Browse by Tags: wais semiar

Abstract: The talk will provide a review of the digital landscape, along with an outline of the affordances of digital technologies. It will focus on networking and open practices and will argue that practitioners need new digital literacies to harness the potential of digital technologies. It will argue that the teachers role is central and that they need a range of Continuing Professional Practice. It will describe a new project at DCU, #OpenTeach, which will develop a course for our 90 part-time tutors to help them design and facilitate online courses. It will argue that new approaches to Learning Design are needed and will describe a number of recent frameworks. It will conclude with a set of final reflections drawing on a recent EU-commissioned report. Bio: Gráinne Conole is a professor and Head of Open Education in the National Institute for Digital Learning at Dublin City University. She has worked at the Universities of Bath Spa, Bristol, Leicester, OU and Southampton. Her research interests are on the use of technologies for learning, including Open Educational Resources (OER) and Massive Open Online Courses (MOOCs), new approaches to designing for learning, e-pedagogies, and social media. She has an HEA National Teaching Fellowship and fellow of EDEN and ASCILITE. She has published and presented over 1000 talks, workshops and articles. See http://e4innovation.co.uk for more details.

Abstract: Over the past couple of years, there has been increasing interest in applying the latest advances in machine learning to creative projects in art and design. From DeepDream and style transfer to a GAN-generated painting selling for $430,000 at auction, AI art has moved beyond the world of research and academia and become a trend in its own right. Meanwhile, the contemporary art world's fascination with the social impact of facial recognition, recommendation systems and deep fakes has encouraged artists to explore AI critically as subject matter. This talk will give an overview of how artists and technologists are using and thinking about machine learning, its creative potential and societal impact. Bio: Luba Elliott is a curator and researcher specialising in artificial intelligence in the creative industries. She is currently working to educate and engage the broader public about the latest developments in AI art through talks, workshops and exhibitions at venues across the art and technology spectrum including The Photographers’ Gallery, Victoria & Albert Museum, Seoul MediaCity Biennale, Impakt Festival, Leverhulme Centre for the Future of Intelligence, NeurIPS and ECCV. Her Creative AI London meetup community includes 2,300+ members. She has advised organisations including The World Economic Forum, Google and City University on the topic and was featured on the BBC, Forbes and The Guardian. She is a member of the AI council at the British Interactive Media Association. Previously, she worked in startups and venture capital and has a degree in Modern Languages from Cambridge University.

Abstract : It is a work in progress to unleash the potentials of B2C e-Commerce in Indonesia. This study focuses on the millenials' impulse buying as digital buyers of SME in Indonesia. Potential personalisation dimension have been identified. These need further experiment and evaluation. About the Speaker : Dr Betty Purwandari is an academic staff in the Faculty of Computer Science, Universitas Indonesia. She is the course leader of MSc Information Technology at Universitas Indonesia. Her research is on Web Science and e-commerce mainly with SME. She also works on e-participation with the Executive Office of the President, Republic of Indonesia. She did her undergraduate at Universitas Indonesia. Then she got her MSc from UCL as the British Chevening awardee. She did her PhD at the University of Southampton. After she came back to Universitas Indonesia, she was appointed as the university’s Information Technology director. Her professional achievements were recognised by the British Council Indonesia in the 2016 UK Alumni Award.

We're not a particularly healthy culture. Our "normal" practices are not optimised for our wellbeing. From the morning commute to the number of hours we believe we need to put in to complete a task that may itself be unreasonable, to the choices we make about time to prepare food to fit into these constraints - all these operations tend to make us feel forced into treating ourselves as secondary to our jobs. How can data help improve our quality of life? FitBits and AppleWatches highlight the strengths and limits of Things that Count, not the least of which is the rather low uptake of things like FITBITS and apple watches. So once we ask the question about how data might improve quality of life, we may need to add the caveat: pervasively, ubiquitously, in the rich variety of contexts that isn't all about Counting. And once we think about such all seeing all knowing environments, we then need to think about privacy and anonymity. That is: does everything have to be connected to the internet to deliver on a vision of improved quality of life through data? And if there is a Big Ubiquity - should we think about inverting new norms, like how to make personal clouds and personal data stores far more easy to manage - rather than outsourcing so much data and computation? In this short talk, I'd like to consider three scenarios about Going where too few humans have gone before to help others The challenges of qualitative data Supporting privacy and content to motivate thinking about data capture, re-use and re-presentation, and opportunities across ECS for machine learning, AI, infoviz and hci.

