On the efficient solution of a multiserver system with two reattempt orbits In communication networks that guarantee seamless mobility of users across service areas, reattempts occur as a result of user behavior but also as automatic retries of blocked handovers. A multiserver system with two reattempt orbits is obtained when modeling these networks. However, an exact Markovian model analysis of such systems has proven to be infeasible and resorting to approximate methods is mandatory. To the best of our knowledge all the existing methods are based on computing the steady state probabilities. We propose another approach based on the relative state values that appear in the Howard equations. We compare the proposed method with the most well-known methods appeared in the literature in a wide range of scenarios. The results of the numerical evaluation carried out show that this solution outperforms the previous approaches in terms of both accuracy and computation cost for the most common performance parameters used in retrial systems. The retrial phenomenon appears in multiple situations in telecommunications, computer networking as well as in many other fields. An in-depth study of the bibliography on retrial queues can be found in [1] . In this paper we focus our attention on a generic communication network that guarantees seamless mobility to its customers by means of a cellular architecture. In these types of networks, the network coverage area is divided into services areas, known as cells and customers can move across different cells of the network. When a customer with an active communication moves from one cell to another a socalled handover procedure is executed to allocate the necessary resources in the new cell and release the unused resources in the former cell. Nowadays, perhaps the most widespread and popular example of this type of network is the telephone cellular networks -2G and 3G. But the current perspective is that in the near future a variety of technologies fitting into this category will be in place, e.g. Mobile IP, IEEE 802.16 [2] -commercially known as WiMAX -which has recently incorporated mobility into the standard [2] and IEEE 802.20 [3] (Mobile Broadband Wireless Access, MBWA).. The phenomenon of repeated attempts in telecommunication systems has been studied, at least, since the 50s [4] . However the scenario under study in those works is that of a classical telephone network where the effect of reattempts is due to the customers' behavior. In contrast, this paper deals with the case in which reattempts appear not only when a customer is blocked but also when a handover is blocked. An example of technology that enables handover reattempts is GSM [5] . To the best of our knowledge, the first and only paper that has considered the effect on network performance of both types of reattempts simultaneously is [6] . Now, in this paper we refer to the former as redials and to the latter as (automatic) retrials, while we use the concept of reattempt to refer to any of them. Blocked handovers will be automatically retried until a reattempt succeeds or the user moves outside the handover area. In the former case the session will continue without the user noticing any disruption, while in the latter the session will be abruptly terminated. In contrast, persistence of redials depends on the user patience and an eventual abandonment results in session setup failure. Another difference is that the maximum number of unsuccessful automatic retrials is set by the network operator while redials are affected by the randomness of human behavior. Therefore, both types of reattempts have different characteristics and as a consequence two separate retrial pools have to be considered in the analysis of the system.. The modeling of repeated attempts has been the subject of numerous investigations [7] [8] [9] . Two functional blocks are typically distinguished in models which consider reattempts: a block that accommodates the servers and possibly a waiting queue, and a block where users that reattempt are accommodated, usually called reattempt orbit. More concretely, the mathematical model of the system under consideration is a multiserver retrial queue. The most important characteristics of the state space of this model are its two infinite dimensions due to the orbits and the non-homogeneity along them as the reattempt rates depend on the number of users in the orbits. It is known that the classical theory [10] is developed for random walks on the semi-strip {0, . . . , C }×Z + with infinitesimal transitions subject to conditions of space-homogeneity. Therefore it is clear that in this case it is necessary to resort to approximate methods, even in a single reattempt orbit case. These methods are usually grouped into three categories: approximations, finite truncated methods and generalized truncated methods [11, 12] . Although all the mentioned categories are in fact approximations, the first category is usually devoted to methods that can be useful only in a certain domain of the system parameters or in special extreme cases [12, Section 2.8], [13] . Therefore we will direct our attention only to finite and generalized truncated methods. The finite truncated methods replace the original infinite state space by a finite one, where steady state probabilities can be computed [14] . On the other hand, generalized truncated methods replace the original infinite state space by another infinite but solvable state space. This last type of method usually outperform the other two types [15] , offering a good tradeoff between precision and computational complexity.. All the approaches presented so far rely on the numerical solution of the steady state Kolmogorov equations of the Continuous Time Markov Chain (CTMC) that describes the system under consideration. Very recently, however, an alternative approach for evaluating infinite state space Markov processes has been introduced by Leino et al. [16] [17] [18] . The new method, named Value Extrapolation (VE), does not rely on solving the global balance equations, but considers the system in its Markov Decision Process (MDP) setting and solves the expected value from the Howard equations written for a truncated state space. So far VE has been applied to simple retrial systems, being able to obtain very promising results in comparison with the most widespread approximation methods used in the solution of retrial systems [19] .. The main objective of this work is to tailor the VE method to a system with two reattempt orbits and compare its performance with the performance of other possible approximate methods. This performance evaluation is done in a cellular network scenario that guarantees seamless mobility to its users. We conclude that VE greatly outperforms the rest of the methods throughout a wide range of scenarios not only in terms of accuracy, but also in terms of computation cost, so its use is highly recommendable.. The rest of the paper is structured as follows. First, we describe the cellular network under study and its associated model, focusing on the reattempt behavior under consideration. In Section 3 we enumerate and explain the main features of the methods we compare VE with. Section 4 is devoted to the description of VE and how it has been applied to the model under study. A numerical study is performed in Section 5 and finally, a summary of the paper and some concluding remarks are given in Section 6. In mobile communication systems like cellular networks, Mobile IP or the recently defined IEEE 802.16e and IEEE 802.20 networks, mobile operators must guarantee seamless mobility to its customers. In these networks, repeated attempts occur due to user redials when their session establishments are blocked and also due to automatic retries when a handover fails. The impact of both phenomena plays an important role in the system performance and, therefore, it should not be ignored. The Markovian model describing such a complex network is a multiserver retrial system that presents space-heterogeneity along two infinite dimensions. However, when the number of servers is higher than two the absence of closed-form solutions for the main performance characteristics can be emphasized, so it is mandatory to develop approximate methods. To the best of our knowledge, all the methods studied in the literature to solve these systems are based on their steady state probabilities. In this paper we propose an alternative method based on a different metric: the relative state values and the Howard equations that relate them. This method performs an efficient truncation of the state space, because the relative state values just outside the truncated state space are extrapolated using some known relative state values.. We have compared the proposed method with the most well-known approaches appeared in the literature so far. The results show that the proposed method greatly outperforms previous approaches not only in terms of accuracy, but also in terms of computation cost. Moreover, we have shown that in some scenarios the proposed method is the only one that is able to guarantee a certain accuracy. For all those reasons the proposed method is highly recommendable to solve these types of systems.