Implementing Lightweight Conceptual Modeling for User-Generated Content Prototype Roman Lukyanenko Memorial University of Newfoundland
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Jeffrey Parsons Memorial University of Newfoundland
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Background and Motivation A growing trend in organizations is to use user-generated content - digital information (e.g., forum posts, tags, product reviews) produced by members of the general public, rather than by employees. This fuels diffusion of crowdsourcing - wherein an organization calls upon general public to produce data for some internal purpose. A major challenge in effectively harnessing user-generated content is conceptual modeling. Conceptual models are used in information systems (IS) development to represent relevant knowledge about the application domain to guide IS design, promote domain understanding and support communication. Conceptual modeling is traditionally a user-driven activity. Users (or stakeholders) provide requirements, supply analysts with subject matter expertise, and evaluate and/or approve conceptual models. In contrast to more traditional corporate domains, in crowdsourcing some requirements and domain knowledge may originate from potential decision makers (i.e., representatives of the organization commissioning the project), but the actual data are provided by often anonymous users. As modelers are unable to fully capture the varying perspectives of contributors, it is difficult to design appropriate structures (e.g., relations) that are congruent with views of users and sufficiently represent the domain of interest (see Lukyanenko and Parsons 2012).
Lightweight Conceptual Modeling We contend that, to support IS development in crowdsourcing, conceptual modeling needs to be embody general, rather than domain-specific, assumptions about the organization of reality. The resulting “lightweight” conceptual models are domain- and observer- invariant. Therefore, the lack of consensus among user views, emergent perspectives, and ill-defined domain boundaries can be represented. These assumptions can be grounded in general ontologies that specify what exists in the world. To provide a proof-of-concept and empirically evaluate the “lightweight modeling” approach, we developed a real crowdsourcing IS, NLNature (www.nlnature.com) that maps biodiversity of Newfoundland and Labrador using sightings of plants and animals provided by ordinary people. This data are then made available for researchers in various disciplines (e.g., biology). NLNature adopted an instance-based meta-model assumed to be broadly applicable across domains (Parsons and Wand 2000). The meta-model uses instances, attributes, and classes as primitive constructs. Consequently, contributors do not need to classify instances of interest (e.g., animals, lichens, geological forms) as would be required under a traditional design. Instead, users can provide attributes of the observed instances. The demonstration of NLNature as an exemplar of "lightweight conceptual modeling" presents an opportunity to consider alternative approaches to traditional domain-specific conceptual modeling. Using "lightweight conceptual modeling" it should be possible to support development in a variety of emerging domains (e.g., crowdsourcing, social media, flexible organizational settings, telemedicine, Semantic Web).
References Lukyanenko, R. and Parsons, J. 2012. “Conceptual modeling principles for Crowdsourcing”, in CIKM Workshop on Multimodal Crowd Sensing, ACM, pp. 3-6. Parsons, J. and Wand, Y. 2000. "Emancipating Instances from the Tyranny of Classes in Information Modeling," ACM Transactions on Database Systems (25), pp. 228–268.
23rd Workshop on Information Technology and Systems, Milan 2013
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