Background Including, for example, relevant previous or parallel research. Theoretical positions and hypotheses where relevant.

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1 L Representational Design Principles to Humanize Automated Scheduling Systems Full Report of Research Activities and Results A full report on the research should accompany the completed report form. The length of this should not exceed 5,000 words. The report should be a succinct, self-contained document, giving a straightforward and critical appraisal of the research in, as far as possible, non-technical language. The following standard headings should be used: Background Including, for example, relevant previous or parallel research. Theoretical positions and hypotheses where relevant. The project brought together research into representational systems from cognitive science with research on automated scheduling from computer science. Working with knowledge, in particular transforming and using information, is critically dependent on the representational systems used. The fundamental role of external representations in complex tasks is well established in cognitive science. Representations (e.g., notational systems, diagrams, iconic languages) can to a significant extent determine the difficulty of a task and will constrain the nature of the solutions to problems. In situations that involve conceptual learning the representations used may even determine how knowledge becomes structured in the mind. In our previous work we have developed an approach to the design of representations to support complex problem solving and learning that focuses on understanding the nature of the knowledge of a target domain and then inventing novel representations to encode that underlying conceptual structure. We have called this the Representational Epistemology (REEP) approach to interface design. The REEP approach aims to satisfy the multiple demands placed on representational systems by (a) human cognitive limitations, (b) the conceptual and informational structure of complex domains, (c) task and problem solving characteristics. We previously formulated principles, which specify desirable systemic properties of complex representations in two categories: (1) semantic transparency; (2) syntactic plasticity. Representations with semantic transparency will: reveal interesting patterns in information; support interpretations from multiple perspectives (e.g., functional, structural); beneficially integrate levels of abstraction; provide a coherent global interpretive scheme; clearly differentiate concepts and cases at a local level. Representations with syntactic plasticity will be generative, easier to manipulate and more compatible with human cognitive abilities and limitations. There is a growing appreciation that the benefit of automated systems can be greatly enhance by having humans judiciously interact with such systems. It is an open question how best to exploit the particular the strengths of automated systems and human cognition to offset each other s limitations. Automating complex tasks can increase safety, efficiency and the quality of solutions and can reduce the time and cost of solution generation. In the area of scheduling, an important advantage of automated systems is that they allow us to take carefully selected components of the complexity of the problem out of the hands of the user. However, providing an adequate decision support system for scheduling 16

2 has always been a difficult task. In addition to the technical difficulties given by problems, which are provably difficult, in some sense, too little attention has been paid to addressing the cognitive challenge of providing effective representations of problem data and solution information. For example, in optimisation approaches each candidate schedule is assigned a number to reflect its quality and the "optimal" solution is often taken to be the solution with the highest number. However, this ignores the very great difficulty that users have in weighting the multiple conflicting objectives of schedule generation. Recently, we have coined the term hyperheuristics for self-adjusting heuristics, which modify their behaviour or choose between a range of solution approaches depending upon the characteristics of the region of the solution space under exploration. There is clearly potential for new approaches to the design of hyperheuristics inspired by observed patterns of human interaction with heuristics or that engage human control of the selection and modification of heuristics. The project brought together these two generative areas of work together to create a new area of research at their intersection. Designing system to aid the solution of complex scheduling problems provides a difficult challenge for the study of representational systems and the application of the cognitive science of knowledge representations provides an original way to advance automated scheduling. Objectives Aims and objectives of the research and any changes to these. You should state clearly how each objective has been addressed and whether the objective has been met or not, referring to other parts of the report as required. Where an objective has not been addressed or has not been met successfully, you should state the reasons for this. This will ensure that genuine difficulties faced in the course of the research are recognised and taken into account by the evaluators. The project aimed to address two critical issues for information technology that supports working with knowledge. (1) What is the nature of the fundamental role that representations have in IT systems? (2) How can the power of automated systems for complex tasks be integrated with the flexibility and creativity of humans? The project s findings have substantially addressed both aims. The questions were addressed by focussing on six objectives: (a) The first objective was to extend and empirically evaluate our existing principles for the design of representational systems by applying them to complex information intensive tasks (examination timetabling and personnel scheduling). This has been achieved with the clear demonstration that the application of the principles of representation design proposed under the REEP approach have utility and value in the design of representations for complex information intensive problem domains (extending the principles beyond the educational domains). It has been shown that the preservation of conceptual structure in the representational schemes of the interface is critical to the design at the knowledge level. [Outputs: 4, 5, 7,11] 17