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A Study on the Effects of Routing Symbol Design on Process Model Comprehension Process modeling grammars are used to create models of business processes. In this paper, we discuss how different routing symbol designs affect an individual's ability to comprehend process models. We conduct an experiment with 154 students to ascertain which visual design principles influence process model comprehension. Our findings suggest that design principles related to perceptual discriminability and pop out improve comprehension accuracy. Furthermore, semantic transparency and aesthetic design of symbols lower the perceived difficulty of comprehension. Our results inform important principles about notational design of process modeling grammars and the effective use of process modeling in practice. Process models have been recognized as an effective means for documenting and communicating business processes, especially as a means for helping to discuss different viewpoints of stakeholders in projects such as the re-design of business processes [61] or the analysis and design of process-aware information systems [45] . Indications that process models indeed make a solid contribution in this area are, for instance, provided through a study of a large number of redesign projects [26] .. Process models are created using process modeling grammars -sets of graphical symbols and rules describing how to connect the graphical symbols [78] . These symbols express relevant aspects of business processes, such as the tasks that have to be performed, the actors that are involved in the execution of tasks, relevant data, and, notably, the control flow logic that describes the logical and temporal order in which tasks are to be performed. In essence, the control flow logic of a business process defines those points in the process where parallel or alternative paths might be taken, or where such paths merge. Such routing points characterize the convergence or divergence of process flows.. In process modeling grammars, convergence or divergence semantics are typically expressed through grammatical symbols named "Gateways", "Connectors, or "Splits" and "Joins" [e.g., 62, 74] . These routing symbols have been subjected to much academic debate. For instance, some scholars have argued that these symbols are ill-defined from a formal perspective [e.g., 74]. They have also been found to be a key reason for modeling errors such as violation of deadlock and synchronization rules [24] , and further argued to lead to understandability problems with practitioners [35] .. While all available process modeling grammars support the expression of convergence or divergence semantics in a business process, they utilize different visual symbols for doing so. This difference is crucial importance for the quality of a grammar. In other domains, it has been found that the form of visual information representation can have a significant impact on the efficiency of information search, explicitness of information, and problem solving [28] , the comprehension and recall of graphical models [11, 41] and even perceived usability [67] .. Our objective in writing this paper, therefore, is to develop insights about the role of routing symbol design in process modeling grammars. We study how model users understand models created with different visual routing symbol designs by drawing on a theory of effective visual notations [39] . We examine four principles of routing symbol design (perceptual discriminability, pop out, semantic transparency and aesthetics) that should lead to improved process model comprehension. We then present an experiment that tests the impact of the four principles of routing symbol design on process model comprehension in terms of accuracy, efficiency and perceived difficulty. The results demonstrate that the symbol design principles affect comprehension accuracy and difficulty in different ways. Comprehension efficiency is not affected by symbol design.. We proceed as follows. First, we review the literature on factors that influence the cognitive load of process model comprehension tasks. We then discuss relevant theoretical considerations pertaining to the visual design of routing symbols in process models and identify four relevant design principles.. Next we describe our research model and the experimental design of the study. We then present our data analysis and results. After that, we discuss the results and limitations. We conclude by summarizing the substantive as well as methodological contributions of this research. Our study provides empirical evidence of the importance of symbol design on (process) model comprehension. We found that notational characteristics such as perceptual discriminability and pop out are significantly associated with perceived cognitive load and model comprehension accuracy but not comprehension efficiency.. In a broader sense, the results provide evidence for the utility of the theory of effective visual design of notations to the study of process modeling in practice and the management of process modeling initiatives in practice. In turn, our research adds to the growing body of experimental research on conceptual modeling practices, and adds to the inventory of relevant theories, complementing relevant, established principles based on ontological considerations [47] , multimedia learning considerations [18] and secondary notation considerations [58] . The cumulative tradition of research of these studies, in turn, advances our understanding of the issues and challenges in an important field of information systems practice, the effective use of modeling notations for the analysis and design of organizational and technological systems. Our empirical study set out to test the influence of routing symbol design on process model comprehension in terms of accuracy, efficiency and perceived difficulty.. From a general perspective, the study reported in this paper extends research into the development of a validated notational design theory for modeling grammars. Most notably, we provide a first operationalization, measurement and test of the theory of visual notations by Moody [39] .. The results obtained provide support for the nomological validity of Moody's design principles. We observed different levels of significance for our hypotheses on the four design attributes of routing symbols. In particular, pop out and perceptual discriminability showed a stronger effect on process model comprehension than semantic transparency and aesthetics. One possible explanation can be that pop out and perceptual discriminability of visual symbols are dimensions that directly relate to early stages of neural processing; differences in form of symbols can even be processed pre-attentively [79] .. Therefore, they have a more direct effect on cognitive load involved in model comprehension tasks. It is not surprisingly that results are similar for both characteristics as they are closely related; symbols that are highly discriminable will also be perceived easily and would be rated higher on the pop out scale. In contrast, semantic transparency and aesthetics relate to later stages of the perceptional processing. They reflect a subjective impression of the quality of the symbol design, which is not directly related to the perceptual effectiveness in the cognitive task. We originally postulated that aesthetic design might have an influence on model comprehension due to affective responses, and semantic transparency because of easy associations with existing knowledge structures which would enable cognitive offloading. Both modes of action are more likely to depend on individual graphic preferences and prior experiences stored in long-term-memory in comparison to the pre-attentative perception processes as reflected in pop out and perceptual discriminability.. Turning to the three different dimension of process model comprehension considered, we found that the effects of symbol design perceptions were not equally strong on the different dependent variables.. Most notably, there was no effect on the comprehension efficiency. On the forefront, this result suggest that secondary notation effects (visual design choices) do not impact interpretational efficiency [8] , viz., on the resource commitment required to gain a faithful understanding of a model.. Another interpretation of that result is that participants could freely choose how much time they wanted to spend, and therefore time spent could also reflect their motivation to solve the comprehension tasks. In general, there is always a tradeoff between time spent and correctness of solution in cognitive tasks (referred to as speed-accuracy tradeoff; e.g. [4] ). So, as speed was not a set target, participants could maximize accuracy if they wanted to.. Our results regarding comprehension efficiency is in line with other conceptual modeling experiments to a certain extent. For instance, Batra and Davis [2] found no time differences when investigating performance differences between novices and experts, although there was a significant difference in quality of the outcome. Also Reijers et al. [58] found that the treatment "color highlighting" had a significant effect on understanding accuracy, but not on understanding speed. In turn, we believe that our findings, coupled with the body of work to date, clearly point to a gap in understanding the reasons for differences in model comprehension efficiency, and what the consequences are for the effective use of conceptual models for systems analysis and design.. Regarding perceived cognitive difficulty, we note that the reported effects of our independent