Abstract: The Data Observatory (DO) at the Data Science Institute (DSI) in Imperial College (IC) is the largest interactive visualisation facility in Europe, consisting of 64 monitors arranged to give 313 degree surround vision and engagement Opened in November 2015, the DO provides an opportunity for academics and industry to visualise data in a way that uncovers new insights, and promotes the communication of complex data sets and analysis in an immersive and multi-dimensional environment. Designed, built by, and housed within the DSI, the DO enables decision makers to derive new implications and actions from interrogating data sets in an innovative, unique environment. The talk will provide an overview of the DO capabilities and case studies of its use.

Abstract: In Wendy Hall's 2017 AI review, the first recommendation was to create data trusts to encourage data access and data sharing. A number of initiatives are exploring these ideas in concrete contexts, including Elena Simperl's Data Pitch project and the Open Data Institute's work on data innovation. This talk will consider the question in more abstraction, to consider data trusts' function, and how this will determine their form. I will argue that a data trust should work within existing law to provide ethical, architectural and governance support for trustworthy data processing, and I will unpack this in terms of how it might create trust, what architectures might help implement data trusts, and how they relate to the existing law of trusts. Biodata: Kieron O'Hara is an associate professor in the WAIS group of ECS. His research interests are in trust, privacy and the nature of digital modernity. He is a lead in the UKAN network of anonymisation experts. His latest book, The Theory and Practice of Social Machines (with Nigel Shadbolt, Dave De Roure and Wendy Hall) will be published by Springer in March.

The use of music as an aid for improving body and mind has received enormous attention over the last 20 years from a wide range of disciplines, including neuroscience, cognitive science, physical therapy, exercise science, psychological medicine, and pedagogy. It is important to translate insights gained from the scientific study of music, learning, and medicine into real-life applications. Such applications should be delivered widely, effectively, and accurately, harnessing the synergy of sound and music computing (SMC), wearable computing, and cloud computing technologies to promote learning and to facilitate disease prevention, diagnosis, and treatment in both developed countries and resource-poor developing countries. In this talk, I will highlight our recent projects at NUS Sound and Music Computing Lab that are developed to facilitate joyful learning, and motivate physical Rehabilitation. Speaker information WANG Ye is an Associate Professor in the Computer Science Department at the National University of Singapore (NUS) and NUS Graduate School for Integrative Sciences and Engineering (NGS). He established and directed the sound and music computing (SMC) Lab (www.smcnus.org). Before joining NUS he was a member of the technical staff at Nokia Research Center in Tampere, Finland for 9 years. His research interests include sound analysis and music information retrieval (MIR), mobile computing, and cloud computing, and their applications in music edutainment, e-Learning, and e-Health, as well as determining their effectiveness via subjective and objective evaluations. He has served as the general chair of ISMIR2017 (https://ismir2017.smcnus.org/) and TPC co-chair of ICOT2017 (http://www.colips.org/conferences/icot2017/). His most recent projects involve the design and evaluation of systems to support 1) therapeutic gait training using Rhythmic Auditory Stimulation (RAS), 2) auditory training and second language learning.

