Supporting service discovery, querying and interaction in ubiquitous computing environments.

In this paper, we contend that ubiquitous computing environments will be highly heterogeneous, service rich domains. Moreover, future applications will consequently be required to interact with multiple, specialised service location and interaction protocols simultaneously. We argue that existing service discovery techniques do not provide sufficient support to address the challenges of building applications targeted to these emerging environments. This paper makes a number of contributions. Firstly, using a set of short ubiquitous computing scenarios we identify several key limitations of existing service discovery approaches that reduce their ability to support ubiquitous computing applications. Secondly, we present a detailed analysis of requirements for providing effective support in this domain. Thirdly, we provide the design of a simple extensible meta-service discovery architecture that uses database techniques to unify service discovery protocols and addresses several of our key requirements. Lastly, we examine the lessons learnt through the development of a prototype implementation of our architecture

Impliance: A Next Generation Information Management Appliance

ably successful in building a large market and adapting to the changes of the last three decades, its impact on the broader market of information management is surprisingly limited. If we were to design an information management system from scratch, based upon today's requirements and hardware capabilities, would it look anything like today's database systems?" In this paper, we introduce Impliance, a next-generation information management system consisting of hardware and software components integrated to form an easy-to-administer appliance that can store, retrieve, and analyze all types of structured, semi-structured, and unstructured information. We first summarize the trends that will shape information management for the foreseeable future. Those trends imply three major requirements for Impliance: (1) to be able to store, manage, and uniformly query all data, not just structured records; (2) to be able to scale out as the volume of this data grows; and (3) to be simple and robust in operation. We then describe four key ideas that are uniquely combined in Impliance to address these requirements, namely the ideas of: (a) integrating software and off-the-shelf hardware into a generic information appliance; (b) automatically discovering, organizing, and managing all data - unstructured as well as structured - in a uniform way; (c) achieving scale-out by exploiting simple, massive parallel processing, and (d) virtualizing compute and storage resources to unify, simplify, and streamline the management of Impliance. Impliance is an ambitious, long-term effort to define simpler, more robust, and more scalable information systems for tomorrow's enterprises.Comment: This article is published under a Creative Commons License Agreement (http://creativecommons.org/licenses/by/2.5/.) You may copy, distribute, display, and perform the work, make derivative works and make commercial use of the work, but, you must attribute the work to the author and CIDR 2007. 3rd Biennial Conference on Innovative Data Systems Research (CIDR) January 710, 2007, Asilomar, California, US

Policy Patterns for Usage Control in Data Spaces

Data-driven technologies have the potential to initiate a transportation related revolution in the way we travel, commute and navigate within cities. As a major effort of this transformation relies on Mobility Data Spaces for the exchange of mobility data, the necessity to protect valuable data and formulate conditions for data exchange arises. This paper presents key contributions to the development of automated contract negotiation and data usage policies in the Mobility Data Space. A comprehensive listing of policy patterns for usage control is provided, addressing common requirements and scenarios in data sharing and governance. The use of the Open Digital Rights Language (ODRL) is proposed to formalize the collected policies, along with an extension of the ODRL vocabulary for data space-specific properties.Comment: 12 pages, 1 figure, 1 table, 2 listing

An Open Framework for Integrating Widely Distributed Hypermedia Resources

The success of the WWW has served as an illustration of how hypermedia functionality can enhance access to large amounts of distributed information. However, the WWW and many other distributed hypermedia systems offer very simple forms of hypermedia functionality which are not easily applied to existing applications and data formats, and cannot easily incorporate alternative functions which would aid hypermedia navigation to and from existing documents that have not been developed with hypermedia access in mind. This paper describes the extension to a distributed environment of the open hypermedia functionality of the Microcosm system, which is designed to support the provision of hypermedia access to a wide range of source material and application, and to offer straightforward extension of the system to incorporate new forms of information access

Unifying Distributed Processing and Open Hypertext through a Heterogeneous Communication Model

A successful distributed open hypermedia system can be characterised by a scaleable architecture which is inherently distributed. While the architects of distributed hypermedia systems have addressed the issues of providing and retrieving distributed resources, they have often neglected to design systems with the inherent capability to exploit the distributed processing of this information. The research presented in this paper describes the construction and use of an open hypermedia system concerned equally with both of these facets

Position Paper: Secure Infrastructure for Scientific Data Life Cycle Management

Abstract—Within the Austrian Grid project phase 2, three different groups, each allocated to a different workpackage, join their efforts to implement a grid infrastructure for the european research project “Breath Gas Analysis for molecular oriented diseases”. This position paper provides background on the task and the resulting requirements, a presentation on solutions developed during related projects in the application domain, identifies problems that have not yet been solved, and finally presents the intended solution to be developed. I. INTRODUCTION & CONTEXT This position paper describes the current state, the in-tended realisation and a discussion of the project Grid Breath Gas Analysis (BAMOD-Grid) carried out withi

Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach.

Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain-computer interface models. However, the absence of standardized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the difficulty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a "containerized" approach and freely available tools we have developed to facilitate the process of annotating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-)analysis. The EEG Study Schema (ESS) comprises three data "Levels," each with its own XML-document schema and file/folder convention, plus a standardized (PREP) pipeline to move raw (Data Level 1) data to a basic preprocessed state (Data Level 2) suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are increasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at www.eegstudy.org and a central catalog of over 850 GB of existing data in ESS format is available at studycatalog.org. These tools and resources are part of a larger effort to enable data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org)

Coordination and P2P computing

Peer-to-Peer (P2P) refers to a class of systems and/or applications that use distributed resources in a decentralized and autonomous manner to achieve a goal. A number of successful applications, like BitTorrent (for file and content sharing) and SETI@Home (for distributed computing) have demonstrated the feasibility of this approach. As a new form of distributed computing, P2P computing has the same coordination problems as other forms of distributed computing. Coordination has been considered an important issue in distributed computing for a long time and many coordination models and languages have been developed. This research focuses on how to solve coordination problems in P2P computing. In particular, it is to provide a seamless P2P computing environment so that the migration of computation components is transparent. This research extends Manifold, an event-driven coordination model, to meet P2P computing requirements and integrates the P2P-Manifold model into an existing platform. The integration hides the complexity of the coordination model and makes the model easy to use

Data Spaces

This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical

Scalable dataspace construction

The conference aimed at supporting and stimulating active productive research set to strengthen the technical foundations of engineers and scientists in the continent, through developing strong technical foundations and skills, leading to new small to medium enterprises within the African sub-continent. It also seeked to encourage the emergence of functionally skilled technocrats within the continent.This paper proposes the design and implementation of scalable dataspaces based on efficient data structures. Dataspaces are often likely to exhibit a multidimensional structure due to the unpredictable neighbour relationship between participants coupled by the continuous exponential growth of data. Layered range trees are incorporated to the proposed solution as multidimensional binary trees which are used to perform d-dimensional orthogonal range indexing and searching. Furthermore, the solution is readily extensible to multiple dimensions, raising the possibility of volume searches and even extension to attribute space. We begin by a study of the important literature and dataspace designs. A scalable design and implementation is further presented. Finally, we conduct experimental evaluation to illustrate the finer performance of proposed techniques. The design of a scalable dataspace is important in order to bridge the gap resulting from the lack of coexistence of data entities in the spatial domain as a key milestone towards pay-as-you-go systems integrationStrathmore University;nstitute of Electrical and Electronics Engineers (IEEE