variables on perceived control flow comprehension difficulty were similar to those on comprehension accuracy but somewhat different from those on perceived cognitive load of the task as a whole. These findings suggest that the perceived control flow comprehension difficulty scale measures objective comprehension difficulty more closely, while perceived cognitive load might reflect a more subjective rating of the general task setting.. Our experimental setting also allowed us to clarify whether notational efficiency is an object property and therefore characteristic of any notation, or dependent on user evaluations. Our results indicate that individual ratings of symbol design were relevant for process model comprehension over and above the actual design of the symbols. Several theories can assist in providing an explanation for this result.. First, research on perception demonstrated in various ways how individual's preferences and motivational states can impact visual processing; so to say people "see what they want to see" [1] .. Although most perceptional processes are bottom-up (the brain turns information from sense organs as eyes into a perception), still, top-down influences (driven by higher-level cognitive processes as the users attitude towards the symbols used) can have a great impact and can lead to perceptional biases (e.g. hills appears steeper than they actually are) or even phenomena such as unattentional blindness [65] . In such a case, a negative first impression of the symbols' design could lead to higher cognitive effort in the perception process needed for solving the comprehension tasks, leading both to lower performance and lower symbol evaluation. Additionally, differences in users' judgments of the symbols as well as in actual performances could reflect the fact that the efficiency of visual perception can vary significantly between individuals (see e.g. [77] ).. In addition to interpretations on the perceptional point of view, our results can also be interpreted through the lens of motivational theories. Research has shown that individual attitudes as achievement motivation or subjective difficulty mediate the relationship between objective task difficulty and performance [9, 20] . For instance, if individuals perceive increased task difficulty, they usually invest higher mental effort to protect performance as long as the tasks doesn't seem impossible to them. So, worse symbol design making the task more difficult per se, could not only lead to a performance loss, but also to an increase of mental effort in motivated participants resulting in similar performance of the experimental groups. However, those individuals who would have had the subjective impression that the symbol design was bad could have been demotivated and performed worse. The evidence in the present analysis is too weak for any real conclusions regarding this issue, however. Future research could include the measurement of intrinsic motivation to clarify the mechanism why individual perceptions of symbol design have a stronger influence on process model comprehension than the symbol design itself.. Finally, we note that our results confirm the relevance of secondary object attributes (perceptions of primary attributes) to understanding object-related behaviors [14] . Recker et al. [55] showed how perceptions of process modeling grammar primary notation characteristics determined behavioral evaluations of the process modeling grammar, such as perceived usefulness and perceived ease of use.. While they found that both primary and secondary (perceptual) attributes of the primary notation of the grammar mattered to these evaluations, our results show that in terms of secondary notation, the secondary attributes are important over and above the primary attributes of visual design.

O O O O O O O O O O O O B B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O B I O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


VDM semantics of programming languages: combinators and monads Abstract. The Vienna Development Method (VDM) was developed in the early 1970s as a variant of denotational semantics. VDM descriptions of programming languages differ from the original Scott-Strachey style by making extensive use of combinators which have a fixed operational interpretation. After recalling the main features of denotational semantics and the Scott-Strachey style, we examine the combinators of the VDM specification language, and relate them to monads, which were introduced more than 15 years later. We also suggest that use of further monadic combinators in VDM could be beneficial. Finally, we provide an overview of published VDM semantic descriptions of major programming languages. The Vienna Development Method, VDM, is a major framework for the formal specification and rigorous development of software systems. In this paper, we focus on the use of VDM for semantic description of programming languages, which was the original motivation for the framework.. VDM evolved from the operational semantics framework known as VDL, the Vienna Definition Language [Weg72] , in the early 1970s [Jon01] . The main change in the transition from VDL to VDM was the adoption of the fundamental principles of denotational semantics, which had already been established by Dana Scott and Christopher Strachey [SS71] .. One of the innovations in the VDM style of denotational semantics was the introduction of a number of combinators having a fixed operational interpretation. We shall see that the combinators introduced in VDM for the definition of PL/I in 1974 [Jon01] are closely related to the monadic style of denotational semantics, which was introduced by Eugenio Moggi only in 1989 [Mog89] . The VDM combinators were first defined to give a side-effect monad, and then redefined to give a monad that also supports exception raising and handling-essentially by using a monad transformer. In the later Meta-IV and VDM-SL versions of VDM, however, a seemingly minor difference in the definitions of the combinators meant that they no longer provided an exception monad.. In fact Scott and Strachey had already introduced combinators that determine a side-effect monad in their seminal paper in 1971 [SS71] . But after the introduction of continuations in 1974 [SW00] , combinators were generally avoided in the Scott-Strachey style, since denotations could be expressed easily enough using the corresponding patterns of λ-abstraction and application.. The contribution of this paper is elucidation of the relationship between various styles of denotational semantics that were introduced in the 1970s and 1980s. Since readers cannot be assumed to be familiar with the details of these styles, we shall start by giving an introductory overview of each, recalling the main concepts and notation and highlighting the distinguishing features: Sect. 2 recalls the fundamental principles of denotational semantics; Sect. 3 illustrates the original Scott-Strachey style adopted in denotational descriptions at Oxford, both before and after the introduction of continuations; Sect. 4 illustrates the VDM style, explaining the main differences between it and the Scott-Strachey style; and Sect. 5 presents the concepts and notation used in the monadic style of denotational semantics. Section 6 then considers the relationship of monads both to the Scott-Strachey style and to the VDM style; it also examines the possibility of using monadic notation to a greater extent in VDM. Section 7 gives an overview of published VDM semantic descriptions of major programming languages, and proposes to establish an online repository for semantic descriptions of programming languages in all frameworks. Section 8 concludes by summarising the main points. This is a revised and extended version of a paper published in the Bjørner-Zhou Festschrift [Mos07] . The main changes are as follows: detailed definitions of the mentioned monad transformers have been added in Sect. 5; the previous Sect. 5.1.3 is now Sect. 6, and a suggestion for how an exception monad could be defined in Meta-IV has been added; and the main contribution of the paper has been made more explicit. The fundamental principles of denotational semantics were established by Scott and Strachey at Oxford in the early 1970s. VDM adopted these principles, but also introduced some innovations: in particular, VDM made much greater use of combinators than was usual in the original Scott-Strachey style. Significantly, each combinator in VDM has a fixed operational interpretation, whereas its definition in λ-notation can vary; see also [Mos77] . We have seen that some of the VDM combinators introduced in the early 1970s correspond directly to operations provided in the monadic style of denotational semantics, which was developed at the end of the 1980s; moreover, the way their definitions vary corresponded to the lifting of operations by particular monad transformers.. VDM semantic descriptions of some major programming languages have been published, including PL/I, Algol 60, Pascal, Ada, and Modula-2. They are valuable sources of examples of how to describe a wide range of programming constructs using VDM, and deserve to be much more easily accessible to researchers and students than at present; including them in the proposed online repository of semantic descriptions would not only make them electronically available, but should also allow searching for descriptions of particular kinds of constructs.