3 (b) The second objective was to design new representational systems for visualizing complex scheduling and timetabling tasks. The STARK-Exam and STARK-Roster systems have been developed for the exam scheduling and nurse rostering domains. Empirical evaluation with the systems show that they support solution improvement and promote sophisticated problem solving strategies. In addition, practicing schedulers and researchers in automated scheduling have provided positive feedback on potential value of the representations. [3, 4, 5, 7] (c+e) The third and fifth objectives were to develop tools that exploit the novel representations for interactive exploration and evaluation of scheduling heuristics and to build and evaluate a prototype system for solving scheduling problems that combine the new representations with the novel scheduling methods. Both have been successfully achieved together in the form of HuSSH workbench for constructive heuristics. Evaluations of HuSSH with practising timetables and scheduling experts has shown that HuSSH can be used not only for improving solutions using heuristics users themselves have devised but also that HuSSH supports the design and improvement of such heuristics [1, 8, 12, 13]. Given the tight integration of human and automated system achieved it was necessarily the case that both objectives had to be addressed simultaneously. (d) The fourth objective was to develop novel (hyper-) heuristics for computerbased scheduling that allow us to capture human heuristic expertise and use this expertise at a higher conceptual level than previously. Exploration of a class of heuristics that holds promise for allowing meaningful human intervention in targeted parts of the operating cycle of heuristics have been conducted [2]. (f) The sixth objective was to formulate guidelines / methodologies for the humanization of complex automated systems by the design of novel representations to support the integration of human abilities into such systems. This objective has changed with the lessons learned from the analysis of the studies on HuSSH. The complexity of the potential integration of humans with automated scheduling systems means simple guidelines for design will not be appropriate, especially because of the numbers of levels at which humans may interact with the system. Thus, we are developing a theoretical framework based on a multi-space search model of interaction with complex systems, from which design scenarios can be proposed and also evaluated. [12] Although good progress has been made with all the objectives, the final phase of journal paper writing is on going at the time of writing this report. The cause of the delay was fourfold: Peter Cowling (investigator) took up a Professorship at the University of Bradford a year into the project; Peter Cheng (principal investigator) took up a Professorship at he University of Sussex during the final year of the project and the award was transferred to Sussex; Samad Ahmadi (project research fellow) took up a lectureship at the DeMontfort University during the last year of the project. A new research assistant, Nikoleta Pappa was recruited and has had an extended period of training to understand in detail the 18

4 operation of HuSSH and the analysis methods being used. The aim is to complete and submit the four outstanding papers by the end of the year. [11-14] Methods Specific reference to methods used, including survey design, special equipment, new methods and analysis of results. The methods for the study of the representational questions and the humanisation questions are somewhat different, so will they will be considered in turn. Overall, the approach used in the project to address the representational questions involved four interrelated stages. First, the conceptual structure of the target problem domains was analysed. Second, a novel representational system for the domain was invented. Third, the representation was implemented in a software interface. Fourth, the interface was empirically evaluated. The studies with the exam scheduling and personnel rostering domains both included all the stages. The details and variations in stages will be considered. (1) The analysis for the conceptual structure of each domain began with theoretical analysis of the nature of the problem, inspection of the real datasets, and solutions obtained from experts. To identify the difficulties caused by common conventional representational schemes, existing representations and software systems for the domains were also examined. Our expert scheduler acted as an informant throughout the project and we conducted interviews with selected practising schedulers. For both domains the primary conceptual dimensions were identified. (2) The novel representations were designed by exploring the space of possible matches of representational schemes to the identified conceptual structures. The representational design principles were used to heuristically guide the search and the representations that appeared to best satisfy the principles were selected. The chosen representation for each task domain was then iteratively refined in terms of common graphical design considerations. (3) The representations were implemented in software (visual C++): STARK-Exam and STARK-Roster for the exam scheduling and the rostering domains, respectively. Close attention was paid to the details of how the functionality of the interface was supported, so as to reduce a far as possible basic interaction problems. For comparison with STARK-Exam, a conventional graphical exam scheduling system was also built with an interface based on a table format and equivalent in functionality to state-of-the-art commercial systems. Alternative versions of STARK-Roster were written with different degrees of integration of information to serve as the basis for comparisons in the experiments. (4) The evaluation of the interfaces included informal and formal studies. The informal studies involved experts, including the project s own expert, using the system and providing feedback. The formal studies were experimental investigations in which STARK-exam was compared with the conventional exam timetabling interface, or the variants of STARK-Roster compared with each other. The experimental task used in both domains was to improve an existing good solution that had been produced by an automated system or by an expert. 19

