Sara Migliorini

Automated error correction of business process models

As order dependencies between process tasks can get complex, it is easy to make mistakes in process model design, especially behavioral ones such as deadlocks. Notions such as soundness formalize behavioral errors and tools exist that can identify such errors. However these tools do not provide assistance with the correction of the process models. Error correction can be very challenging as the intentions of the process modeler are not known and there may be many ways in which an error can be corrected. We present a novel technique for automatic error correction in process models based on simulated annealing. Via this technique a number of process model alternatives are identified that resolve one or more errors in the original model. The technique is implemented and validated on a sample of industrial process models. The tests show that at least one sound solution can be found for each input model within a reasonable response time.

Representing Business Processes Through a Temporal Data-Centric Workflow Modeling Language: An Application to the Management of Clinical Pathways

Workflow technology has emerged as one of the leading technologies in modeling, redesigning, and executing business processes in several different application domains. Among them, the representation and management of health and clinical processes have been attracting a growing interest. Such processes are in general related to the way each health organization provides the required healthcare services. Health and clinical processes underlie the specification and application of clinical protocols, clinical guidelines, clinical pathways, and the most common clinical/administrative procedures. Current workflow systems are lacking in effective management of three general key aspects that are common (not only) in the clinical/health context: data dependencies, exception handling, and temporal constraints. For example, a laparoscopic intervention may need the results of the concurrent bioptic analysis to be properly concluded while exceptional recovery activities have to be performed in case of emergency evidence during standard treatment; however, the successful application of a fibrinolytic therapy requires a maximum delay of 30 min after the admission into the emergency department. In this paper, we propose TNest, a new advanced, structured, and highly modular workflow modeling language that allows one to easily express data dependencies and time constraints during process design, in addition to exception handling and compensation activities. As for temporal constraints, we focus here on temporal controllability which is the capability of executing a workflow for all possible durations of all tasks satisfying all temporal constraints. Moreover, we analyze the computational complexity of the temporal controllability problem in TNest, and we propose a general algorithm to check the controllability. All the features of TNest that have been considered to model clinical pathways from classical clinical guidelines, i.e., those features for the management of STEMI patients, published by the American College of Cardiology/American Heart Association, will be used throughout the paper as a motivating scenario.

From the conceptual design of spatial constraints to their implementation in real systems

The spatial data community recognizes the need for procedures that automatically validate spatial integrity constraints defined at conceptual level. This validation becomes particularly important in an open and distributed environment, like a Spatial Data Infrastructure (SDI), where the level of integration and interoperability is very high. However, the current gap between the conceptual design of a spatial database and its implementation into a GIS system makes the definition of spatial constraints useful only for documentation purposes and not for automatic validation. The GeoUML modeling language provides a set of predefined OCL templates for expressing the most common spatial constraints. In this paper, we deal with the validation problem by proposing a methodology for automatically translating the OCL constraints of GeoUML into SQL spatial queries, thus obtaining a platform independent general validation tool.

A Framework for Managing Temporal Dimensions in Archaeological Data

Time and space are two important characteristics of archaeological data. As regards to the first aspect, in literature many time dimensions for archaeology have been defined which extend from the excavation time, to the dating of archaeological objects. Standard ISO 19018 describes temporal characteristics of geographical information in terms of both geometric and topological primitives. The first aim of this paper is to analyze the applicability of such Standard for representing archaeological data, referring to the model adopted by the city of Verona (Italy) as case study. However, since archaeological dates are often subjective, estimated and imprecise, one of the main lack in the Standard is the inability to incorporate such vagueness in date representation. Therefore, the second contribution of this paper is the extension of the Standard in order to represent fuzzy dates and fuzzy relationships among them. Finally, considering the process through which objects are usually manually dated by archeologists, some existing automatic techniques for time reasoning may be successfully applied in this context in order to guide the dating process. For this purpose, the last paper contribution regards the translation of some archaeological temporal data into a Fuzzy Temporal Constraint Network (FTCN) for checking the overall data consistency and reducing the vagueness of some dates based on their relationships with other ones.

Modelling temporal, data-centric medical processes

Workflow technology has emerged as one of the leading technologies in modeling, redesigning, and executing medical processes and some interesting workflow management systems are available. Nevertheless, such systems are lacking in an effective management of two key aspects: data dependencies and temporal constraints. In clinical/health context these two aspects are of paramount importance. For example, a surgery intervention could need the results of the concurrent bioptic analysis to be properly concluded; on the other hand, to successfully apply a fibrinolytic therapy to patients with ST-segment Elevation Myocardial Infarction (STEMI) a maximum delay of 30 minutes must be considered w.r.t. the emergency department admission. In this paper, we propose TNest, a new advanced, structured and highly modular workflow modeling language that allows one to easily express data dependencies and time constraints during process design. All the features of TNest have been considered to model the process related to classical clinical guidelines, i.e. those for the management of STEMI patients, published by the American College of Cardiology/American Heart Association.

Robustness of spatial relation evaluation in data exchange

Topological relationships between geometric objects are important in several spatial applications, like spatial query evaluation, spatial integrity constraints checking, and spatial reasoning. Although the conceptual aspects of topological relationships between geometric objects embedded in the Euclidean space have been extensively studied, the problems arising when topological relationships are evaluated on real data have been much less explored. In particular, robustness problems arise in the evaluation of topological relationships between geometric objects implemented as vectors in a discrete space. A lack of robustness is characterized by the fact that different systems can produce different evaluations of topological relationships on the same data, and it is caused by the fact that coordinates are represented as finite numbers. The goal of this paper is to formally analyze some rules for increasing the robustness of a topological relationship evaluation and to give some examples w.r.t. a specific topological relationship.

A framework for integrating multi-accuracy spatial data in geographical applications

In recent years the integration of spatial data coming from different sources has become a crucial issue for many geographical applications, especially in the process of building and maintaining a Spatial Data Infrastructure (SDI). In such context new methodologies are necessary in order to acquire and update spatial datasets by collecting new measurements from different sources. The traditional approach implemented in GIS systems for updating spatial data does not usually consider the accuracy of these data, but just replaces the old geometries with the new ones. The application of such approach in the case of an SDI, where continuous and incremental updates occur, will lead very soon to an inconsistent spatial dataset with respect to spatial relations and relative distances among objects. This paper addresses such problem and proposes a framework for representing multi-accuracy spatial databases, based on a statistical representation of the objects geometry, together with a method for the incremental and consistent update of the objects, that applies a customized version of the Kalman filter. Moreover, the framework considers also the spatial relations among objects, since they represent a particular kind of observation that could be derived from geometries or be observed independently in the real world. Spatial relations among objects need also to be compared in spatial data integration and we show that they are necessary in order to obtain a correct result in merging objects geometries.

A Spatio-Temporal Framework for Managing Archeological Data

Space and time are two important characteristics of data in many domains. This is particularly true in the archaeological context where information concerning the discovery location of objects allows one to derive important relations between findings of a specific survey or even of different surveys, and time aspects extend from the excavation time, to the dating of archaeological objects. In recent years, several attempts have been performed to develop a spatio-temporal information system tailored for archaeological data.The first aim of this paper is to propose a model, called 𝓢

The NestFlow interpretation of workflow control-flow patterns

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Approximate Queries for Spatial Data

tar, for representing spatio-temporal data in archaeology. In particular, since in this domain dates are often subjective, estimated and imprecise, 𝓢