B O O O O B O B O O O O O B O O O O O O O O O O B I B O O O O O O O O O O O O O O O B O O O O O O O O O O O O B I O O O O O O O B O O B O O O O O O B O O O O O O O O O O O O O O O O B O B O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O B I O O O O O O O O O O O O O O O O O O O B O O B I O O O O O O O B O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O B O O O O O O O O O O B O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Foundations for Modeling University Curricula in Terms of Multiple Learning Goal Sets Abstract-It is important, but very challenging, to design degree programs, so that the sequence of learning activities, topics, and assessments over three to five years give an effective progression in learning of generic skills, discipline-specific learning goals and accreditation competencies. Our CUSP (Course and Unit of Study Portal) system tackles this challenge, by helping subject teachers define the curriculum of their subject, linking it to Faculty and institutional goals. The same information is available to students, enabling them to see how each subject relates to those goals. It then gives additional big-picture views of the degree for the academics responsible for the whole degree, including the ability to easily assess if a degree meets accreditation requirements. CUSP achieves this by exploiting a lightweight semantic mapping approach that gives a highly flexible and scalable way to map learning goals from multiple internal and external accrediting sources across the degree. We report its validation as used in a live university environment, across three diverse faculties, with 277 degrees and 7,810 subject sessions over a period of three years. Data from this evaluation indicates steady improvement in the documentation of the relationships between subjects, assessments, learning outcomes, and program level goals. This is driven by the reporting tools and visualizations provided by CUSP, which enable program designers and lecturers to identify parts of the curriculum that are unclear. This improved documentation of the curriculum enables more accurate and immediate quality reviews. Key contributions of this work are: a validated new approach for curriculum design that helps address the complexity of ensuring learners progressively develop generic skills; and a validated lightweight semantic mapping approach that can flexibly support visualizing the curriculum against multiple sets of learning goal frameworks. U NIVERSITY degree programs typically aim to build learners' generic skills, such as written and spoken communication, team work, design, and problem solving. These are highly valued both within learning institutions [1] , [2] and by outside groups, notably employers [3] , [4] . Learners need to develop these skills progressively, over several years, aided by a suitable sequence of learning experiences [5] . To achieve such long term learning over a whole degree program, designers of each subject must appreciate how their subject fits into the full curriculum.. Also, those responsible for each degree program must ensure that generic skills are developed via a series of learning activities across subjects. This is quite complex, especially where students have flexibility to select elective subjects that match their background, interests, and goals [6] .. Despite the importance of learning generic skills, it is difficult to rigorously classify the skills learned in each subject. For this, we need to define two aspects: the generic skill; and the proficiency level of that skill. While there has been some research involving fine-grained ontological models for learning design, such as [7] , this approach is not adequate for our goals to model long term learning of generic skills across the many subjects that span the three to five years of a degree program.. A central problem is that the semantic model describing the learning progression must be agreed upon and used by several groups of people. First, the lecturer responsible for teaching a particular subject must understand just what is required from their subject; otherwise they may fail to keep it true to the curriculum. Second, people at the faculty level must understand the curriculum design well enough to assess if it does develop the faculty's required generic attributes. Outside the university, accreditation/regulatory bodies must be convinced that their stated learning requirements are being met.. Importantly, universities, accreditation, regulatory, and professional bodies each define their own learning goal sets. While these bodies may attempt to ensure general alignment with other existing standards, the learning goal sets defined by each vary in their descriptors, granularity, specificity, and structure.. For example, the Bachelor of Engineering in Software Engineering BE(SE) degree at the University of Sydney in Australia needs to anticipate learning goal requirements as defined in: Our work was driven by the need to enable people to overcome the complexity of designing the curriculum for whole degree programs so that they develop students' skills and knowledge in the key learning areas that are defined by institutions and accreditation bodies. All of these areas involve long term learning, over several years, to learn then consolidate that learning and move to higher levels of learning. This requires that the individual subjects each play their role in building these long term broad sets of skills and knowledge. This is an ambitious and challenging goal that is important for the quality of degree programs.. Our approach to designing CUSP drew upon available research. At the same time, we needed to take care to minimize any additional load on lecturers. This led us to an approach based on a light-weight ontological model, and a small number (up to five) levels of proficiency for each learning goal. We use the institution's learning attributes as the master; each other set of learning goals is mapped to it. We have demonstrated that our approach, and its realisation in CUSP, is effective in supporting curriculum design. It enables the lecturer to define their own subject in relation to the institutional learning attributes and to see how it relates to these and their levels. CUSP gives a big picture overview of the whole of a degree and serves as a foundation for improvements to the design of the curriculum, with flexible views across any of the relevant sets of learning attributes. Our key contribution is a new mechanism for supporting the complex and important task of degree level curriculum design.. While CUSP has demonstrated the value of our approach for curriculum designers, at the level of the subject and the degree, we plan to extend our approach to incorporate available assessment data within each subject to create detailed individual student models. To do this, we will move beyond our current mapping of attributes to assessments via learning outcomes. This will allow us to explore the value of personalized attribute progress matrices for students in terms of making more informed subject enrolment decisions, personal reflection and gaining a better understanding of the governing factors influencing their degree. It will also provide a basis for longitudinal data mining of the learner models to improve understanding of the causes of student difficulties.. Richard Gluga received the BE degree in software engineering and BS degree in computer science from the University of Sydney, Australia. Currently, he is working toward the PhD degree in computer science and education. He has several years of industry experience in enterprise integration at IBM Australia and as a software architect at the University of Sydney. He is the lead architect and developer of the Course and Unit of Study Portal (CUSP) system described in this paper, and also the ProGoSs system, specializing in fine-grained modeling of learning and progression. His main research interests include life-long learner modeling, curriculum design, and improved learning goal accreditation practices.. Judy Kay is a professor of computer science in the School of Information Technologies at the University of Sydney. She is the principal in the CHAI: Computer Human Adapted Interaction Research Group, leading research in advanced technologies for human computer interaction, supporting personalization, and pervasive and mobile interaction. Her vision is to support a highly personalized way for people to interact with the computers that they carry, those embedded within the environment, as well as desktop computers. She has published extensively in conferences such as Pervasive, Computer Human Interaction (CHI), and User Modeling (UM, AH, UMAP), and in journals such as the IEEE Transactions on Knowledge and Data Engineering, the International Journal of Artificial Intelligence in Education, User Modeling and User-Adapted Interaction, Personal and Ubiquitous Computing, Communications of the ACM, and Computer Science Education.. Tim Lever received the PhD degree in political science from Macquarie University and has worked as an education designer and curriculum developer at the University of Sydney for the past eight years. He initiated and currently coordinates the CUSP project at the University of Sydney's Faculty of Engineering and Information Technologies. His contribution was recognized in 2011 with the University Vice-Chancellor's Award for Systems that Achieve Collective Excellence in Teaching. He comes from a language teaching background.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


