Dr. Richard Caulfield: antiquarian, scholar and academic librarian

The history of higher learning in Cork can be traced from its late eighteenth-century origins to its present standing within the extended confines of the Neo-Gothic architecture of University College, Cork. This institution, founded in 1845 was the successor and ultimate achievement of its forerunner, the Royal Cork Institution. The opening in 1849 of the college, then known as Queen's College, Cork, brought about a change in the role of the Royal Cork Institution as a centre of education. Its ambition of being the 'Munster College' was subsumed by the Queen's College even though it continued to function as a centre of learning up to the 1805. At this time its co-habitant, the School of Design, received a new wing under the benevolent patronage of William Crawford, and the Royal Cork Institution ceased to exist as the centre for cultural, technical and scientific learning it had set out to be. The building it occupied is today known as the Crawford Municipal Art Gallery.

Engaging with leadership development in Irish academic libraries: some reflections of the Future Leaders Programme (FLP)

Four librarians from Irish university libraries completed the U.K. Future Leaders Programme (FLP) in 2010. In this article they recount their experience and assess the effect of the programme on their professional practice and the value for their institutions. The programme is explored in the context of the Irish higher education environment, which is facing significant challenges due to the demise of the Celtic Tiger economy. A brief review of the literature relating to structured programmes to prepare librarians for senior positions, is presented. The structure and content of the FLP and the learning methodologies, theories, tools and techniques used throughout are discussed. The article suggests that the programme has real value for both individuals and institutions and that it can play a significant role in succession planning and the leadership development of librarians

Reasoning with imprecise trade-offs in decision making under certainty and uncertainty

In many real world situations, we make decisions in the presence of multiple, often conflicting and non-commensurate objectives. The process of optimizing systematically and simultaneously over a set of objective functions is known as multi-objective optimization. In multi-objective optimization, we have a (possibly exponentially large) set of decisions and each decision has a set of alternatives. Each alternative depends on the state of the world, and is evaluated with respect to a number of criteria. In this thesis, we consider the decision making problems in two scenarios. In the first scenario, the current state of the world, under which the decisions are to be made, is known in advance. In the second scenario, the current state of the world is unknown at the time of making decisions. For decision making under certainty, we consider the framework of multiobjective constraint optimization and focus on extending the algorithms to solve these models to the case where there are additional trade-offs. We focus especially on branch-and-bound algorithms that use a mini-buckets algorithm for generating the upper bound at each node of the search tree (in the context of maximizing values of objectives). Since the size of the guiding upper bound sets can become very large during the search, we introduce efficient methods for reducing these sets, yet still maintaining the upper bound property. We define a formalism for imprecise trade-offs, which allows the decision maker during the elicitation stage, to specify a preference for one multi-objective utility vector over another, and use such preferences to infer other preferences. The induced preference relation then is used to eliminate the dominated utility vectors during the computation. For testing the dominance between multi-objective utility vectors, we present three different approaches. The first is based on a linear programming approach, the second is by use of distance-based algorithm (which uses a measure of the distance between a point and a convex cone); the third approach makes use of a matrix multiplication, which results in much faster dominance checks with respect to the preference relation induced by the trade-offs. Furthermore, we show that our trade-offs approach, which is based on a preference inference technique, can also be given an alternative semantics based on the well known Multi-Attribute Utility Theory. Our comprehensive experimental results on common multi-objective constraint optimization benchmarks demonstrate that the proposed enhancements allow the algorithms to scale up to much larger problems than before. For decision making problems under uncertainty, we describe multi-objective influence diagrams, based on a set of p objectives, where utility values are vectors in Rp, and are typically only partially ordered. These can be solved by a variable elimination algorithm, leading to a set of maximal values of expected utility. If the Pareto ordering is used this set can often be prohibitively large. We consider approximate representations of the Pareto set based on ϵ-coverings, allowing much larger problems to be solved. In addition, we define a method for incorporating user trade-offs, which also greatly improves the efficiency.

Innovation and evolution: challenges and opportunities for 21st century academic and research libraries

A report from the inaugural CONUL (Consortium of National & University Libraries) conference held in the Radisson Blu Hotel, Athlone, June 3rd & 4th 2015.