CHARACTERIZATION AND THERMAL-HYDRAULIC MODELING OF ENGINEERED BARRIERS FOR A CANADIAN DEEP GEOLOGICAL REPOSITORY FOR USED NUCLEAR FUEL

Within Canada there are more than 2.5 million bundles of spent nuclear fuel with another approximately 2 million bundles to be generated in the future. Canada, and every country around the world that has taken a decision on management of spent nuclear fuel, has decided on long-term containment and isolation of the fuel within a deep geological repository. At depth, a deep geological repository consists of a network of placement rooms where the bundles will be located within a multi-layered system that incorporates engineered and natural barriers. The barriers will be placed in a complex thermal-hydraulic-mechanical-chemical-biological (THMCB) environment. A large database of material properties for all components in the repository are required to construct representative models. Within the repository, the sealing materials will experience elevated temperatures due to the thermal gradient produced by radioactive decay heat from the waste inside the container. Furthermore, high porewater pressure due to the depth of repository along with possibility of elevated salinity of groundwater would cause the bentonite-based materials to be under transient hydraulic conditions. Therefore it is crucial to characterize the sealing materials over a wide range of thermal-hydraulic conditions. A comprehensive experimental program has been conducted to measure properties (mainly focused on thermal properties) of all sealing materials involved in Mark II concept at plausible thermal-hydraulic conditions. The thermal response of Canada’s concept for a deep geological repository has been modelled using experimentally measured thermal properties. Plausible scenarios are defined and the effects of these scenarios are examined on the container surface temperature as well as the surrounding geosphere to assess whether they meet design criteria for the cases studied. The thermal response shows that if all the materials even being at dried condition, repository still performs acceptably as long as sealing materials remain in contact.

Multilingualism and conceptual modelling

One of the leading motivations behind the multilingual semantic web is to make resources accessible digitally in an online global multilingual context. Consequently, it is fundamental for knowledge bases to find a way to manage multilingualism and thus be equipped with those procedures for its conceptual modelling. In this context, the goal of this paper is to discuss how common-sense knowledge and cultural knowledge are modelled in a multilingual framework. More particularly, multilingualism and conceptual modelling are dealt with from the perspective of FunGramKB, a lexico-conceptual knowledge base for natural language understanding. This project argues for a clear division between the lexical and the conceptual dimensions of knowledge. Moreover, the conceptual layer is organized into three modules, which result from a strong commitment towards capturing semantic knowledge (Ontology), procedural knowledge (Cognicon) and episodic knowledge (Onomasticon). Cultural mismatches are discussed and formally represented at the three conceptual levels of FunGramKB.

D6.1 – Ecosystem Software Platform with Underlying Software Repository, Digital Library and Media Archive

The objective of D6.1 is to make the Ecosystem software platform with underlying Software Repository, Digital Library and Media Archive available to the degree, that the RAGE project can start collecting content in the form of software assets, and documents of various media types. This paper describes the current state of the Ecosystem as of month 12 of the project, and documents the structure of the Ecosystem, individual components, integration strategies, and overall approach. The deliverable itself is the deployment of the described components, which is now available to collect and curate content. Whilst this version is not yet feature complete, full realization is expected within the next few months. Following this development, WP6 will continue to add features driven by the business models to be defined by WP7 later on in the project.

The RAGE Software Asset Model and Metadata Model

Software assets are key output of the RAGE project and they can be used by applied game developers to enhance the pedagogical and educational value of their games. These software assets cover a broad spectrum of functionalities – from player analytics including emotion detection to intelligent adaptation and social gamification. In order to facilitate integration and interoperability, all of these assets adhere to a common model, which describes their properties through a set of metadata. In this paper the RAGE asset model and asset metadata model is presented, capturing the detail of assets and their potential usage within three distinct dimensions – technological, gaming and pedagogical. The paper highlights key issues and challenges in constructing the RAGE asset and asset metadata model and details the process and design of a flexible metadata editor that facilitates both adaptation and improvement of the asset metadata model.

