In textual modeling, models are created through an intermediate parsing step which maps textual representations to abstract model structures. Therefore, the identify of elements is not stable across different versions of the same model. Existing model differencing algorithms, therefore, cannot be applied directly because they need to identify model elements across versions. In this paper we present Textual Model Diff (tmdiff), a technique to support model differencing for textual languages. tmdiff requires origin tracking during text-to-model mapping to trace model elements back to the symbolic names that define them in the textual representation. Based on textual alignment of those names, tmdiff can then determine which elements are the same across revisions, and which are added or removed. As a result, tmdiff brings the benefits of model differencing to textual languages.
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Purpose – To analyse common metaphors used in the intellectual capital (IC) and knowledge management literatures to conceptualise knowledge, in order to study the nature of the intellectual capital concept. Design/methodology/approach – A textual analysis methodology is used to analyse texts from The Knowledge-Creating Company by Nonaka and Takeuchi, Working Knowledge by Davenport and Prusak and “Brainpower” by Stewart, in order to identify underlying metaphors. Findings – Over 95 per cent of the statements about knowledge identified are based on some kind of metaphor. The two dominant metaphors that form the basis for the concept of intellectual capital are “knowledge as a resource” and “knowledge as capital”. Research limitations/implications – Metaphors highlight certain characteristics and ignore others, so the IC community should ask itself what characteristics of knowledge the “knowledge as a resource” and “knowledge as capital” metaphors ignore. Practical implications – Knowledge has no referent in the real world and requires metaphor to be defined, conceptualised, and acted upon. When using such metaphors we should become aware of their limitations as they steer us in certain directions and this may happen unconsciously. The paper concludes by asking whether we need new metaphors to better understand the mechanisms of the knowledge economy, hence allowing us to potentially change some of the more negative structural features of contemporary society. Originality/value – This paper is the first to highlight that intellectual capital is a metaphor and that the metaphorical nature of the concept has far reaching consequences.
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Metaphors are at the basis of our understanding of reality. Using the theory of metaphor developed by Lakoff and Johnson (1980, 1999) this paper analyses common metaphors used in the intellectual capital and knowledge management literatures. An analysis of key works by Davenport & Prusak (2000), Nonaka & Takeuchi (1995), and Stewart (1991) suggests that at least 95 percent of all statements about either knowledge or intellectual capital are based on metaphors. The paper analyses the two metaphors that form the basis for the concept of intellectual capital: ‘Knowledge as a Resource’ and ‘Knowledge as Capital’, both of which derive their foundations from the industrial age. The paper goes into some of the implications of these findings for the theory and practice of intellectual capital. Common metaphors used in conceptualising abstract phenomena in traditional management practices unconsciously reinforce the established social order. The paper concludes by asking whether we need new metaphors to better understand the mechanisms of the knowledge economy, hence allowing us to potentially change some of the more negative structural features of contemporary society.
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Within the food industry there is a need to be able to rapidly react to changing regulatory requirements and consumer preferences by adjusting recipes, processes, and products. A good knowledge of the properties of food ingredients is crucial in this process. Currently this knowledge is available in scattered heterogeneous resources such as scientific peer-reviewed articles, databases, recipes, food blogs as well as in the experience of food-experts. This prevents, in practice, the efficient integration and use of this knowledge, leading to inefficiency and missed opportunities. In this project we will build a structured database of properties of food ingredients, focusing in particular on the taste and texture properties. By large-scale collection and text mining on a large number of textual resources, a comprehensive data set on ingredient properties will be created, along with knowledge on the relationships between these ingredients. This database will then be used for to find new potential applications for healthy and taste enhancing ingredient combinations by network-based discovery methods and artificial intelligence algorithms will be used. A concrete focus will be on application questions formulated by the industrial partners. The resulting hypothesis will be validated in a real life setting at the premises of the industrial partners. The deliverables of this project will be: - A reusable open-access ingredient database that is accessible via a user-friendly web portal - A set of state-of-the-art mining algorithms that can address a wide variety of industry driven use cases - Novel product formulations that can be further developed for the consumer and business2business market
In this project we will build a structured database of properties of food ingredients, focusing in particular on the taste and texture properties. By large-scale collection and text mining on a large number of textual resources, a comprehensive data set on ingredient properties will be created, along with knowledge on the relationships between these ingredients. This database will then be used for to find new potential applications for healthy and taste enhancing ingredient combinations by network-based discovery methods and artificial intelligence algorithms will be used. A concrete focus will be on application questions formulated by the industrial partners. The resulting hypothesis will be validated in a real life setting at the premises of the industrial partners.The deliverables of this project will be:• A reusable open-access ingredient database that is accessible via a user-friendly web portal• A set of state-of-the-art mining algorithms that can address a wide variety of industry driven use cases• Novel product formulations that can be further developed for the consumer and business2business market
The precarity in the cultural sector became exposed during the COVID-19 pandemic. With the lockdowns, the sources of income for cultural venues and cultural workers vanished overnight, intensifying an already challenging labour market. Particularly freelance cultural workers were hit hard. While the immediate shock of the pandemic on the cultural sector has been well documented, the effects on the sector in the aftermath of the pandemic are still to be revealed and repaired. This project tackles these issues by zooming in on the case of the performing arts scene in Groningen. This scene constitutes the part of the cultural sector that was affected the most by the lockdowns. Currently, venues and event organizers in Groningen lack qualified freelance staff as many left the industry during the pandemic. At the same time, self-employed cultural workers find it difficult to generate sufficient incomes and develop sustainable careers in the city. The municipality is eager to support the industry, including freelancers, but is unsure about how best to do so. With a consortium composed of the university, the municipality, a knowledge organisation specialised in cultural entrepreneurship, and a network for creative freelancers in the North of the Netherlands the project is well-equipped to reach its two-fold aims of investigating this current situation and coming up with suggestions for solutions. The core component of the project is an interview study with three groups of self-employed cultural freelancers: experienced production staff, experienced performers, and nascent freelancers (both production staff and performers). Based on data from this study, the project provides a multifaceted picture of the cultural ecosystem in Groningen, highlighting how this system is experienced. This establishes a solid foundation for staging discussions on working conditions in the sector, enabling the project to eventually conclude with recommendations on how to improve the situation.