5 Global performance measures were taken, such as, solution improvement, speed of performing operations and distributions of operation types. The systems automatically logged all the users operations. A process oriented approach to probing relations between operations derived from the logs has been specifically developed to analyse the users patterns of actions in manner that is sensitive to the current and local problem solving context. From these patterns of problem solving strategies were successfully identified. The approach to studies of the humanisation questions followed a somewhat different pattern. The HuSSH system was explicitly designed as a workbench for designing and testing heuristics. The users interaction with HuSSH was conceptualised in terms of cycles of heuristic design with nested cycles of schedule creation, but procedures for design and schedule creation were left as flexible as possible. Users were given dynamically updating information about the quality of solutions, including visualisations of the contributions of different classes of violations. The STARK-Exam system was embedded in HuSSH so that user could visualise the solution state or manually improve the solution if desired. Informal and formal experiments were conducted with HuSSH. Expert schedulers and scheduling system designers in the informal experiments were given the task of finding the best possible solution to a particular problem. In the formal study participants were asked to design new heuristics and to test them. In addition to global measures of performance, details of the designs of heuristics were recorded and all the users actions on HuSSH automatically logged. Users patterns of interactions occurred at many different levels and were complex. Thus graphical visualisations have been developed to display the patterns of users operations as a means to understand how they are switching between the different problem spaces that are available in HuSSH. Results A report of the results of the project and analyses to date. The survey of the representations currently used in the two target domains has provided some interesting findings. Interfaces for the domains all have a primary table that is used to coordinating information contained in secondary tables or lists that hold additional information. A common feature of the representations is their inconsistent use of the same representational features for distinct classes of information, or different graphical schemes for information of the same generic type. The existing displays do not conform well to the representational design principles. The structure of the interfaces is likely to be due to historical accident rather than deliberate design. These designs probably endure through historical momentum rather than fitness for purpose or explicit choice. The analysis of the conceptual structure of the domains has revealed their underlying semantic complexity. The exam scheduling domain can be characterised in terms of spatial-temporal resources and demands and nested set theoretical relations involving students within exams, exams within slots, and slots within periods and rooms. The nurse rostering domain can be 20

6 characterised in terms of matching individual requirements and the demands of shifts under multiple constraints, ranging from the values of basic properties through to more complex sequential, arithmetic and set theoretic relational constraints. Although both domains are scheduling problems involving the assignment of one type of entity to another under constraints, it has been shown they differ substantially in terms of their underlying conceptual structure. Hence, distinct graphical schemes will be needed to effectively preserve the unique conceptual structure of each domain. The novel representations were designed to preserve the identified conceptual structures. STARK-Exam used a nested spatial-temporal scheme to provide a thoroughgoing interpretive framework within which set theoretic, sequential and order constraints could be effectively embedded using a combination of a containment metaphor and quantified entity connection scheme. STARK-Roster combined a person-temporal scheme with a generic coding for degrees of constraint satisfaction across all of the different classes of constraints. These representational schemes stand as design exemplars of how equivalent conceptual dimensions from quite different classes of problem may be encoded. The STARK-Exam and STARK-Roster interfaces are briefly presented in the appendix. In the evaluations the users of STARK-Exam were able to improve solutions that were generate by an industrial strength scheduling heuristic. In the direct comparisons with the STARK-Exam users performed significantly and substantially better than the users of the conventional interface. The analysis of problem solving strategies show that STARK-Exam supported sophisticated recursive strategies in which sequences of coordinated operations were used to remove violations that could not be resolved by simple reallocation. The users of the conventional interface used a trial and error approach or when they did more sophisticated sequences of operations they were much slower than the STARK- Exam users. They also did sequences of operations that did advance the solution, but there merely served to manage the complexity of the problem. The behaviour of the STARK-Exam users tended to be homogenous within each individual s run, with similar behaviour across the whole group. The conventional interface users showed heterogeneous behaviour, with each individual moving between a range of (mostly unsuccessful) strategies, and a wide variety of strategies in the test group. This suggests that the design of the STARK-Exam interface is exerting strong normative influence on the users a manifestation of representational determinism as found in the simple problem solving domains of cognitive science. The novel representation for this domain is effective: it improves performance and transforms the nature of the user s problem solving activity. This provides evidence supporting the validity of the representational design principles. The evaluations of the STARK-Roster system shows that it effectively supports problem solving, with novice users of the system demonstrating an ability improve a solution generated by an expert scheduler, after brief training and twenty minutes of on a practice problem. Although STARK-Roster includes zoom and perspective selection and switching tools, the users generally chose 21

