myTea: Connecting the Web to Digital Science on the Desktop

Bioinformaticians regularly access the hundreds of databases and tools that are available to them on the Web. None of these tools communicate with each other, causing the scientist to copy results manually from a Web site into a spreadsheet or word processor. myGrids' Taverna has made it possible to create templates (workflows) that automatically run searches using these databases and tools, cutting down what previously took days of work into hours, and enabling the automated capture of experimental details. What is still missing in the capture process, however, is the details of work done on that material once it moves from the Web to the desktop: if a scientist runs a process on some data, there is nothing to record why that action was taken; it is likewise not easy to publish a record of this process back to the community on the Web. In this paper, we present a novel interaction framework, built on Semantic Web technologies, and grounded in usability design practice, in particular the Making Tea method. Through this work, we introduce a new model of practice designed specifically to (1) support the scientists' interactions with data from the Web to the desktop, (2) provide automatic annotation of process to capture what has previously been lost and (3) associate provenance services automatically with that data in order to enable meaningful interrogation of the process and controlled sharing of the results

Mapping web personal learning environments

A recent trend in web development is to build platforms which are carefully designed to host a plurality of software components (sometimes called widgets or plugins) which can be organized or combined (mashed-up) at user's convenience to create personalized environments. The same holds true for the web development of educational applications. The degree of personalization can depend on the role of users such as in traditional virtual learning environment, where the components are chosen by a teacher in the context of a course. Or, it can be more opened as in a so-called personalized learning environment (PLE). It now exists a wide array of available web platforms exhibiting different functionalities but all built on the same concept of aggregating components together to support different tasks and scenarios. There is now an overlap between the development of PLE and the more generic developments in web 2.0 applications such as social network sites. This article shows that 6 more or less independent dimensions allow to map the functionalities of these platforms: the screen dimensionmaps the visual integration, the data dimension maps the portability of data, the temporal dimension maps the coupling between participants, the social dimension maps the grouping of users, the activity dimension maps the structuring of end users–interactions with the environment, and the runtime dimensionmaps the flexibility in accessing the system from different end points. Finally these dimensions are used to compare 6 familiar Web platforms which could potentially be used in the construction of a PLE

An Opportunistic Approach to Adding Value to a Photograph Collection

The Semantic Web can, among other things, be used for photograph annotation. Many implementations of this idea exist, but all are limited by the fact that a human must manually create the annotations for the photographs, often using a program with which he or she is not familiar. This poster discusses an opportunistic method of photograph annotation that uses logical inference in conjunction with existing data from various sources in order to obtain information about the images being annotated