Display At Your Own Risk: The Metadata

This book contains the Exif, XMP, and IPTC metadata extract ed from the 100 digital surrogates featured in Display At Your Own Risk, an online exhibition experiment. In some cases, the metadata is extensive, almost overwhelming; in others, little to no metadata was embedded in the digital surrogate's file at all. Preparing this book to accompany the Display At Your Own Risk exhibition made us realise that metadata can be beautiful. We hope you find beauty here too.

Online document repository for GEM Website (2016)

Resources created at University of Southampton for the module GIS for Environmental Management (GEM)

Diaries Metadata

A journal of commercial voyages and domestic life on the Tigris River -- diary metadata.

RDA and Linked Data: A New Way to Look at the Henson Collection

In 2005, the University of Maryland acquired over 70 digital videos spanning 35 years of Jim Henson’s groundbreaking work in television and film. To support in-house discovery and use, the collection was cataloged in detail using AACR2 and MARC21, and a web-based finding aid was also created. In the past year, I created an "r-ball" (a linked data set described using RDA) of these same resources. The presentation will compare and contrast these three ways of accessing the Jim Henson Works collection, with insights gleaned from providing resource discovery using RIMMF (RDA in Many Metadata Formats).

Building a Successful (and Flexible) Partnership with UMD's Gymkana Troupe

Presented at the 2016 Library Research and Innovative Practice Forum, this poster provides an overview of a successful partnership between the University of Maryland Archives and UMD's Gymkana Troupe to publicize Gymkana's 70th anniversary and to digitize the troupe's holdings in the Archives. Gymkana is an exhibition gymnastics troupe founded on campus in 1946 which runs a variety of educational and healthy-living outreach programs. Various stages of the project are highlighted, including an exhibit in McKeldin Library, a LaunchUMD fundraising campaign, and the troupe's participation in metadata creation for digital objects. By maintaining an open and flexible dialogue throughout the project planning and execution, both the library and the troupe members ultimately benefited from this collaboration.

Security and Trust in Distributed Computation

We propose three research problems to explore the relations between trust and security in the setting of distributed computation. In the first problem, we study trust-based adversary detection in distributed consensus computation. The adversaries we consider behave arbitrarily disobeying the consensus protocol. We propose a trust-based consensus algorithm with local and global trust evaluations. The algorithm can be abstracted using a two-layer structure with the top layer running a trust-based consensus algorithm and the bottom layer as a subroutine executing a global trust update scheme. We utilize a set of pre-trusted nodes, headers, to propagate local trust opinions throughout the network. This two-layer framework is flexible in that it can be easily extensible to contain more complicated decision rules, and global trust schemes. The first problem assumes that normal nodes are homogeneous, i.e. it is guaranteed that a normal node always behaves as it is programmed. In the second and third problems however, we assume that nodes are heterogeneous, i.e, given a task, the probability that a node generates a correct answer varies from node to node. The adversaries considered in these two problems are workers from the open crowd who are either investing little efforts in the tasks assigned to them or intentionally give wrong answers to questions. In the second part of the thesis, we consider a typical crowdsourcing task that aggregates input from multiple workers as a problem in information fusion. To cope with the issue of noisy and sometimes malicious input from workers, trust is used to model workers' expertise. In a multi-domain knowledge learning task, however, using scalar-valued trust to model a worker's performance is not sufficient to reflect the worker's trustworthiness in each of the domains. To address this issue, we propose a probabilistic model to jointly infer multi-dimensional trust of workers, multi-domain properties of questions, and true labels of questions. Our model is very flexible and extensible to incorporate metadata associated with questions. To show that, we further propose two extended models, one of which handles input tasks with real-valued features and the other handles tasks with text features by incorporating topic models. Our models can effectively recover trust vectors of workers, which can be very useful in task assignment adaptive to workers' trust in the future. These results can be applied for fusion of information from multiple data sources like sensors, human input, machine learning results, or a hybrid of them. In the second subproblem, we address crowdsourcing with adversaries under logical constraints. We observe that questions are often not independent in real life applications. Instead, there are logical relations between them. Similarly, workers that provide answers are not independent of each other either. Answers given by workers with similar attributes tend to be correlated. Therefore, we propose a novel unified graphical model consisting of two layers. The top layer encodes domain knowledge which allows users to express logical relations using first-order logic rules and the bottom layer encodes a traditional crowdsourcing graphical model. Our model can be seen as a generalized probabilistic soft logic framework that encodes both logical relations and probabilistic dependencies. To solve the collective inference problem efficiently, we have devised a scalable joint inference algorithm based on the alternating direction method of multipliers. The third part of the thesis considers the problem of optimal assignment under budget constraints when workers are unreliable and sometimes malicious. In a real crowdsourcing market, each answer obtained from a worker incurs cost. The cost is associated with both the level of trustworthiness of workers and the difficulty of tasks. Typically, access to expert-level (more trustworthy) workers is more expensive than to average crowd and completion of a challenging task is more costly than a click-away question. In this problem, we address the problem of optimal assignment of heterogeneous tasks to workers of varying trust levels with budget constraints. Specifically, we design a trust-aware task allocation algorithm that takes as inputs the estimated trust of workers and pre-set budget, and outputs the optimal assignment of tasks to workers. We derive the bound of total error probability that relates to budget, trustworthiness of crowds, and costs of obtaining labels from crowds naturally. Higher budget, more trustworthy crowds, and less costly jobs result in a lower theoretical bound. Our allocation scheme does not depend on the specific design of the trust evaluation component. Therefore, it can be combined with generic trust evaluation algorithms.