User interface description languages for next generation user interfaces In recent years HCI researchers have developed a broad range of new interfaces that diverge from the "window, icon, menu, pointing device" (WIMP) paradigm, employing a variety of novel interaction techniques and devices. Developers of these next generation user interfaces face challenges that are currently not addressed by state of the art user interface software tools. As part of the user interface software community's effort to address these challenges, the concept of a User Interface Description Language (UIDL), reemerge as a promising approach. To date, the UIDL research area has demonstrated extensive development, mainly targeting multi-platform and multi-modal user interfaces. However, many open questions remain regarding the usefulness and effectiveness of UIDLs in supporting the development of next generation interfaces. The aim of this workshop is to bring together both developers of next generation user interfaces and UIDL researchers in an effort to identify key challenges facing this community, to jointly develop new approaches aimed at solving these challenges and finally to consider future spaces for UIDL research. In the last decade, new classes of devices for accessing information have emerged along with an increased connectivity. In parallel to the proliferation of these devices, new interaction styles have been explored. Among these new styles are virtual reality, mixed reality, 3D interaction, tangible user interfaces, context-aware interfaces and recognition-based interfaces. As a result of this increasing diversity of devices and interaction styles, developers of next-generation interfaces experience difficulties such as the lack of appropriate interaction abstractions, the need to create different design variations of a single user interface and the integration of novel hardware. As part of the user interface software research community effort to address these difficulties, the concept of UIDL, which has its foundations in user interface management systems and model-based authoring, has reemerged as a promising approach. UIDLs allow user interface designers to specify a user interface, using high-level constructs, which abstract away implementation details. UIDL specifications can then be automatically or semi automatically converted into concrete user interfaces or user interface implementations. Several UIDLs, mostly using XML as the general language, have been developed in recent years in order to simplify the development of next generation interfaces. However, despite the advancements demonstrated by the UIDL research community (see workshop on developing user interfaces with XML at AVI 2004 [6] , and the adoption of this approach in commercial-level applications), many questions regarding the usefulness and effectiveness of UIDLs for next generation user interfaces remain open:. What models are required for specifying the dynamic behavior of next generation interfaces that are characterized by continuous, physical and multi-user interactions? How can UIDLs be made understandable and useful to user interface developers from different disciplinary backgrounds? How should UIDL's be evaluated? What UIDL approaches will result in powerful design and run time services? And finally how the result of collaboration between user interface developers and UIDL researchers will affect the UI architectural framework of the next generation of user interfaces?

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A framework for incremental generation of closed itemsets Association rule mining from a transaction database (TDB) requires the detection of frequently occurring patterns, called frequent itemsets (FIs), whereby the number of FIs may be potentially huge. Recent approaches for FI mining use the closed itemset paradigm to limit the mining effort to a subset of the entire FI family, the frequent closed itemsets (FCIs). We show here how FCIs can be mined incrementally yet efficiently whenever a new transaction is added to a database whose mining results are available. Our approach for mining FIs in dynamic databases relies on recent results about lattice incremental restructuring and lattice construction. The fundamentals of the incremental FCI mining task are discussed and its reduction to the problem of lattice update, via the CI family, is made explicit. The related structural results underlie two algorithms for updating the set of FCIs of a given TDB upon the insertion of a new transaction. A straightforward method searches for necessary completions throughout the entire CI family, whereas a second method exploits lattice properties to limit the search to CIs which share at least one item with the new transaction. Efficient implementations of the parsimonious method is discussed in the paper together with a set of results from a preliminary study of the method's practical performances. Association rule mining from a transaction database (TDB) [2] is a classical data mining topic, whereby the most challenging problem is the detection of frequent patterns (itemsets) in the transaction set [1, 6, 22] . A major difficulty with association rules is the prohibitive number of frequent itemsets (FIs) (and hence rules) that can be generated even from a reasonably sized data set. The frequent closed itemsets (FCIs) research topic [27, 29, 43, 44, 46, 47] constitutes a promising solution to the problem of reducing the number of the reported associations. Yet another difficulty arises with dynamic databases where the transaction set is frequently updated. Although the necessity of processing volatile data in an incremental manner has been repeatedly emphasized in the general data mining literature (e.g., in [20] ), a few incremental mining algorithms have been reported so far [3, 13, 14, 17, 30, 34] . All these studies have highlighted the need for some additional storage and/or some supplementary database passes to cope with data set evolution.. Our own approach to incremental FI mining is motivated by the belief that FCIs provide the key to compact rule sets and low storage requirements. Therefore, we have been investigating the potential benefits of using concept analysis as a formal basis for the resolution of the FCIs mining problem. The ultimate goal of our study is the definition of a complete framework for that problem, i.e., a consistent body of theoretical knowledge that underlies a set of high-level algorithms which are in turn realized by effective mining tools. It is to be completed by experimental evidence about its strength drawn from practical studies on association mining test-beds.. In this paper, we present an initial, but complete version of our framework: the core theoretical part is presented together with some further structural results that pertain to a minimalist approach toward the incremental FI generation. The approach consists in reducing the dynamic FI mining problem to a one-by-one insertion of transactions into an available database. The resulting incremental FI problem is successfully mapped into a lattice maintenance problem [35] and the underlying theory is adapted to the association rule paradigm so that efficient algorithms can be designed based on the structural properties. First, we establish the correspondence between basic elements of both frameworks. Then, we present a way to transform a recent enhancement of a classical lattice algorithm into an FCI-miner. As the resulting approach relies on extensive exploration of the temporary FCI family upon each update, we investigate possible pruning strategies to reduce the set of examined FCIs. To that end, we provide a set of characteristic properties of the involved lattice substructures and embody them into a new method that only processes relevant lattice nodes. Efficient implementation of the method yields an incremental FCI-miner whose performances are compared to those of a known batch procedure [29] . The paper starts with summaries on association rule mining (Section 2) and on lattices and dedicated algorithms (Section 3). The theoretical foundations of our framework are presented in Section 4. Our generic mining approach, GALICIA, is outlined in Section 5 together with two methods, a straightforward one and an optimized one. Section 6 presents an implementation of the second method. Section 7 lists related work and Section 8 discusses theoretical worst-case complexity as well as preliminary results about the practical performances of our methods. Incrementality is a major challenge in data mining. The proposed framework for incremental FCI mining is a first step toward achieving that goal. The framework is based on FCA and lattices whose benefits for the association rule mining problem have already been demonstrated. Two concrete mining algorithms have been devised within the framework, one straightforward and the other one using a pruning mechanism, with an additional valuable feature which is the low-cost response to readjustments in the support threshold.. Appropriate implementation of the basic algorithms have been discussed and their respective practical performances were compared to those of a major batch algorithm. The results of a