of social media, millions of comments about customer opinions and feedback regarding products and brands are available. However, before using this ‘wisdom of the crowd’ as a source for marketing research, several challenges have to be tackled: the sheer volume of posts, their unstructured format, and the dozens of different languages used on the internet. All of them make automated usage of this data challenging. In this paper, we draw on dashboard design principles and follow a design science research approach to develop a framework for search, integration, and analysis of cross-language user-generated content. With ‘MarketMiner’, we implement the framework in the automotive industry by analyzing Chinese auto forums. The results are promising in that MarketMiner can dramatically improve utilization of foreign-language social media content for market intelligence purposes