Building blocks for semantic data organization on the desktop

Die Organisation von (Multimedia-) Daten auf Desktop-Systemen wird derzeit hauptsächlich durch das Einordnen von Dateien in ein hierarchisches Dateisystem bewerkstelligt. Zusätzlich werden gewisse Inhalte (z.B. Musik oder Fotos) von spezialisierter Software mit Hilfe Datei-bezogener Metadaten verwaltet. Diese Metadaten werden meist direkt im Dateikopf in einer Unzahl verschiedener, vorwiegend proprietärer Formate gespeichert. Allgemein nehmen Metadaten und Links die Schlüsselrollen in fortgeschrittenen Datenorganisationskonzepten ein, ihre eingeschränkte Unterstützung in vorherrschenden Dateisystemen macht die Einführung solcher Konzepte auf dem Desktop jedoch schwierig: Erstens müssen Anwendungen sowohl Dateiformat als auch Metadatenschema verstehen um auf Metadaten zugreifen zu können; zweitens ist ein getrennter Zugriff auf Daten und Metadaten nicht möglich und drittens kann man solche Metadaten nicht mit mehreren Dateien oder mit Dateiordnern assoziieren obgleich letztere die derzeit wichtigsten Konstrukte für die Dateiorganisation darstellen. Dies bedeutet in weiterer Folge: (i) eingeschränkte Möglichkeiten der Datenorganisation, (ii) eingeschränkte Navigationsmöglichkeiten, (iii) schlechte Auffindbarkeit der gespeicherten Daten, und (iv) Fragmentierung von Metadaten. Obschon es Versuche gab, diese Situation (zum Beispiel mit Hilfe semantischer Dateisysteme) zu verbessern, wurden die meisten dieser Probleme bisher vor allem im Web und im Speziellen im semantischen Web adressiert und gelöst. Das Anwenden dort entwickelter Lösungen auf dem Desktop, einer zentralen Plattform der Daten- und Metadatenmanipulation, wäre zweifellos von Vorteil. In der vorliegenden Arbeit wird ein neues, rückwärts-kompatibles Metadatenmodell als Lösungsversuch für die oben genannten Probleme präsentiert. Dieses Modell basiert auf stabilen Datei-Identifikatoren und externen, semantischen, Datei- bezogenen Metadatenbeschreibungen welche im RDF Graphenmodell repräsentiert werden. Diese Beschreibungen sind durch eine einheitliche Linked-Data- Schnittstelle zugänglich und können mit anderen Beschreibungen und Ressourcen verlinkt werden. Im Speziellen erlaubt dieses Modell semantische Links zwischen lokalen Dateisystemobjekten und Netzressourcen im Web sowie im entstehenden “Daten Web” und ermöglicht somit die Integration dieser Datenräume. Das Modell hängt entscheidend von der Stabilität dieser Links ab weshalb zwei Algorithmen präsentiert werden, welche deren Integrität in lokalen und vernetzten Umgebungen erhalten können. Dies bedeutet, dass Links zwischen Dateisystemobjekten, Metadatenbeschreibungen und Netzressourcen nicht brechen wenn sich deren Adressen ändern, z.B. wenn Dateien verschoben oder Linked-Data Ressourcen unter geänderten URIs publiziert werden. Schließlich wird eine prototypische Implementierung des vorgeschlagenen Metadatenmodells präsentiert, welche demonstriert wie die Summe dieser Bausteine eine Metadatenschicht bildet die als Grundlage für semantische Datenorganisation auf dem Desktop verwendet werden kann.The organization of (multimedia) data on current desktop systems is done to a large part by arranging files in hierarchical file systems, but also by specialized applications (e.g., music or photo organizing software) that make use of file-related metadata for this task. These metadata are predominantly stored in embedded file headers, using a magnitude of mainly proprietary formats. Generally, metadata and links play the key roles in advanced data organization concepts. Their limited support in prevalent file system implementations, however, hinders the adoption of such concepts on the desktop: First, non-uniform access interfaces require metadata consuming applications to understand both a file’s format and its metadata scheme; second, separate data/metadata access is not possible, and third, metadata cannot be attached to multiple files or to file folders although the latter are the primary constructs for file organization. As a consequence of this, current desktops suffer, inter alia, from (i) limited data organization possibilities, (ii) limited navigability, (iii) limited data findability, and (iv) metadata fragmentation. Although there were attempts to improve this situation, e.g., by introducing semantic file systems, most of these issues were successfully addressed and solved in the Web and in particular in the Semantic Web and reusing these solutions on the desktop, a central hub of data and metadata manipulation, is clearly desirable. In this thesis a novel, backwards-compatible metadata model that addresses the above-mentioned issues is introduced. This model is based on stable file identifiers and external, file-related, semantic metadata descriptions that are represented using the generic RDF graph model. Descriptions are accessible via a uniform Linked Data interface and can be linked with other descriptions and resources. In particular, this model enables semantic linking between local file system objects and remote resources on the Web or the emerging Web of Data, thereby enabling the integration of these data spaces. As the model crucially relies on the stability of these links, we contribute two algorithms that preserve their integrity in local and in remote environments. This means that links between file system objects, metadata descriptions and remote resources do not break even if their addresses change, e.g., when files are moved or Linked Data resources are re-published using different URIs. Finally, we contribute a prototypical implementation of the proposed metadata model that demonstrates how these building blocks sum up to constitute a metadata layer that may act as a foundation for semantic data organization on the desktop

LBWiki: A Location-Based Wiki

Wiki systems provide a simple interface paradigm that allow non-technical users to author collaborative on-line hypertexts. In this paper we propose to use the same simple paradigm to allow users to create content for ubiquitous information systems, and present LBWiki, a prototype location-based Wiki that allows users with a mobile device to create Wiki pages based on GPS co-ordinates. We describe the hierarchical location scheme used within LBWiki and the results of a small evaluation, in which users reacted positively to the concept, but asked for greater control over geographical regions, and highlighted the importance of accurate location technology

The information retrieval challenge of human digital memories

Today people are storing increasing amounts of personal information in digital format. While storage of such information is becoming straight forward, retrieval from the vast personal archives that this is creating poses significant challenges. Existing retrieval techniques are good at retrieving from non-personal spaces, such as the World Wide Web. However they are not sufficient for retrieval of items from these new unstructured spaces which contain items that are personal to the individual, and of which the user has personal memories and with which has had previous interaction. We believe that there are new and exciting possibilities for retrieval from personal archives. Memory cues act as triggers for individuals in the remembering process, a better understanding of memory cues will enable us to design new and effective retrieval algorithms and systems for personal archives. Context data, such as time and location, is already proving to play a key part in this special retrieval domain, for example for searching personal photo archives, we believe there are many other rich sources of context that can be exploited for retrieval from personal archives

Semantic Support for Computational Land-Use Modelling

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