7 not to use them preferring to view the solution at a large scale and showing all of the classes of constraints simultaneously in the interface. Analysis of the combinations of violations that the users choose to resolve indicated they often focussed on cases with multiple coincidental violations. The analysis of the patterns of problem solving strategy showed that the users were doing related sequences of operations in a sophisticated fashion. STARK-Roster is visually complex, but the underpinning coherent interpretive scheme allows users to adopt an attention switching approach to focus on particular perspectives without the need to split that information in to separate views, as done in conventional interface designs. The success of STARK-Roster provides further evidence that the REEP approach to representational design is effective. In general the users of the HuSSH heuristic design workbench were able to use the system to generate good solutions to the examinations schedules. In the lab based evaluations of HuSSH the users were asked to think up their own novel heuristics and they then used HuSSH to test whether the heuristics were effective or not. The users suggested a wide variety heuristics. At the simplest end of the spectrum there were basic constructive heuristics in which the selection weights of exams, rooms or periods were tuned to obtain better solutions. More complex approaches included the sampling of different permutations of selection heuristics or incrementally augmenting a successful heuristics with new selection rules. This proved to be quite effective. HuSSH has the facility to unallocate exams based on the weights of the violations and one user adopted the strategy of unallocating and reallocating exams with particulars types of constraints in turn. Another imaginative strategy one user tested involved two stages: (1) incremental iterative construction, in which the number of available periods was gradually increased as the numbers of allocated exams increased; (2) iterative repairing, in which the violation type that was most severe was reallocated but with the greatest weight placed on that violation type in the reallocation. Moreover, users were able to integrate the heuristic they had designed with periods of direct manual intervention. The evaluation of HuSSH clear demonstrates that it is possible to integrate human abilities with the power of automated scheduling, provided an appropriate visualisations and set of tools are provided. Many of the users were in effect implementing hyperheuristics in HuSSH. Effective human intervention may occur at different levels, including: the manual editing of solutions; the partial and incremental rescheduling; focussed parameter turning in relation to a specific class of violation; invention and exploration of novel heuristics. The project has specifically investigated a class of heuristic inspired by the studies with HuSSH, which has interesting potential for more focussed intervention of humans in the automated scheduling process. Perturbation based neighbourhood search heuristics have been explored as an alternative to simple constructive heuristics. The approach may be considered as the automated search of two spaces. The first is the space of weighting parameters for given permutations of selection heuristics and the second space consists of the permutations themselves. The weights can be sensibly searched using a straightforward fully automatic sampling and weight-set selection approach. 22

8 Although a random sampling approach to permutations of selections can be used, it would make more sense to have have human schedulers to seed that search space with permutations based on their understanding of the nature of the problem and dataset. These studies have shown that the way in which automated systems and humans may be integrated is not only complex but diverse. Rather than attempt (naïvely) to derive highly context dependent guidelines for the humanisation of automated systems, we have decided instead to begin developing a generic theoretical framework for such design. The approach draws upon studies in cognitive science on the process of discovery, which characterises the creative process as mutually constrained search of multiple problem spaces. The model can be extended to the humanisation of automated systems by identifying the particular spaces that humans and machines can most effectively search and by considering how to coordinate the interaction of the searches so that they mutually constrain each other. The analysis of patterns of search by the users of HuSSH is currently being analysed to provide a demonstration of the applicability of the framework. If successful, the multi-search space framework may be used to derive design guidelines that encompass the inherent complexity and the different levels of interaction. Activities To include related activities such as conferences, networks etc. The project ran two timetabling competitions in parallel at the fourth Practice and Theory of Automated Timetabling (PATAT) conference, which was held at KaHo St.-Lieven, Gent, Belgium in August 2002 ( The PATAT International Series of Conferences on is held bi-annually as a forum for both researchers and practitioners of timetabling to exchange ideas. The first competition used the STARK-Exam system for manual examination solution improvement and the competition contestants attempted improve a full scale examination solution. The objective was to optimise the quality of an exam according to a given evaluation function. The other competition used the HuSSH workbench for scheduling heuristic design. The contestants for this competition designed new heuristics to generate the best solution for a full-scale examination timetable from scratch. The aim of the competitions was to disseminate the work of the project beyond academic researchers (and also to other academics). The conference was attended by about 100 delegates, including representatives from software companies in this sector and actual administrators or timetabling officers (e.g., NEC Corp., ORTEC Consultants BV, SAP Portals Europe GmbH, Gower Optimal Algorithms Ltd.) The results have been presented at a wide range of industrially-oriented seminars. Professor Cowling has presented these results at invited seminars at Vidus Ltd. (a large scheduling company) in April 2004, the Yorkshire and Humerside Operational Research Group in November 2003, the Faraday Packaging conference in October 2003 and the IEE Yorkshire branch in April

