Brookes equation: The basis for a qualitative characterization of information behaviours

Brookes equation, which has hitherto been regarded as a kind of non-mathematical shorthand description of information use, is extended so as to show the qualitative pattern of information access. Information inputs are represented by a simple power law, and changes in knowledge structure by possible changes to a simple mental map. The resulting pattern shows seven forms of information input and three forms of change in knowledge structure, giving 21 categories overall. These have the potential for use as an explanatory tool and taxonomy for studying and summarizing information behaviour, and offer the possibility of being developed into more sophisticated and quantitative treatments

Evaluating a workspace's usefulness for image retrieval

Image searching is a creative process. We have proposed a novel image retrieval system that supports creative search sessions by allowing the user to organise their search results on a workspace. The workspace’s usefulness is evaluated in a task-oriented and user-centred comparative experiment, involving design professionals and several types of realistic search tasks. In particular, we focus on its effect on task conceptualisation and query formulation. A traditional relevance feedback system serves as a baseline. The results of this study show that the workspace is more useful in terms of both of the above aspects and that the proposed approach leads to a more effective and enjoyable search experience. This paper also highlights the influence of tasks on the users’ search and organisation strategy

Systematic review of the behavioural assessment of pain in cats

Objectives The objectives were to review systematically the range of assessment tools used in cats to detect the behavioural expression of pain and the evidence of their quality; and to examine behavioural metrics (considering both the sensory and affective domains) used to assess pain. Methods A search of PubMed and ScienceDirect, alongside articles known to the authors, from 2000 onwards, for papers in English was performed. This was followed by a manual search of the references within the primary data sources. Only peer-reviewed publications that provided information on the assessment tool used to evaluate the behavioural expression of pain in cats, in conscious animals (not anaesthetised cats), were included. Results No previous systematic reviews were identified. One hundred papers were included in the final assessment. Studies were primarily related to the assessment of pain in relation to surgical procedures, and no clear distinction was made concerning the onset of acute and chronic pain. Ten broad types of instrument to assess pain were identified, and generally the quality of evidence to support the use of the various instruments was poor. Only one specific instrument (UNESP-Botucatu scale) had published evidence of validity, reliability and sensitivity at the level of a randomised control trial, but with a positive rather than placebo control, and limited to its use in the ovariohysterectomy situation. The metrics used within the tools appeared to focus primarily on the sensory aspect of pain, with no study clearly discriminating between the sensory and affective components of pain. Conclusions and relevance Further studies are required to provide a higher quality of evidence for methods used to assess pain in cats. Furthermore, a consistent definition for acute and chronic pain is needed. Tools need to be validated that can detect pain in a range of conditions and by different evaluators (veterinary surgeons and owners), which consider both the sensory and emotional aspects of pain

An explorative study of interface support for image searching

In this paper we study interfaces for image retrieval systems. Current image retrieval interfaces are limited to providing query facilities and result presentation. The user can inspect the results and possibly provide feedback on their relevance for the current query. Our approach, in contrast, encourages the user to group and organise their search results and thus provide more fine-grained feedback for the system. It combines the search and management process, which - according to our hypothesis - helps the user to onceptualise their search tasks and to overcome the query formulation problem. An evaluation, involving young design-professionals and di®erent types of information seeking scenarios, shows that the proposed approach succeeds in encouraging the user to conceptualise their tasks and that it leads to increased user satisfaction. However, it could not be shown to increase performance. We identify the problems in the current setup, which when eliminated should lead to more effective searching overall

Interactions of Generated Weather Raster and Soil Profiles in Simulating Adaptive Crop Management and Consequent Yields for Five Major Crops throughout a Region in Southern Germany