Abstract: Data is everywhere. Today people are faced with the daunting task of understanding and managing the data created by them, about them, and for them, due to the lack of mechanisms between them and the data. In this talk, I will use some examples in my own research to explain how we can bridge the gap between humans and data through a series of interaction mechanisms. I will first explain how we can use agencies such as recommender systems to help people manage the access to their personal data. I will then explain how data visualisations can be used to help people extract better insights from their personal data. I will also introduce my on-going work about applying data visualisations to public data to help people make better decisions and, beyond visualisations, telling stories about data. Biodata: Yuchen Zhao is a research fellow at the Web and Internet Science Research Group (WAIS) in the school of Electronic and Computer Science (ECS), the University of Southampton. He received his Ph.D. in computer science from University of St Andrews in 2017. His research aims to understand and address the issues in human data interaction. His previous research focused on understanding privacy issues in personal data and designing agencies to help people solve those issues. His recent research has expanded to apply data visualisations and narrative visualisations to provide better insights, transparency, and engagement in public data.

Feeling drowsy at work? Despite findings that poor indoor air quality causes cognitive performance decline, the average office-worker has no access to information on the quality of air in the room until it becomes poor enough to cause discomfort. In this talk, I discuss our user-centred research from the REFRESH project, which joins the dots between the individual and social factors that affect perception of IAQ, and the human physiological responses to changes in air quality. This involves (1) physiological measurement such as (EEG) to detect the effect of air quality on drowsiness, (2) qualitative methods to understanding the social factors which influence air quality in offices, and (3) designing ambient technology which visualises CO2 of an office- an indicator of indoor air quality. At the end of the talk you will have some actions for how you can detect- and do something about- the air quality of your office; how easily you can incorporate qualitative methods into your research and use technology to understand your users’ needs.

Researchers from the Web and Internet Science group have been exploring hypertexts and computational narrative for nearly two decades. In this seminar we present our most recent work on the Leverhulme Trust funded project StoryPlaces (http://storyplaces.soton.ac.uk/) where we have investigated the poetics and technology associated with location aware narratives. Location Aware Narratives are a type of Strange Hypertext (hypertexts that go beyond traditional node-link models) because location aware stories reflects the physical context of the reader - examples include tour guides where the reader is required to be in a particular location to access certain pages, interactive fiction where location is used to set the tone or backdrop to the drama, or dynamic narrative that changes or responds to the user’s wanderings. The StoryPlaces system is driven by a Sculptural Hypertext engine which models narrative as a state machine and delivers a mobile storytelling experience through a location aware web application. StoryPlaces is based on a general model for location aware narrative called "Canyons, Deltas, Plains" that we have shown to support the structures used in a broad sample of location aware storytelling systems. By working with both student and professional writers we have expanded our knowledge of the common patterns and structures used by authors in location aware narrative, and have begun to see how the structures of the narrative and the topology of the locations involved are intrinsically connected, and that the 'poetics of space' are a fundamental part of this medium. As part of the seminar we will demonstrate the StoryPlaces reader, and show how these patterns have begun to inform the design of our authorship tools.

Abstract: Computational science (also scientific computing) involves the development of models and simulations to understand natural systems answering questions that neither theory nor experiment alone are equipped to answer. Despite the increasing importance of so-called in-silico experiments to the scientific discovery process, state-of-the-art software engineering practices are not fully adopted in computational science. However, software engineering is central to any effort to increase computational science’s software productivity. Among the methods and techniques that software engineering can offer to computational science, I’ll present work model-driven software engineering with domain specific languages and on modular software architectures. For good scientific practice, it is important that research results may properly be checked by reviewers, and possibly be repeated and extended by other researchers. This is of particular interest for "digital science" i.e. for in-silico experiments. In this talk, I’ll discuss some efforts on open science in both, computational science and computer science. Reference: A. Johanson, W. Hasselbring: “Software Engineering for Computational Science: Past, Present, Future”, In: Computing in Science & Engineering, pp. 90-109, March/April 2018. https://doi.org/10.1109/MCSE.2018.108162940# Biodata: Prof. Dr. Wilhelm (Willi) Hasselbring is professor of Software Engineering and former dean of the Faculty of Engineering at Kiel University, Germany. In the competence cluster Software Systems Engineering (KoSSE), he coordinates technology transfer projects with industry. In the excellence cluster Future Ocean, in the Helmholtz Research School Ocean System Science and Technology (HOSST), and in the new Helmholtz School for Marine Data Science (MarDATA), he collaborates with the GEOMAR Helmholtz Centre for Ocean Research Kiel.