9 The project participated in the PACCIT workshop Understanding your users in November, 2003, at The Royal Society, London. A talk entitled Diagrams to Unlock Knowledge was presented along with a rolling slide show and software demonstrations. The workshop was attended by commercial, industrial and academic parties. Outputs Publications, other dissemination, datasets (with confirmation of deposit at the Data Archive where applicable), software etc. These should not duplicate the Regard return but may be used to highlight particularly important outputs. [1] Ahmadi, S., Barone, R., Burke, E., Cheng, P.C-H., Cowling, P.I., McCollum, B. (2002). Integrating human abilities and automated systems for timetabling: A competition using STARK and HuSSH representations at the PATAT 2002 conference. In E. Burke & P. Causmaecker (Eds.), Proceedings of the 4th international conference on the practice and theory of automated timetabling (PATAT 2002), KaHo St.-Lieven, Gent, August 21-23, 2002, pp (ISBN ) [2] Ahmadi, S., Barone, R., Cheng, P., Cowling, P., McCollum, B. (2003) Perturbation based variable neighbourhood search in heuristic space for the examination timetabling problem. Proceedings of the 1st Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA 2003), Vol 1, pp (ISBN ) [3] Barone, R., & Cheng, P. C.-H. (2004). Representations for problem solving: on the benefits of integrated structure. In E. Banissi, K. Börner, C. Chen, et al. (Eds.), Proceedings of the 8th International Conference on Information Visualisation (pp ). Los Alamitos, CA: IEEE. (ISBN ) [4] Barone, R., Cheng, P. C.-H., Ahmadi, S., & Cowling, P. I. (2003). The strategic influence of conceptual structure in graphical interfaces for scheduling. Interactive Graphical Communication Workshop 2003 (pp. 7-20). Queen Mary: University of London. [5] Cheng, P. C-H., & Barone, R, (2004). Representing Rosters: Conceptual Integration Counteracts Visual Complexity. In A. Blackwell, K. Marriott & A. Shimojima (Eds.), Diagrammatic Representation and Inference: Third International Conference, Diagrams 2004, (pp ). Berlin: Springer-Verlag. (ISBN X) [6] Cheng, P. C.-H., Barone, R., Ahmadi, S., & Cowling, P. I. (2003). Integrating human abilities with the power of automated scheduling systems: Representational epistemological interface design. In D. Kortenkamp & M. Freed (Eds.), Human Interaction with Autonomous Systems in Complex Environments: Papers from the 2003 AAAI Spring Symposium (SS-03-04) (pp ). Menlo Park, CA: AAAI Press. (ISBN ) [7] Cheng, P. C.-H., Barone, R., Cowling, P. I., & Ahmadi, S. (2002). Opening the information bottleneck in complex scheduling problems with a novel representation: STARK diagrams. In M. Hegarty, B. Meyer & N. H. Narayanan (Eds.), Diagrammatic representations and inference: Second International Conference, Diagrams 2002 (pp ). Berlin: Springer-Verlag. (ISBN ) [8] Cowling P.I., Ahmadi S., Cheng P. C and Barone R. (2002). Combining Human and Machine Intelligence to Produce Effective Examination Timetables", In L.Wang, K. Tan, C. Furuhashi., J- H Kim, and X. Yao (Eds.), Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL2002), Singapore; (pp ). (ISBN ) 24