Self-archiving publications

This chapter discusses the historical development, current practice and future prospects of the self-archiving of research papers in open-access repositories (so-called 'e-print archives'). It describes how the development of interoperable e-print repositories in a number of subject communities has shown that self-archiving can benefit academic researchers (and potentially others) by enabling quick and easy access to the research literature and therefore maximising the impact potential of papers. Realising that the possible benefits are high and the technical entry barriers low, many organisations such as universities have recently tried to encourage widespread self-archiving by setting up institutional repositories. However, major barriers to self-archiving remain - most of them cultural and managerial. There are concerns about quality control, intellectual property rights, disturbing the publishing status quo, and workload. Ways in which these issues are currently being addressed are discussed in this chapter. A number of self-archiving initiatives in different countries have been set up to address the concerns and to kick-start e-print repository use. However, issues remain which require further investigation; those discussed in this chapter include discipline differences, definitions of 'publication', versioning problems, digital preservation, costing and funding models, and metadata standards. The ways in which these issues are resolved will be important in determining the future of self-archiving. Possible futures are discussed with particular reference to journal publishing and quality control. If widely adopted, self-archiving might come to assume a central place in the scholarly communication process, but a great deal of restructuring of the process needs to take place before this potential can be realised.

Virtual Research Environments Roundtable

The roundtable offered an opportunity to share experiences and perceptions of virtual research environments. John Doove (SURFfoundation) presented his impressions from the VRE projects. Jim Farmer, Instructional Media + Magic led a 50 minute discussion on key developments and challenges. The discussion included issues like: An emerging issue is the sharp and continuous increase of data in an era of limited resources. These increases often reduce the effectiveness of search-additional time is required to find expected results. Would new methods of search may be useful? Should this be included as services in a VRE? The form of much new 'knowledge' is in informal 'publications' such as blogs, email, audio, and video which lack the precise metadata of books and journal articles. Could VRE services assist in using these resources as well? The programme continued with discussions on business models for sustainability led by Birte Christensen-Dalsgaard, The Royal Library, and policy and funders' interventions led by Sigrun Eckelmann, DFG.

Preparing for the Research Excellence Framework: Examples of Open Access Good Practice across the United Kingdom

This article concerns how higher education institutions across the United Kingdom are implementing systems and workflows in order to meet open access requirements for the next Research Excellence Framework. The way that institutions are preparing is not uniform, although there are key areas which require attention: cost management, advocacy, systems and metadata, structural workflows, and internal policy. Examples of preparative work in these areas are taken from institutions who have participated in the Open Access Good Practice initiative supported by Jisc.

Permanent Public Access for Citizens - Finnish Government Publications on a Repository Platform

Poster presented at Open Repositories 2016 in Dublin, Ireland, June 14, 2016