Klimaanpassung und MitigationThe ability of bioeconomic simulation modelling to realistically predict agricultural adaptation is limited by the degree of detail in crucial model components. Model robustness must be tested before localized calibrations can be applied to regions of heterogenous environmental conditions. The agent-based model FARMACTOR was used to simulate the timing of field management actions (planting, harvest etc.) in response to environmental conditions, and consequent yields of winter wheat, barley and rapeseed, spring barley and silage maize as the predominant crops in a distinct region of Germany, by linking weather data and the crop growth simulation model EXPERT-N. The integrated models were calibrated to observed experimental data and official phenological observations and then run from 1990 to 2009, forced with climate data from ERA-interim Reanalyses data which was downscaled with the Weather and Research Forecast (WRF) model to a 12 X 12 km² grid. Variability in regional soils was replicated with 10 different soil profiles mapped at 1/25,000 scale. The nature of the forcing climate data dictates temporal aggregation for analysis, so that validity is examined by comparing mean simulated planting and harvest dates and yields to official records in the area. The mean predicted planting dates are very close to observations over the period, within a few days of observations, but show less variance. Harvest dates are accurately predicted as well, within one to two weeks, and the variances are closer to observations. Predicted winter wheat yields are well simulated in comparison to observed data, but maize yields are underestimated, while winter and spring barley and winter rapeseed yields are greater than observed district ("Landkreis") yields. The degree of variance in simulated yields is acceptable in wheat, winter barley and maize, but excessive in spring barley and winter rapeseed. Cross-sectional examination of yields shows that the different soil profiles are responsible for more yield variance than simulated weather cells in all crops. While the coupled models appear accurate in predicting crop management dates and physiological development, the inaccuracy in yields in all crops except winter wheat calls into question the reliability of the integrated models when applied, as is, outside of calibration conditions. That soil parameterization is responsible for more variance than generated weather is helpful in seeking to improve performance and encouraging in terms of the method of weather generation. Reliable extension of the coupled models to include all soils in an area together with artificial spatial climatic variability may require regionalized calibration to increase crop model stability

An adaptive technique for content-based image retrieval

We discuss an adaptive approach towards Content-Based Image Retrieval. It is based on the Ostensive Model of developing information needs—a special kind of relevance feedback model that learns from implicit user feedback and adds a temporal notion to relevance. The ostensive approach supports content-assisted browsing through visualising the interaction by adding user-selected images to a browsing path, which ends with a set of system recommendations. The suggestions are based on an adaptive query learning scheme, in which the query is learnt from previously selected images. Our approach is an adaptation of the original Ostensive Model based on textual features only, to include content-based features to characterise images. In the proposed scheme textual and colour features are combined using the Dempster-Shafer theory of evidence combination. Results from a user-centred, work-task oriented evaluation show that the ostensive interface is preferred over a traditional interface with manual query facilities. This is due to its ability to adapt to the user's need, its intuitiveness and the fluid way in which it operates. Studying and comparing the nature of the underlying information need, it emerges that our approach elicits changes in the user's need based on the interaction, and is successful in adapting the retrieval to match the changes. In addition, a preliminary study of the retrieval performance of the ostensive relevance feedback scheme shows that it can outperform a standard relevance feedback strategy in terms of image recall in category search

Towards a data publishing framework for primary biodiversity data: challenges and potentials for the biodiversity informatics community

Background: Currently primary scientific data, especially that dealing with biodiversity, is neither easily discoverable nor accessible. Amongst several impediments, one is a lack of professional recognition of scientific data publishing efforts. A possible solution is establishment of a ‘Data Publishing Framework’ which would encourage and recognise investments and efforts by institutions and individuals towards management, and publishing of primary scientific data potentially on a par with recognitions received for scholarly publications. Discussion: This paper reviews the state-of-the-art of primary biodiversity data publishing, and conceptualises a ‘Data Publishing Framework’ that would help incentivise efforts and investments by institutions and individuals in facilitating free and open access to biodiversity data. It further postulates the institutionalisation of a ‘Data Usage Index (DUI)’, that would attribute due recognition to multiple players in the data collection/creation, management and publishing cycle. Conclusion: We believe that institutionalisation of such a ‘Data Publishing Framework’ that offers socio-cultural, legal, technical, economic and policy environment conducive for data publishing will facilitate expedited discovery and mobilisation of an exponential increase in quantity of ‘fit-for-use’ primary biodiversity data, much of which is currently invisible

Information scent, searching and stopping : modelling SERP level stopping behaviour

Current models and measures of the \emph{Interactive Information Retrieval (IIR)} process typically assume that a searcher will always examine the first snippet in a given \emph{Search Engine Results Page (SERP)}, and then with some probability or cutoff, he or she will stop examining snippets and/or documents in the ranked list (snippet level stopping). Prior work has however shown that searchers will form an initial impression of the SERP, and will often abandon a page without clicking on or inspecting in detail any snippets or documents. That is, the \emph{information scent} affects their decision to continue. In this work, we examine whether considering the information scent of a page leads to better predictions of stopping behaviour. In a simulated analysis, grounded with data from a prior user study, we show that introducing a SERP level stopping strategy can improve the performance attained by simulated users, resulting in an increase in gain across most snippet level stopping strategies. When compared to actual search and stopping behaviour, incorporating SERP level stopping offers a closer approximation than without. These findings show that models and measures that na\"{i}vely assume snippets and documents in a ranked list are actually examined in detail are less accurate, and that modelling SERP level stopping is required to create more realistic models of the search process