preliminary experimental study on two synthetic data sets of contrasted profiles revealed some potential benefits but also important limitations in the incremental paradigm. When taken as a whole, they seem to suggest that a straightforward incremental approach of the kind described here will most probably prove inefficient in purely static databases when the target support threshold is known beforehand. However, the approach will certainly be more appealing for database applications and data mining tasks where data stores are very dynamic and the mining task is carried out in an exploratory manner. More precisely, incremental mining procedures may be very helpful in environments where the user may want to frequently: (i) modify the support threshold of FIs for a given TDB and/or (ii) process new transactions in dynamic databases and analyze their impact on the mining result.. The scalability of our incremental approach is clearly obstructed by the necessity of maintaining the whole set of CIs. Therefore, we are now focusing on parsimonious updating only of its frequent part. As a first step, the MAGALICE algorithm [31] was devised. It helped identify the CI drift phenomenon and its high computational cost. Hence there is still room for further research on parsimonious traversal of FCIs. Another promising track seems to reside in the joint use of GALICIA and an efficient FCI miner, e.g., CLOSET, ACLOSE or CHARM. The latter could extract the FCIs plus their border from the known part of a data set while leaving the subsequent maintenance of the result to GALICIA. The idea reflects to a different yet somewhat related aspect of our lattice-based framework, i.e., the incremental integration of batches of transactions by lattice merge procedures (see [42] ). The underlying framework offers a large choice of operations reflecting updates in the data set such as the removal of transaction batches.. Clearly other data mining tasks could be translated into the FCA framework. For example, the computation of nonredundant bases for association rules has already been researched from the perspective of the implication extraction in FCA [33, 36] . A discussion of the potential benefits of applying FCA to a wide range of data mining tasks may be found in [40] . The above facts provide some evidence to support the benefits of the incremental approach. In fact, running CLOSET once with an augmented data set may cost up to 100 times more than the time spent for inserting a single transaction with GALICIA. In other words, one may run, say, several hundreds of insertions with GALICIA while CLOSET is working on the entire data set. Of course, this does not make our algorithm more efficient for the whole task as the total execution time remains too high. However, with a dynamic database, the mining process is spread over the entire database life-cycle (usually long) so that the main question becomes the establishment of a proper trade-off between the update costs and the urgent need for intermediate results.. When taken as a whole, the experimental results suggest that the benefits of the parsimonious update strategy in GALICIA-P, as opposed to the more straightforward one in GALICIA-M, are more substantial with sparse data sets than with dense ones. An important factor behind those gains, although probably not the only one, is the difference in complexity order for both algorithms. To spell it in figures, while GALICIA-M depends more heavily on the size of the context seen as a matrix, i.e., on the number of items/transactions (see Section 8.1), GALICIA-P only depends on the total number of items in the database. One may express the underlying dependency as follows: execution time gains of GALICIA-P with respect to GALICIA-M inversely depend on the ratio between the number of examined elements and the total size of the CI family. Clearly, the denser the data set, the larger the ratio. Therefore, we hypothesize that sparse data sets will generally tend to favor the parsimonious update in GALICIA-P. Frequent pattern mining is a key step in many data mining tasks such as the discovery of association rules, sequential patterns, and episodes. In the following, we report in a non-exhaustive way related work on incremental FI mining or extraction of CIs as well as on connected aspects of FCA algorithmic practice, especially on concept computation and lattice construction.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Splatterplots: Overcoming Overdraw in Scatter Plots Abstract-We introduce Splatterplots, a novel presentation of scattered data that enables visualizations that scale beyond standard scatter plots. Traditional scatter plots suffer from overdraw (overlapping glyphs) as the number of points per unit area increases. Overdraw obscures outliers, hides data distributions, and makes the relationship among subgroups of the data difficult to discern. To address these issues, Splatterplots abstract away information such that the density of data shown in any unit of screen space is bounded, while allowing continuous zoom to reveal abstracted details. Abstraction automatically groups dense data points into contours and samples remaining points. We combine techniques for abstraction with perceptually based color blending to reveal the relationship between data subgroups. The resulting visualizations represent the dense regions of each subgroup of the data set as smooth closed shapes and show representative outliers explicitly. We present techniques that leverage the GPU for Splatterplot computation and rendering, enabling interaction with massive data sets. We show how Splatterplots can be an effective alternative to traditional methods of displaying scatter data communicating data trends, outliers, and data set relationships much like traditional scatter plots, but scaling to data sets of higher density and up to millions of points on the screen. S CATTER plots are a simple, intuitive, and natural way of visualizing two-dimensional point data. Scatter plots can display data trends and correlations between any two dimensions. They can make outliers easy to identify because regions with higher density of points will be grouped perceptually. Additionally, scatter plots offer a means for comparing different data sets when plotted on the same axes. These properties make scatter plots good for exploring data sets and communicating interesting findings. Unfortunately, scatter plots become less effective as the overlap within points increases.. Overdrawing occurs when the glyphs that are used to visualize data points overlap. This overlap can become so severe that it is impossible to perceive the number of points in a given region of the scatter plot. This interferes with the viewer's ability to group points perceptually and spot outliers. Overdrawing increases as the available drawing space per glyph decreases. High density regions, large numbers of points, and multiple data sets all contribute to the overdraw problem. Even if we decrease the size of the glyphs to be a single pixel, an increasing number of data sets contain many more points than there are pixels in a monitor. Additionally, many analysis and visualization techniques, such as scatter plot matrices (SPLOMS), call for several different concurrent plots, further diminishing the amount of available screen space.. In this paper, we introduce Splatterplots, a novel presentation of point data that addresses weaknesses in scatter plots to better scale to larger data sets. Our key idea is to limit the amount of visual complexity in any screen space area. Splatterplots abstract point data so that the amount of information shown in any area of screen space is bounded. Dense regions are shown as smooth shapes, and outlying points are subsampled so they do not exceed a specified visual density. A screen space metric controls both the amount of detail in the smooth shapes and the display density of outlier glyphs, enforcing a limit on the amount of visual complexity. The details removed in a Splatterplot can be revealed through interaction mechanisms such as zooming and panning, enabling fast exploration of massive data sets. Continuous zooming automatically reveals abstracted details since abstractions are determined in screen space. Splatterplots allow a user to see trends and patterns in data sets even as the number of points grows large relative to the diagram size. Particularly, subgroup relationships and ranges can be clearly observed, even as the number of data subgroups grows past 2 or 3. The main features of Splatterplots are illustrated in Fig. 1 . This paper discusses the design of Splatterplots, describing how perceptual research led us to a design that uses abstraction and multiple visual representations. We describe a process for creating Splatterplots that incorporates kerneldensity estimation (KDE) and especially tuned color blending. We integrate zooming techniques that reveal abstracted information as it becomes feasible to perceive it. A GPUaccelerated implementation allows interaction, even with large data sets. We demonstrate the usefulness and flexibility of Splatterplots on examples of several hundred thousand scatter points.. Contributions: The central contribution of this paper is a new technique for displaying scattered data that remains interpretable as the number of points grows large. Our design is based on two key ideas: to explicitly