LIBER's involvement in supporting digital preservation in member libraries

Digital curation and preservation represent new challenges for universities. LIBER has invested considerable effort to engage with the new agendas of digital preservation and digital curation. Through two successful phases of the LIFE project, LIBER is breaking new ground in identifying innovative models for costing digital curation and preservation. Through LIFE’s input into the US-UK Blue Ribbon Task Force on Sustainable Digital Preservation and Access, LIBER is aligned with major international work in the economics of digital preservation. In its emerging new strategy and structures, LIBER will continue to make substantial contributions in this area, mindful of the needs of European research libraries

Engineering Crowdsourced Stream Processing Systems

A crowdsourced stream processing system (CSP) is a system that incorporates crowdsourced tasks in the processing of a data stream. This can be seen as enabling crowdsourcing work to be applied on a sample of large-scale data at high speed, or equivalently, enabling stream processing to employ human intelligence. It also leads to a substantial expansion of the capabilities of data processing systems. Engineering a CSP system requires the combination of human and machine computation elements. From a general systems theory perspective, this means taking into account inherited as well as emerging properties from both these elements. In this paper, we position CSP systems within a broader taxonomy, outline a series of design principles and evaluation metrics, present an extensible framework for their design, and describe several design patterns. We showcase the capabilities of CSP systems by performing a case study that applies our proposed framework to the design and analysis of a real system (AIDR) that classifies social media messages during time-critical crisis events. Results show that compared to a pure stream processing system, AIDR can achieve a higher data classification accuracy, while compared to a pure crowdsourcing solution, the system makes better use of human workers by requiring much less manual work effort

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

The LIFE2 final project report

Executive summary: The first phase of LIFE (Lifecycle Information For E-Literature) made a major contribution to understanding the long-term costs of digital preservation; an essential step in helping institutions plan for the future. The LIFE work models the digital lifecycle and calculates the costs of preserving digital information for future years. Organisations can apply this process in order to understand costs and plan effectively for the preservation of their digital collections The second phase of the LIFE Project, LIFE2, has refined the LIFE Model adding three new exemplar Case Studies to further build upon LIFE1. LIFE2 is an 18-month JISC-funded project between UCL (University College London) and The British Library (BL), supported by the LIBER Access and Preservation Divisions. LIFE2 began in March 2007, and completed in August 2008. The LIFE approach has been validated by a full independent economic review and has successfully produced an updated lifecycle costing model (LIFE Model v2) and digital preservation costing model (GPM v1.1). The LIFE Model has been tested with three further Case Studies including institutional repositories (SHERPA-LEAP), digital preservation services (SHERPA DP) and a comparison of analogue and digital collections (British Library Newspapers). These Case Studies were useful for scenario building and have fed back into both the LIFE Model and the LIFE Methodology. The experiences of implementing the Case Studies indicated that enhancements made to the LIFE Methodology, Model and associated tools have simplified the costing process. Mapping a specific lifecycle to the LIFE Model isn’t always a straightforward process. The revised and more detailed Model has reduced ambiguity. The costing templates, which were refined throughout the process of developing the Case Studies, ensure clear articulation of both working and cost figures, and facilitate comparative analysis between different lifecycles. The LIFE work has been successfully disseminated throughout the digital preservation and HE communities. Early adopters of the work include the Royal Danish Library, State Archives and the State and University Library, Denmark as well as the LIFE2 Project partners. Furthermore, interest in the LIFE work has not been limited to these sectors, with interest in LIFE expressed by local government, records offices, and private industry. LIFE has also provided input into the LC-JISC Blue Ribbon Task Force on the Economic Sustainability of Digital Preservation. Moving forward our ability to cost the digital preservation lifecycle will require further investment in costing tools and models. Developments in estimative models will be needed to support planning activities, both at a collection management level and at a later preservation planning level once a collection has been acquired. In order to support these developments a greater volume of raw cost data will be required to inform and test new cost models. This volume of data cannot be supported via the Case Study approach, and the LIFE team would suggest that a software tool would provide the volume of costing data necessary to provide a truly accurate predictive model