10 [9] McCollum, B., Ahmadi, S., Burke, E., Barone, R., Cheng, P., Cowling, P. (2002). A review of existing interfaces of automated examination and lecture scheduling systems. In E. Burke & P. Causmaecker (Eds.) Proceedings of the 4th international conference on the practice and theory of automated timetabling (PATAT 2002), KaHo St.-Lieven, Gent, August 21-23, 2002, pp (ISBN ) [10] Trafton, J. G., Shah, P., Freedman, E. G., Kirschenbaum, S., & Cheng, P. C.-H. (2002). The Cognition of Complex Visualizations. In Proceedings of the Twenty-Fourth Annual Conference of the Cognitive Science Society (pp ). Mahwah, NJ: Lawrence Erlbaum. (ISBN X/ ; ISSN ) [11] (In preparation). Knowledge level interface design for complex problem solving: Representational determinism and transformation of strategies. Submit to Human Factors or IJHCS. [12] (In preparation). Integrating human abilities and computational capabilities: humanising automated scheduling systems. Submit to Communications of the ACM. [13] (In preparation). Semantically transparent approach to representing knowledge: interfaces for examination scheduling and personnel rostering. Submit to Journal of Information visualisation. [14] (In preparation). Effects of information integration in interface design for a scheduling problem. Submit to Human Computer Interaction. Impacts Are there instances of the research results being used or applied outside of the project, including commercial exploitation, either actual or proposed? Please detail any links with, or interest shown by, users of the research. The project has attempted to commercialise the design of the STARK-Exam interface with the commercial organisation that took over Optime, which was the original commercial collaborator on the project. The negotiations with that software development company reached the stage of drafting and revising a license. However, the board of directors of the company chose not to pursue the development for commercial reasons. Future Research Priorities Are there lines of research arising from this project which might profitably be pursued (not necessarily with ESRC funding)? Funded lines of research spawned by the project: The project has demonstrated that the Representational Epistemology approach to knowledge level interface design is applicable to complex information intensive event and personnel scheduling problems. Other areas of scheduling, and also operations research, may also be amenable to the approach. Peter Cheng holds was awarded PACCIT-Link project, 25

11 which began in 2004, to apply the approach to dynamic production processes in the areas of bakery scheduling. The project has highlighted the potential of considering event scheduling in terms of higher-level components and distributional characteristics of whole datasets that are more meaningful to users. David Ranson is investigating the design of representations to support such knowledge based scheduling at the University of Sussex, supported by an Informatics Department Studentship. Other lines of research that arise from the project include: Combining the event and personnel scheduling components of STARK- Exam and the STARK-Roster in a single integrated representation for class (lecture / teacher) scheduling. Application of the multi-problem space search model of system humanisation to other classes of automated systems, such as dynamic control of processes. Extension and generalisation of the contextual techniques developed in the project for the analysis behaviour logs and the extract patterns of operations relating to problem solving strategies. Extension of representational design ideas for building and solving models of problems which are poorly defined, with multiple, conflicting objectives. 26

12 Appendix STARK-Exam Interface Yellow (light) icons represent exams and blue (dark) icons represent space-time slots. The height of the exam icon indicates the number of students sitting the exam. The width of the exam icon indicates its duration. In a similar fashion the height of the space-time slot expresses its room capacity and its the width expresses the duration that it is available. Columns of blue icons represent individual time-slots ordered along the horizontal axes and rows of blue icons represent a room over the cause of the examination period. Violations of resources occur emergently through the expression of exceeded time-slot boundaries along either the horizontal (period availability) or vertical axes (room capacity) of the diagram. The size of the boundary over-flow indicates the magnitude of the resource violation. Intersection violations (clashes, consecutive examinations) are represented by lines that touch exams at a point on the vertical side of the exams icon to indicate the size of the student intersection. 27

13 STARK-Roster Interface Main columns represent days, sub-columns are shifts in a day. Rows are particular nurses. The subdivisions within each shift represent different nurse grades and skills. Each row consists of a pipe. A plug in the pipe is an assignment of a nurse to a shift. A shift preference is shown by an annulus around the pipe: plain (with rounded corners) for an on shift preference and with cross for an off shift preference. Degree to which requirements are satisfied uses a simple colour scheme: grey in the desired range; white insufficient; black excess. Hence the regions in the circles show severe under allocation (left) or over allocation (right). ŅPipeÓ Shifts Grade / skill requirements Off shift preference On shift preference Shift assigned Large scale view: users preferred to work at this scale and coped easily with this degree of visual complexity. 28