Linked Data - the story so far

The term “Linked Data” refers to a set of best practices for publishing and connecting structured data on the Web. These best practices have been adopted by an increasing number of data providers over the last three years, leading to the creation of a global data space containing billions of assertions— the Web of Data. In this article, the authors present the concept and technical principles of Linked Data, and situate these within the broader context of related technological developments. They describe progress to date in publishing Linked Data on the Web, review applications that have been developed to exploit the Web of Data, and map out a research agenda for the Linked Data community as it moves forward

When Technology Makes Headlines: The Media's Double Vision About the Digital Age

Analyzes technology-related news items appearing in lead sections of mainstream media for trends in popular topics, companies, and messages about technology's influence and its risks. Compares findings with trends in new media such as blogs and Twitter

Linking Locations: Storytelling with Pervasive Technology

With online location-aware smart phones in more and more pockets, storytelling is moving to the streets. Simultaneously, an increasing abundance of Linked Data is being made available, complete with geographical information. In this paper, we review the state of the art and suggest approaches to, and issues with, a storytelling system that combines these two technologies

Information access tasks and evaluation for personal lifelogs

Emerging personal lifelog (PL) collections contain permanent digital records of information associated with individuals’ daily lives. This can include materials such as emails received and sent, web content and other documents with which they have interacted, photographs, videos and music experienced passively or created, logs of phone calls and text messages, and also personal and contextual data such as location (e.g. via GPS sensors), persons and objects present (e.g. via Bluetooth) and physiological state (e.g. via biometric sensors). PLs can be collected by individuals over very extended periods, potentially running to many years. Such archives have many potential applications including helping individuals recover partial forgotten information, sharing experiences with friends or family, telling the story of one’s life, clinical applications for the memory impaired, and fundamental psychological investigations of memory. The Centre for Digital Video Processing (CDVP) at Dublin City University is currently engaged in the collection and exploration of applications of large PLs. We are collecting rich archives of daily life including textual and visual materials, and contextual context data. An important part of this work is to consider how the effectiveness of our ideas can be measured in terms of metrics and experimental design. While these studies have considerable similarity with traditional evaluation activities in areas such as information retrieval and summarization, the characteristics of PLs mean that new challenges and questions emerge. We are currently exploring the issues through a series of pilot studies and questionnaires. Our initial results indicate that there are many research questions to be explored and that the relationships between personal memory, context and content for these tasks is complex and fascinating

Social Dynamics of Digg

Online social media provide multiple ways to find interesting content. One important method is highlighting content recommended by user's friends. We examine this process on one such site, the news aggregator Digg. With a stochastic model of user behavior, we distinguish the effects of the content visibility and interestingness to users. We find a wide range of interest and distinguish stories primarily of interest to a users' friends from those of interest to the entire user community. We show how this model predicts a story's eventual popularity from users' early reactions to it, and estimate the prediction reliability. This modeling framework can help evaluate alternative design choices for displaying content on the site.Comment: arXiv admin note: text overlap with arXiv:1010.023

Geoscience after IT: Part J. Human requirements that shape the evolving geoscience information system

The geoscience record is constrained by the limitations of human thought and of the technology for handling information. IT can lead us away from the tyranny of older technology, but to find the right path, we need to understand our own limitations. Language, images, data and mathematical models, are tools for expressing and recording our ideas. Backed by intuition, they enable us to think in various modes, to build knowledge from information and create models as artificial views of a real world. Markup languages may accommodate more flexible and better connected records, and the object-oriented approach may help to match IT more closely to our thought processes

Applying XP Ideas Formally: The Story Card and Extreme X-Machines

By gathering requirements on story cards extreme programming (XP) makes requirements collection easy. However it is less clear how the story cards are translated into a �finished product. We propose that a formal specification method based on X-Machines can be used to direct this transition. Extreme X-Machines �t in to the XP method well, without large overheads in design and maintenance. We also investigate how such machines adapt to change in the story cards and propose how this could be further enhanced

Testing the Role of Technical Information in Public Risk Perception

It is widely believed that more detail about health effects and likely exposure routes is apt to reduce citizens\u27 concerns about low-probability Risks. The authors\u27 study suggests that providing such detail may not be as useful as, e.g., addressing public concerns and keeping citizens current on officials\u27 actions