A central problem in the analysis of observational data is inferring casual relationships - what are the underlying causes of the observed behaviours? With the recent proliferation of Big Data from online social networks, it has become important to determine to what extent social influence causes certain messages to 'go viral', and to what extent other causes also play a role. In this thesis, we propose a methodological framework for quantitatively measuring and for qualifying the effects of social influence from Web-mediated interactions, while accounting for other relevant causes, on individual and collective outcomes, using 'found' observational digital data. This framework is based on causality theory and is informed by the social sciences, constituting a methodological contribution of the type that is much needed in the emergent interdisciplinary area of computational social science. We demonstrate theoretically and empirically how our framework offers a way for successfully addressing many of the limitations of the popular information diffusion-based paradigm for social influence online, enabling researchers to disentangle, measure and qualify the effects of social influence from online interactions, at the individual and the collective level.

In this talk, I will discuss the unexpected uses of social machines, and how individual and collective behaviour on platforms such as Twitter, Wikipedia, and the Zooniverse contribute to their development, success, and failure. Based on these observations, we will explore how we can take advantage of the emergent features and interpretive flexibility of social machines, in order to support current global challenges.

In recent years, there has been increased interest in real-world event summarization using publicly accessible data made available through social networking services such as Twitter and Facebook. People use these outlets to communicate with others, express their opinion and commentate on a wide variety of real-world events, such as disasters and public disorder. Due to the heterogeneity, the sheer volume of text and the fact that some messages are more informative than others, automatic summarization is a very challenging task. This paper presents three techniques for summarizing microblog documents by selecting the most representative posts for real-world events (clusters). In particular, we tackle the task of multilingual summarization in Twitter. We evaluate the generated summaries by comparing them to both human produced summaries and to the summarization results of similar leading summarization systems. Our results show that our proposed Temporal TF-IDF method outperforms all the other summarization systems for both the English and non-English corpora as they lead to informative summaries.

Abstract: In my talk I will discuss the way in which the ideas of the Data Science, Web and Semantic Web, Open Science contribute to new methods and approaches to data driven chemistry and chemical informatics. A key aspect of the discussion will be how to facilitate the improved acquisition and integration and analysis of chemical data in context. I will refer to lesions learnt in the e-Science and Digital Economy (particularly the IT as a Utility Network) programmes and the EDISON H2020 project. Jeremy G. Frey Jeremy Frey obtained his DPhil on experimental and theoretical aspects of van der Waals complexes, in Oxford, followed by a fellowship at the Lawrence Berkeley Laboratory with Yuan Lee. In 1984 he joined the University of Southampton, where he is now Professor of Physical Chemistry and head of the Computational Systems Chemistry Group. His experimental research probes molecular organization from single molecules to liquid interfaces using laser spectroscopy from the IR to soft X-rays. In parallel he investigates how e-Science infrastructure supports intelligent access to scientific data. He is strongly committed to collaborative inter and multi-disciplinary research and is skilled in facilitating communication between diverse disciplines speaking different languages. He has successfully lead several large interdisciplinary collaborative RUCK research grants, from Basic Technology (Coherent Soft X-Ray imaging), e-Science (CombeChem) and most recently the Digital Economy Challenge area of IT as a Utility Network+, where he has successfully created a unique platform to facilitate collaboration across the social, science, engineering and design domains, working with all the research, commercial, third and governmental sectors.

