A Software-based Knowledge Management System Using Narrative Texts

Technical and professional communicators have in recent research been challenged to make significant contributions to the field of knowledge management, and to learn or create the new technologies allowing them to do so. The purpose of this dissertation is to make such a combined theoretical and applied contribution from the context of the emerging discipline of Texts and Technology. This dissertation explores the field of knowledge management (KM), particularly its relationship to the related study of artificial intelligence (AI), and then recommends a KM software application based on the principles of narratology and narrative information exchange. The focus of knowledge is shifted from the reductive approach of data and information to a holistic approach of meaning and the way people make sense of complex events as experiences expressed in stories. Such an analysis requires a discussion of the evolution of intelligent systems and narrative theory as well as an examination of existing computerized and non-computerized storytelling systems. After a thorough discussion of these issues, an original software program that is used to collect, analyze, and distribute thematic stories within any hierarchical organization is modeled, exemplified, and explained in detail

Can we forecast conflict? A framework for forecasting global human societal behavior using latent narrative indicators

The ability to successfully forecast impending societal unrest, from riots and protests to assassinations and coups, would fundamentally transform the ability of nations to proactively address instability around the world, intervening before unrest accelerates to conflict or prepositioning assets to enhance preventive activity. It would also enhance the ability of social scientists to quantitatively study the underpinnings of how and why grievances transition from agitated individuals to population-scale physical unrest. Recognizing this potential, the US government has funded research on “conflict early warning” and conflict forecasting for more than 40 years and current unclassified approaches incorporate nearly every imaginable type of data from telephone call records to traffic signals, tribal and cultural linkages to satellite imagery. Yet, current approaches have yielded poor outcomes: one recent study showed that the top models of civil war onset miss 90% of the cases they supposedly explain. At the same time, emerging work in the economics disciplines is finding that new approaches, especially those based on latent linguistic indicators, can offer significant predictive power of future physical behavior. The information environment around us records not just factual information, but also a rich array of cultural and contextual influences that offer a window into national consciousness. A growing body of literature has shown that measuring the linguistic dimensions of this real–time consciousness can accurately forecast many broad social behaviors, ranging from box office sales to the stock market itself. In fact, the United States intelligence community believes so strongly in the ability of surface-level indicators to forecast future physical unrest more successfully than current approaches, it now has an entire program devoted to such “Open Source Indicators.” Yet, few studies have explored the application of these methods to the forecasting of non-economic human societal behavior and have primarily focused on large-bore events such as militarized disputes, epidemics, and regime change. One of the reasons for this is the lack of high-resolution cross-national longitudinal data on societal conflict equivalent to the daily indicators available in economics research. This dissertation therefore presents a novel framework for evaluating these new classes of latent-based forecasting measures on high-resolution geographically-enriched quantitative databases of human behavior. To demonstrate this framework, an archive of 4.7 million news articles totaling 1.3 billion words, consisting of the entirety of international news coverage from Agence France Presse, the Associated Press, and Xinhua over the last 30 years, is used to construct a database of more than 29 million global events in over 300 categories using the TABARI coding system and CAMEO event taxonomy, resulting the largest event database created in the academic literature. The framework is then applied to examine the hypothesis of latent forecasting as a classification problem, demonstrating the ability of a simple example-based classifier to not only return potentially actionable forecasts from latent discourse indicators, but to quantitatively model the topical traces of the metanarratives that underlie them. The results of this dissertation demonstrate that this new framework provides a powerful new evaluative environment for exploring the emerging class of latent indicators and modeling approaches and that even rudimentary classification-based models may have significant forecasting potential

Sensor web geoprocessing on the grid

Recent standardisation initiatives in the fields of grid computing and geospatial sensor middleware provide an exciting opportunity for the composition of large scale geospatial monitoring and prediction systems from existing components. Sensor middleware standards are paving the way for the emerging sensor web which is envisioned to make millions of geospatial sensors and their data publicly accessible by providing discovery, task and query functionality over the internet. In a similar fashion, concurrent development is taking place in the field of grid computing whereby the virtualisation of computational and data storage resources using middleware abstraction provides a framework to share computing resources. Sensor web and grid computing share a common vision of world-wide connectivity and in their current form they are both realised using web services as the underlying technological framework. The integration of sensor web and grid computing middleware using open standards is expected to facilitate interoperability and scalability in near real-time geoprocessing systems. The aim of this thesis is to develop an appropriate conceptual and practical framework in which open standards in grid computing, sensor web and geospatial web services can be combined as a technological basis for the monitoring and prediction of geospatial phenomena in the earth systems domain, to facilitate real-time decision support. The primary topic of interest is how real-time sensor data can be processed on a grid computing architecture. This is addressed by creating a simple typology of real-time geoprocessing operations with respect to grid computing architectures. A geoprocessing system exemplar of each geoprocessing operation in the typology is implemented using contemporary tools and techniques which provides a basis from which to validate the standards frameworks and highlight issues of scalability and interoperability. It was found that it is possible to combine standardised web services from each of these aforementioned domains despite issues of interoperability resulting from differences in web service style and security between specifications. A novel integration method for the continuous processing of a sensor observation stream is suggested in which a perpetual processing job is submitted as a single continuous compute job. Although this method was found to be successful two key challenges remain; a mechanism for consistently scheduling real-time jobs within an acceptable time-frame must be devised and the tradeoff between efficient grid resource utilisation and processing latency must be balanced. The lack of actual implementations of distributed geoprocessing systems built using sensor web and grid computing has hindered the development of standards, tools and frameworks in this area. This work provides a contribution to the small number of existing implementations in this field by identifying potential workflow bottlenecks in such systems and gaps in the existing specifications. Furthermore it sets out a typology of real-time geoprocessing operations that are anticipated to facilitate the development of real-time geoprocessing software.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research Council (EPSRC) : School of Civil Engineering & Geosciences, Newcastle UniversityGBUnited Kingdo

