WebAL Comes of Age: A review of the first 21 years of Artificial Life on the Web

We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from 1994—when the first WebAL work appeared—up to the present day, together with a brief discussion of relevant precursors. We examine recent projects, from 2010–2015, in greater detail in order to highlight the current state of the art. We follow the survey with a discussion of common themes and methodologies that can be observed in recent work and identify a number of likely directions for future work in this exciting area

Evaluating Knowledge Anchors in Data Graphs against Basic Level Objects

The growing number of available data graphs in the form of RDF Linked Da-ta enables the development of semantic exploration applications in many domains. Often, the users are not domain experts and are therefore unaware of the complex knowledge structures represented in the data graphs they in-teract with. This hinders users’ experience and effectiveness. Our research concerns intelligent support to facilitate the exploration of data graphs by us-ers who are not domain experts. We propose a new navigation support ap-proach underpinned by the subsumption theory of meaningful learning, which postulates that new concepts are grasped by starting from familiar concepts which serve as knowledge anchors from where links to new knowledge are made. Our earlier work has developed several metrics and the corresponding algorithms for identifying knowledge anchors in data graphs. In this paper, we assess the performance of these algorithms by considering the user perspective and application context. The paper address the challenge of aligning basic level objects that represent familiar concepts in human cog-nitive structures with automatically derived knowledge anchors in data graphs. We present a systematic approach that adapts experimental methods from Cognitive Science to derive basic level objects underpinned by a data graph. This is used to evaluate knowledge anchors in data graphs in two ap-plication domains - semantic browsing (Music) and semantic search (Ca-reers). The evaluation validates the algorithms, which enables their adoption over different domains and application contexts

TOWARDS EFFICIENT PRESENTATION AND INTERACTION IN VISUAL DATA ANALYSIS

The "data explosion'' since the era of the Internet has increased data size tremendously, from several hundred Megabytes to millions of Terabytes. Large amounts of data may not fit into memory, and a proper way of handling and processing the data is necessary. Besides, analyses of such large scale data requires complex and time consuming algorithms. On the other hand, humans play an important role in steering and driving the data analysis, while there are often times when people have a hard time getting an overview of the data or knowing which analysis to run. Sometimes they may not even know where to start. There is a huge gap between the data and understanding. An intuitive way to facilitate data analysis is to visualize it. Visualization is understandable and illustrative, while using it to support fast and rapid data exploration of large scale datasets has been a challenge for a long time. In this dissertation, we aim to facilitate efficient visual data exploration of large scale datasets from two perspectives: efficiency and interaction. The former indicates how users could understand the data efficiently, this depends on various factors, such as how fast data is processed and how data is presented, while the latter focuses more on the users: how they deal with the data and why they interact with the system in a particular way. In order to improve the efficiency of data exploration, we have looked into two steps in the visualization pipeline: rendering and processing (computations). We first address visualization rendering of large dataset through a thorough evaluation of web-based visualization performance. We evaluate and understand the page loading effects of Scalable Vector Graphics (SVG), a popular image format for interactive visualization on the web browsers. To understand the scalability of individual elements in SVG based visualization, we conduct performance tests on different types of charts, in different phases of rendering process. From the results, we have figured out optimization techniques and guidelines to achieve better performance when rendering SVG visualization. Secondly, we present a pure browser based distributed computing framework (VisHive) that exploits computational power from co-located idle devices for visualization. The VisHive framework speeds up web-based visualization, which is originally designed for single computer and cannot make use of additional computational resources on the client side. It takes advantage of multiple devices that today's users often have access to. VisHive constructs visualization applications that can transparently connect multiple devices into an ad-hoc cluster for local computation. It requires no specific software to be downloaded for setup. To achieve a more interactive data analysis process, we first propose a proactive visual analytics system (DataSite) that enable users to analyze the data smoothly with a list of pre-defined algorithms. DataSite provides results through selecting and executing computations using automatic server-side computation. It utilizes computational resources exhaustively during data analysis to reduce the burden of human thinking. Analyzing results identified by these background processes are surfaced as status updates in a feed on the front-end, akin to posts in a social media feed. DataSite effectively turns data analysis into a conversation between the user and the computer, thereby reducing the cognitive load and domain knowledge requirements on users. Next we apply the concept of proactive data analysis to genomic data, and explore how to improve data analysis through adaptive computations in bioinformatics domain. We build Epiviz Feed, a web application that supports proactive visual and statistical analysis of genomic data. It addresses common and popular biological questions that may be asked by the analyst, and shortens the time of processing and analyzing the data with automatic computations. We further present a computational steering mechanism for visual analytics that prioritizes computations performed on the dataset leveraging the analyst's navigational behavior in the data. The web-based system, called Sherpa, provides computational modules for genomic data analysis, where independent algorithms calculate test statistics relevant to biological inferences about gene regulation in various tumor types and their corresponding normal tissues

Proceedings of the 1st International Conference on Live Coding

Open Access peer reviewed papers on live coding published at the 1st International Conference on Live Coding (ICLC) in Leeds

MediaSync: Handbook on Multimedia Synchronization

This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences

Responsible AI and Analytics for an Ethical and Inclusive Digitized Society

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