perform abstraction to reduce visual clutter; and to perform these abstractions in screen space. To realize these ideas, we provide a design that uses different encodings for sparse and dense regions, each bounding information density in screen space. The design reduces the amount of information presented so that the main features of the data remain visible. Additionally, abstracting dense regions as smooth regions enables data subgroup comparisons. Our novel design is supported through a pipeline of steps that couple standard data abstraction tools with interaction techniques, all performed with the aid of the GPU, enabling our approach to scale well. Our results show useful depictions of massive data sets. The problem providing scalable views of scatter data has been approached in several ways. These prior efforts motivate our work.. Perhaps one of the most common ways of dealing with dense scatter data is the use of density estimations. Whether the method is parametric or not, these methods involve computing a smooth function over the area of interest. These densities can then be displayed as a continuous scalar field, for example, by mapping the values to visual parameters or creating contour plots. Unfortunately, existing methods for scalar field display are problematic. Methods do not handle outliers well, as isolated points create small regions of low density. Methods for the denser regions do not scale to multiple data series. While effective encodings of a single value are well known, for example, color ramps from ColorBrewer [1] , encoding multiple, overlapping fields is challenging. Contour plots quantize the density values to better expose shape, but fail to capture outliers, become complex quickly with data details, and fail to scale to multiple data series. Hexbin plots and 2D histograms similarly quantize density in local regions, but dense regions created by such plots do not create perceptually smooth contours, making them hard to group and compare visually. Our approach builds on the ideas of density estimation, color mapping, and contour finding but adds explicit consideration of abstraction in screen space to limit visual complexity and handles outliers specifically.. Alpha bending can be used to show each individual scatter plot point semitransparently [2] . This common and simple form of density estimation can be implemented efficiently using accumulation in the frame buffer. While it does not address any of the shortcomings of the more general approach, it does suggest an efficient implementation using graphics hardware, an approach we build upon.. The general challenge of visualizing multiple scalar fields has led to techniques that are unsatisfying for display density information from scatter data. Color blending does not offer a satisfactory solution for even two sets as the nonlinearity of perception make a quantitatively interpretable blend difficult [3] , [4] . Methods such as Texton Maps [5] , Attribute Blocks [6] , and Color Weaving [7] all trade spatial resolution for value resolution and are primarily effective at indicating regions of constant value, not continuously varying quantities such as density. The methods also fail to scale in the number of fields. Our approach provides spatial resolution by explicitly showing contours and limits the amount of density information conveyed so that we can employ ideas inspired by the multifield techniques to provide for multiple overlapping data subgroups. The contours created by our technique are analogous to overlapping sets. Bubble Sets [8] and Simonetto et al. [9] show relationships between overlapping sets by enclosing related groups with contours. While these techniques effectively show relationships between different sets, they fail to scale directly to visualizations representing large amounts of data points.. The dense point problem has also been addressed through the use of clustering, sampling, and filtering. Ellis and Dix [10] , [11] use sampling as a means to reduce the density of points shown. Bertini and Santucci [12] model the underlaying data density to perform uniform and nonuniform sampling. Ellis and Dix [13] have also compiled a taxonomy of clutter reduction techniques used in information visualization. While these approaches can very effectively reduce the number of points in the data set to a manageable number, the challenge of handling multiple sets remains. Our approach effectively performs clustering by grouping dense regions of points into continuous regions. These solutions provide a perceptually motivated clustering that affords effective visual presentation and adapts to interaction. We use sampling strategies in less dense regions.. Dang et al. [14] present a method for dealing with overlapping data by stacking points in the third dimension, but this method does not scale well with large data sets. Tory et al. [15] compare similar encodings, but similarly do not consider issues of scalability.. Generalized scatter plots [16] present a way of nonlinearly warping the scatter dimensions to avoid overdrawing. While this makes the shape of the data in the dense regions more apparent without losing outliers, it is difficult to see the relationship between the dense regions and the nondense regions. The warps are also hard to understand intuitively, but they can be visualized by overlaying Voronoi shapes over the points. This makes it hard to overlay different data sets on top of each other, since the warp must be computed for the aggregated set. Variable binned scatter plots [17] explicitly groups regions of space into subplots and highlight different statistical properties, such as median and internal quartiles. Again, while this may work for one data set, comparison with another is difficult. Additionally, the visualization is not as intuitive as scatter plots and requires a significant amount of training to understand.. Scatter plots have been extended in several ways. For example, extensions support higher dimensional data, such as interactive SPLOMs [18] . Such techniques do not address the scalability issues in scatter plots, if anything they exacerbate it by creating more, smaller plots. This problem can be ameliorated by view selections techniques such as those presented Sips et al. [19] and Wilkinson and Wills [20] . Other extensions that encode additional data variables onto the points, such as bubble plots or shaped glyphs, generally fail to scale to dense point sets as they also exacerbate the overdraw problem.. Several studies have examined specific aspects of the perception of scatter plots. These include the perception of correlation [21] , discrimination of symbol size [22] , symbol lightness [23] , and symbol contrast [24] . While these do not explicitly deal with the perception issues caused by overdrawing, a full solution toward perceptually scalable scatter plots should take these findings into account.. Continuous scatter plots [25] solve an orthogonal problem. They are designed to generate 2D continuous histograms of values from a scalar or vector field with a spatial embedding, in an effort to bring the advantages of scatter plots to scalar and vector fields. We performed several experiments to analyze the performance and behavior of several of our design decisions and our prototype implementation. Our prototype system was written as a 64-bit .Net application in C# and uses OpenGL through the OpenTK library. Our performance analysis was conducted in a machine with an Intel i7-3770k processor, 16 GB of RAM, and an NVIDIA GTX 670 graphics card, all under Windows 7 64 bit.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Feasible database querying using a visual end-user approach Querying databases is a common daily task carried out by a great deal of end-users who do not have specific skills in SQL language. Today, most of the database interaction is achieved by means of query interfaces provided by the database environment. However, most of these interfaces suffer from expressive limitations, since they are mostly based on metaphors that drastically restrict the expressiveness of the SQL language that is generated and executed in the background. In this paper, we present a visual interaction language and tool focused on easily querying databases by end-users. We make no assumption on the level of the user's experience with query languages, as our visual metaphor is intended for querying databases by unskilled end-users and also leveraging the restriction on the expressiveness of the queries created by them. We also report on some late braking results obtained by an experiment carried out with real users. Interacting with databases has become commonplace in most end-user activities today. In the past, such interaction was carried out using sentences in textual languages that the database expert had to provide to the application using the system prompt and/or executing programming code to obtain the desired outcome.. Nowadays, modern computing advocates the idea of people using and creating databases in order to accomplish their daily tasks. They are professionals such as engineers, scientists and freelances that may have concrete domain skills but lack programming abilities. In this regard, further support is needed in order to provide such non-programmer professionals with easy-to-use mechanisms, avoiding the need for them to learn programming languages and