Providing a Realist Perspective on the eyeGENE Database System

One of the achievements of the eyeGENE Network is a repository of DNA samples of patients with inherited eye diseases and an associated database that tracks key elements of phenotype and genotype information for each patient. Although its database structure serves its direct research needs, eyeGENE has set a goal of enhancing this structure to become increasingly well integrated with medical information standards over time. This goal should be achieved by ensuring semantic interoperability with other information systems but without adopting the incoherencies and inconsistencies found in available biomedical standards. Therefore, eyeGENE’s current pragmatic perspective with focus on data and information, rather than what the information is about, should shift to a realism-based perspective that includes also the portion of reality described, and the competing opinions that clinicians may hold about it. An analysis of eyeGENE’s database structure and user interfaces suggests that such a transition is possible indeed

Citizen Science 2.0 : Data Management Principles to Harness the Power of the Crowd

Citizen science refers to voluntary participation by the general public in scientific endeavors. Although citizen science has a long tradition, the rise of online communities and user-generated web content has the potential to greatly expand its scope and contributions. Citizens spread across a large area will collect more information than an individual researcher can. Because citizen scientists tend to make observations about areas they know well, data are likely to be very detailed. Although the potential for engaging citizen scientists is extensive, there are challenges as well. In this paper we consider one such challenge – creating an environment in which non-experts in a scientific domain can provide appropriate and accurate data regarding their observations. We describe the problem in the context of a research project that includes the development of a website to collect citizen-generated data on the distribution of plants and animals in a geographic region. We propose an approach that can improve the quantity and quality of data collected in such projects by organizing data using instance-based data structures. Potential implications of this approach are discussed and plans for future research to validate the design are described

Referent tracking for corporate memories

For corporate memory and enterprise ontology systems to be maximally useful, they must be freed from certain barriers placed around them by traditional knowledge management paradigms. This means, above all, that they must mirror more faithfully those portions of reality which are salient to the workings of the enterprise, including the changes that occur with the passage of time. The purpose of this chapter is to demonstrate how theories based on philosophical realism can contribute to this objective. We discuss how realism-based ontologies (capturing what is generic) combined with referent tracking (capturing what is specific) can play a key role in building the robust and useful corporate memories of the future

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

Ontological clarity and comprehension in health data models

Conceptual modeling forms an important part of systems analysis. If this is done incorrectly or incompletely, there can be serious implications for the resultant system, specifically in terms of rework and useability. One approach to improving the conceptual modelling process is to evaluate how well the model represents reality. Emergence of the Bunge-Wand-Weber (BWW) ontological model introduced a platform to classify and compare the grammar of conceptual modelling languages. This work applies the BWW theory to a real world example in the health arena. The general practice computing group data model was developed using the Barker Entity Relationship Modelling technique. We describe an experiment, grounded in ontological theory, which evaluates how well the GPCG data model is understood by domain experts. The results show that with the exception of the use of entities to represent events, the raw model is better understood by domain expert

A FOUNDATION FOR OPEN INFORMATION ENVIRONMENTS

Traditionally, information systems were developed within organizations for use by known audiences for known purposes. Advances in information technology have changed this landscape dramatically. The reach of information systems frequntly extends beyond organizational boundaries for use by unknown audiences and for purposes not originally anticipated. Individuals and informal communities can generate and use information in ways previously restricted to formal organizations. We term applications with these characteristics open information environments (OIEs). OIEs are marked by diversity of information available, flexibility in accommodating new sources, users and uses, and information management with minimal controls on structure, content, and access. This creates opportunities to generate new information and use it in unexpected ways. However, OIEs also come with challenges in managing the semantic diversity, flexibility of use, and information quality issus arising from the range of users and lack of controls. In this paper, we propose a set of principles for managing OIEs effectively. We outline a research program to examine the potential of OIEs, the challenges they present, and how to design OIEs to realize the benefits while mitigating the challenges. We highlight our ongoing research in this area, and conclude with a call for more research on this important phenomenon

A Survey of Cognitive Theories to Support Data Integration

Business intelligence applications are being increasingly used to facilitate managerial insight and maintain competitiveness.These applications rely on the availability of integrated data from multiple data sources, making database integration anincreasingly important task. A central step in the process of data integration is schema matching, the identification of similarelements in the two databases. While a number of approaches have been proposed, the majority of schema matchingtechniques are based on ad-hoc heuristics, instead of an established theoretical foundation. The absence of a theoreticalfoundation makes it difficult to explain and improve schema matching process. This research surveys current cognitivetheories of similarity and demonstrates their application to the problem of schema matching. Better integration techniqueswill benefit business intelligence applications and can thereby contribute to business value

More Enduring Questions in Cognitive IS Research

In the April 2012 issue of the Journal of the Association for Information Systems, Michael Davern, Teresa Shaft, and Dov Te’eni published an article titled “Cognition Matters: Enduring Questions in IS Research”. Their paper reviewed much of the history of cognitive research in the IS discipline, especially that related to human-computer interaction and decision support systems. While we believe their article is excellent in many respects, we also believe that it omitted a great deal of the most basic cognitive research performed in the IS domain over the past 10-15 years, especially work in the area of systems analysis and design. Our purpose in this paper is to supplement the work of Davern et al. by discussing much of this recent work. We use two theoretical lenses to organize our review: basic cognition and behavioral decision-making research. Our review provides many illustrations of IS research in these areas, including memory and categorization (basic cognition) and heuristics and biases (behavioral decision making). The result, we believe, is a fuller picture of the breadth of cognition-based work in the IS discipline in general and systems analysis and design in particular. The paper provides further evidence of the importance of cognitive research in IS and suggests additional enduring questions for future investigations

Supporting Database Designers in Entity-Relationship Modeling: An Ontology- Based Approach

Database design has long been recognized as a difficult problem, requiring a great deal of skill on the part of the designer. Research has been carried out that provides methodologies and rules for creating good designs. There have even been attempts to automate the design process. However, before these can be truly successful, methodologies and tools are needed that can incorporate and use domain knowledge. In this research, a methodology for supporting database design is proposed that makes use of domain-specific knowledge about an application, which is stored in the form of ontologies. The ontologies provide information that is useful in both the creation of new designs and the verification of existing ones. They also capture the constraints of an application domain. A methodology for assisting database design that takes advantage of the ontologies has been implemented in a prototype system. Initial testing of the prototype illustrates that the incorporation and use of ontologies are effective in creating database design