Abstract: Circular Economy is a paradigm for sustainable growth that envisions the transformation of how modern societies design, produce and consume goods and services towards a regenerative economic cycle. Future and emerging technologies, such as 5G, the blockchain, and crowdsourced sensing systems, along with innovative models and paradigms, such as the Internet of Things, Industry 4.0, and community networks, will play an important role in the transition to Circular Economy by enabling and facilitating, among others, digitization (efficient asset management, open data, etc.) and collaboration (co-innovation, shared value creation, etc.). In this talk we will introduce the paradigm of Smart (i.e. data-driven) Circular Economy, we will review corresponding technological enablers and will present data-driven circular business models. Biodata: Dr. Marios Angelopoulos is Principal Academic in Computing at Bournemouth University (UK), specialising in future and emerging paradigms of computer networks and distributed systems. Previously, he was with University of Geneva (CH) under the prestigious Swiss Government Excellence Scholarship for Foreign Researchers. At BU, he has established and leads the Open Innovation Lab (OIL) and is a founding member of the Future & Complex Networks (FlexNet) Research Group. He is also the founding Programme Leader of three master courses in the area of Internet of Things. Marios is also active in international standardisation bodies. Since 2018, he serves at the International Telecommunication Union (ITU-T) as Associate Rapporteur of Question 5 "Research and emerging technologies, terminology and definitions" in Study Group 20: Internet of Things (IoT) and Smart Cities and Communities (SC&C). He is also the Liaison co-Rapporteur of Study Group 20 to the Standardization Committee for Vocabulary (SCV). His research on Crowdsourced Systems has greatly contributed to the ITU-T work item on "Requirements and Functional Architecture of IoT-related Crowdsourced Systems". Finally, he has published in and served in the committees of several highly-esteemed international Journals and Conferences in his area of expertise (such as IEEE ToN, Elsevier's ComNet, ComCom, Ad-Hoc Nets, IEEE ICDCS, DCOSS, ICC, ACM MSWiM, etc).

Abstract: A common issue among European municipalities is the lack of information of mobility infrastructure Points of Interest (PoIs). This information is valuable both for powering services to citizens and as a mean to audit the urban health and environment of the city. Currently, municipalities need to send their employees to the field to do the counting, an expensive and error-prone approach that does not scale in the size of the area to be covered. Alternatively, one can rely on Volunteered Geographical Information (VGI) systems to crowdsource the data, but at the expense of having no control over data updates. We propose a faster and cheaper solution to tackle the problem by taking advantage of virtual imagery to use paid crowdworkers who can perform the item locating task remotely with no need of to be physically in place and without having any prior local knowledge of the area for which the exploration is required. We implemented a standalone crowdsourcing system named Virtual City Explorer (VCE) which allows collecting locations and images of PoIs on virtual spaces with paid crowdworkers. Our system takes as input a virtual space (e.g. a Google Street View instance), a type of PoI and an area of interest (defined as a geo-spatial polygon) and returns coordinates of instances of the target PoI type inside the area of interest discovered by a fixed, configurable, number of crowdworkers. Each crowdworker is asked to explore the area of interest finding a (configurable) number of PoIs, being rewarded upon completion. Our first experiments resulted in being very encouraging, showing how the VCE can effectively be used to find and collect locations of PoIs, in a cheaper and faster way. Speaker information Eddy Maddalena is a research fellow in the Web and Internet Science (WAIS) group of the University of Southampton, United Kingdom. Eddy got a PhD in Computer Science in 2017 at the University of Udine, Italy. During his PhD, Eddy mainly focused on Information Retrieval (IR) and crowdsourcing to create human annotated test collection of documents to be used to evaluate the effectiveness of IR systems. After holding his PhD, Eddy moved to the University of Southampton where he is the leader of the Crowdsourcing Work Package for the H2020 QROWD Project, and designs and develops crowdsourcing based solutions to improve mobility and reduce transportation issues for smart cities, which aim to include “human in the loop” participation in the Big Data Value Chain information flow.

The purpose of this seminar session is to share with you some of my experience with publishing in top quality journals. The session will be structured as follows: - Publish or Perish - The CS Debate (conferences vs journals) - Top journals - Multidiciplinary work - The Process