Modeling, Predicting and Capturing Human Mobility

Realistic models of human mobility are critical for modern day applications, specifically for recommendation systems, resource planning and process optimization domains. Given the rapid proliferation of mobile devices equipped with Internet connectivity and GPS functionality today, aggregating large sums of individual geolocation data is feasible. The thesis focuses on methodologies to facilitate data-driven mobility modeling by drawing parallels between the inherent nature of mobility trajectories, statistical physics and information theory. On the applied side, the thesis contributions lie in leveraging the formulated mobility models to construct prediction workflows by adopting a privacy-by-design perspective. This enables end users to derive utility from location-based services while preserving their location privacy. Finally, the thesis presents several approaches to generate large-scale synthetic mobility datasets by applying machine learning approaches to facilitate experimental reproducibility

From Social Data Mining to Forecasting Socio-Economic Crisis

Socio-economic data mining has a great potential in terms of gaining a better understanding of problems that our economy and society are facing, such as financial instability, shortages of resources, or conflicts. Without large-scale data mining, progress in these areas seems hard or impossible. Therefore, a suitable, distributed data mining infrastructure and research centers should be built in Europe. It also appears appropriate to build a network of Crisis Observatories. They can be imagined as laboratories devoted to the gathering and processing of enormous volumes of data on both natural systems such as the Earth and its ecosystem, as well as on human techno-socio-economic systems, so as to gain early warnings of impending events. Reality mining provides the chance to adapt more quickly and more accurately to changing situations. Further opportunities arise by individually customized services, which however should be provided in a privacy-respecting way. This requires the development of novel ICT (such as a self- organizing Web), but most likely new legal regulations and suitable institutions as well. As long as such regulations are lacking on a world-wide scale, it is in the public interest that scientists explore what can be done with the huge data available. Big data do have the potential to change or even threaten democratic societies. The same applies to sudden and large-scale failures of ICT systems. Therefore, dealing with data must be done with a large degree of responsibility and care. Self-interests of individuals, companies or institutions have limits, where the public interest is affected, and public interest is not a sufficient justification to violate human rights of individuals. Privacy is a high good, as confidentiality is, and damaging it would have serious side effects for society.Comment: 65 pages, 1 figure, Visioneer White Paper, see http://www.visioneer.ethz.c

Alter ego, state of the art on user profiling: an overview of the most relevant organisational and behavioural aspects regarding User Profiling.

This report gives an overview of the most relevant organisational and\ud behavioural aspects regarding user profiling. It discusses not only the\ud most important aims of user profiling from both an organisation’s as\ud well as a user’s perspective, it will also discuss organisational motives\ud and barriers for user profiling and the most important conditions for\ud the success of user profiling. Finally recommendations are made and\ud suggestions for further research are given

The Design and Evaluation of Interactivities in a Digital Library

The US National Science Foundation has established a program to create a National Science, Mathematics, Engineering and Technology Education Digital Library (NSDL). One of the subsidiary NSDL libraries under development is the National Civil Engineering Educational Resources Library (NCERL). The first phase of NCERL is the creation and collection of digital resources in three areas of civil engineering—geotechnical (soil), rock, and water engineering (GROW). The concept of interactivities guides the design, development, and evaluation efforts of the GROW digital collection. This article describes the salient features of GROW, defines and discusses interactivities as an emerging, integral part of teaching and learning in civil engineering education. Interactivities take place at three distinct levels: the information resource, the collection, and the context. Very simply, the concept of interactivities can be defined as the emphasis on structured representations of interactive multimedia resources. Additionally, resources are designed with rich learning tasks and organized in pedagogical collections supplemented with contextual information. Preliminary evaluation of GROW-NCERL using interactivities is briefly described

Feature Repurposing and Cognitive Efficiency in Financial Trading Systems

Many IS research domains such as cognitive fit and information overload assume that the user selects from a fixed menu of IS features to accomplish goals. IS pliability researchers offer a new perspective by recognizing the users’ discretion in altering or creating new features. While this IS pliability research has important implications, it is currently descriptive rather than explanatory. To explore IS pliability in the form of causal propositions, we examine data from a Fortune 1000 brokerage firm where some traders created what the IS developers considered superfluous “extra” accounts. Levering insights from the referent theory of cognitive niche construction, we propose that these multiple accounts align the representation of information presented with the users’ conceptual trading strategies. This alignment in turn facilitates trading research through the reduction of task switching and the learning benefits supported by category labels. The empirical analysis is consistent with these propositions

Scaled Agile Framework Meets Traditional Management – A Case of a Financial Services Provider

Inspired by the success of agile practices in small teams, organizations seek to achieve agility at scale, leading to large-scale agile transformations. Several frameworks have been developed to guide organizations through this process. While multiple challenges for adopting scaled agile frameworks have already been identified, research on the interplay between traditional management approaches and scaled agile frameworks is scarce. We conduct an in-depth exploratory case study with a German financial services provider to identify tensions that arise when applying a scaled agile framework in a non-agile environment. As a result, we derive 13 tensions along with three areas: goal-setting, planning, and reporting. Thereby, we advance the understanding of tensions within large-scale agile transformations and provide a foundation for future research on scaled agile practices in traditional organizations. Further, we provide insights for managers to ensure the successful application of scaled agile frameworks