specifications that are usually deemed to be irrelevant for their daily work activities Database research has recently produced notable results related to architectural and storage facilities, likely paying less attention to interaction. This has enabled databases systems to deal with large volumes of information for different purposes (such as distribution), but decreasing, however, the facility for end-users to easily access and manipulate information.. In the last decade, some database systems have included visual tools intended to manipulate models and data for supposed unskilled end-users. The existence of visual tools helps reduce the gap between users and the information they desire to query. However, the creation of good visual tools for database query is not such an easy task. Most of the existing query environments lack both visual expressiveness and/or ease of use -an essential trade-off that most end-user-intended applications should guarantee today [11] . This lack of expressiveness sometimes implies that some capabilities related to build complex queries are missing, or they are hard to be accomplished by end-users. For instance, some systems are based on a table-like metaphor that severely restrict the capability to deal with aggregation conditions, filters, and complex operations such as UNION, INTERSECTION, IN and NOT IN. On the other hand, the usability assurance in such query interfaces has been barely addressed as, in most of the cases, neither user-centered techniques have been used nor user mental model has been considered throughout the design.. In order to overcome the aforementioned drawbacks, we have created a visual query tool called VISQUE (VIsual Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Star-schema QUery by Example) that takes up the challenge of creating queries (specifically in data warehouse schemas) by example, empowering the way users can create different kinds of queries with minimal expressive limitations, and carrying through an explicit ease of use to achieve a better user experience. Our system exploits different knowledge-visualization techniques including a tree-based metaphor to easily represent the measures and dimensions of a multidimensional database schema, providing expressiveness enough to create complex SQL-based constructions such as set-based, nested and aggregation queries.. The main objective of our work is twofold:. • To provide end-users with the capability to create database queries, assuming no skills in SQL statements, enhancing the ease of use and so reducing the cognitive load during the interaction.. • To provide a less restrictive metaphor by which endusers can create different kinds of queries; including set-based and aggregation operations, which are not very common in other table-based database query environments.. In order to support the above objectives, we have built our authoring tool by means of using user-centered techniques such as Competitive Analysis [13] and Paper Prototyping [15] . Also, we have evaluated the current prototype by means of an experiment achieved with real users, also utilizing user-centered techniques such as the Retrospective Test [13] and usability evaluation through the USE questionnaire [10] .. The rest of this paper is organized as follows. In the next section, we will present related work addressing some of the most common tools related to our approach. Next, an overview of our system is given on the basis the of the DW schema composition and query. Then, late breaking results from our last experiment with real users will be introduced in order to discuss the most relevant outcome obtained. Finally, we outline some conclusions and future work. We have presented an overview of our work, which is an attempt to deal with the problem of visualization and query in data warehouse schemas, taking into account usability features and feasibility in an explicit expressiveness/easeof-use trade-off. Our work is aimed at supporting easy web interaction with databases for the end-users to obtain valuable information from them. The solution provided is a combination of End-User Development techniques, webbased user interface design and data models, all combined in an interactive environment called VISQUE.. The multidimensional model used helps reduce complex relations and simplifies the user's mental model of both data and interaction. Additionally, visual representations drastically reduce the abstraction level and support user interaction easily.. The idea of visual tools intended for database is not new at all. However, we have found deficiencies in existing applications that have been collected using heuristic evaluation of (partial) usability as well as comparative/competitive analysis commonly used in the analysis phase when designing interactive software [13] . Also, comparative analysis is useful to analyze the cognitive load and the sequence of steps typically used in data warehouse queries, checking the operations missing and noticing those that have usability problems. In this sense, our approach overcomes other systems providing the following features that outperform, on average, the tools previously discussed:. • Automatic inference of the data schema.. • Greater expressiveness and interaction in the representation and manipulation of data warehouse schemas, improving the ability to suggest possible values for filters, and supporting an expressive and interactive way to represent the data schema For the time being, we have the definition of the visual language as well as a functional prototype of VISQUE that has been validated through several use cases. Furthermore, the test carried out with real users allowed evaluating the tool. In particular, it enabled to obtain a general perception about the ease of use. Partial correlations calculated using other dimensions (i.e., Usefulness, Satisfaction and Ease of Learning) suggested that, while both drive Satisfaction, Ease of Use and Usefulness influence one another, such that improvements in Ease of Use improve ratings of Usefulness and vice versa. In addition, Satisfaction is strongly related to the usage (actual or predicted). The items contributing to Ease of Use could be separated into two factors, Ease of Learning and Ease of Use, which are obviously highly correlated [10] . In particular, the analysis of the questionnaire reported positive results about the ease of use of the tool, which empowers to corroborate the initial hypotheses and contribute to the usability assurance in our tool.. VISQUE has been built using user-centered techniques such as Comparative Analysis, Retrospective Testing (including Thinking Aloud [14] sessions) and Paper Prototyping, a common interaction analysis technique that enabled us to capture the user's mental model matching the behavior and appearance of the web user interface very early in the development process.. Additionally, we are still studying different possibilities for the visualization of other complex query operations not covered by existing approaches. Finally, we plan to improve the tool further from the feedback obtained from the user test, as well as to achieve some additional experiments to validate the new improvements. In some way, the usability of a database system is as important as its capability [4] , which means that the information should be organized and presented to end-users in a natural and understandable way, enabling to manipulate the data in an easy manner. Visual-query interfaces have been proposed in the past to assist users in building queries for different domains. Query by example (QBE) [20] has been the inspiration for several visual query tools (such as Microsoft Access or SQL-Server). However, QBE uses a visual table-like metaphor that is not able to deal with setbased or nested operations in a visual way. A different approach is presented in Spago BI QbE Enterprise Scope [17] , which proposes the creation of queries from a fixed sequence of steps, but it still lacks the visual richness and variety of (relational) query operations. There are other open source tools like Eclipse Birt Project [3] , which also provides facilities for creating queries, but it lacks of visual expressiveness and is not suitable for unskilled users since it demands to directly manipulate SQL code. Additionally, Tableau Desktop [19] is the commercial version of a research tool called Polaris [18] , which is mainly focused on data warehouse schemas. However, this tool uses a method of classification for measures and dimensions based on the type of data related to the fields. By contrast, VISQUE analyzes the structure of the model and, by using a worked algorithm, it determines the fact table with the corresponding measures, as well as the dimension tables having the dimensional attributes. Visual languages are frequently used to facilitate the creation of queries by endusers. The main goal is to facilitate the use of predefined domain concepts, as visual representations drastically reduce the abstraction level required to create programmatic representations [12] . Our approach attempts to complement other visual tools in the area, adding a novel visual representation of data warehouse schemas and including graphical representations of set-based and nested query operations that are commonly infrequent or even unavailable in other approaches.

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