The Invention of Good Games: Understanding Learning Design in Commercial Videogames

This work sought to help inform the design of educational digital games by the studying the design of successful commercial videogames. The main thesis question was: How does a commercially and critically successful modern video game support the learning that players must accomplish in order to succeed in the game (i.e. get to the end or win)? This work takes a two-pronged approach to supporting the main argument, which is that the reason we can learn about designing educational games by studying commercial games is that people already learn from games and the best ones are already quite effective at teaching players what they need to learn in order to succeed in the game. The first part of the research establishes a foundation for the argument, namely that accepted pedagogy can be found in existing commercial games. The second part of the work proposes new methods for analysing games that can uncover mechanisms used to support learning in games which can be employed even if those games were not originally designed as educational objects. In order to support the claim that ‘good’ commercial videogames already embody elements of sound pedagogy an explicit connection is made between game design and formally accepted theory and models in teaching and learning. During this phase of the work a significant concern was raised regarding the classification of games as ‘good’, so a new methodology using Borda Counts was devised and tested that combines various disjoint subjective reviews and rankings from disparate sources in non-trivial manner that accounts for relative standings. Complementary to that was a meta-analysis of the criteria used to select games chosen as subjects of study as reported by researchers. Then, several games were chosen using this new ranking method and analysed using another new methodology that was designed for this work, called Instructional Ethology. This is a new methodology for game design deconstruction and analysis that would allows the extraction of information about mechanisms used to support learning. This methodology combines behavioural and structural analysis to examine how commercial games support learning by examining the game itself from the perspective of what the game does. Further, this methodology can be applied to the analysis of any software system and offers a new approach to studying any interactive software. The results of the present study offered new insights into how several highly successful commercial games support players while they learn what they must learn in order to succeed in those games. A new design model was proposed, known as the 'Magic Bullet' that allows designers to visualize the relative proportions of potential learning in a game to assess the potential of a design

Bowdoin Orient v.135, no.1-25 (2005-2006)

https://digitalcommons.bowdoin.edu/bowdoinorient-2000s/1006/thumbnail.jp

Environmentally sensitive printmaking: a framework for safe practice.

This research is concerned with establishing a rationale which will link safe printmaking practices with artists' individual and sustainable creative practices, by investigating the preconception that printmaking practices may be limited by adopting such an environmentally sensitive approach. This has been investigated through a practice-led approach, which implicitly involves the researchers' professional practice as a visual artist printmaker. The cross disciplinary nature of this practice-led research has established that diverse and non-text based sources be included in the literature review. The resulting contextual review established the evolutionary nature of printmaking practices, the role played by individual artists perceptions of risk, and the limited ability of available literature to adequately link evolving and didactic creative practices to emergent boundaries established by environmental and occupational health and safety legislative criteria. There was evidently no theoretical framework for linking these apparently divergent criteria. The multi-disciplinary and practice-led context i. e. the research was generated by practice and carried out through practice, determined the range of methods employed: questionnaire, quantitative tests of materials; participation in, and initiation of collaborative case studies; documenting workshop practice and visual development of printed art works; and exhibition for peer review. These multiple methods and their complex interrelationships were visualised as a system of consequential actions, in order to externalise possible alternative actions and choices made by the researcher in response to this research. Analysis of these methods revealed that: the collaborative case studies and the researcher's own visual and practical response, established that a systematic revaluation of practice could link the idiosyncratic and individual creative practices to the use and selection of nonhazardous practices, which did respond to objective occupational health and safety rationale. This revealed the extent to which a systematic re-evaluation of 'established practices' may be synthesised into the working practice of the researcher and lead to the diversification of that practice - visually and practically. This process has resulted in the generation of a body of printed art works which implicitly embodied the hypothesis developed in this research; the development of a electronic database or 'morphological framework', which initiates a sequential examination of process at a structural level, collating, comparing and promoting previously un-considered alternatives based on a heterarchical model of risk. This process has offered tangible means of visualising the generative processes involved in making prints. The 'morphological framework' has implicitly linked the researcher's printmaking to a sustainable and environmentally sensitive creative practice, which is methodologically transparent and procedurally transferable