Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

On the mining of artful processes

Artful processes are those processes in which the experience, intuition, and knowledge of the actors are the key factors in determining the decision making. These knowledge-intensive processes are typically carried out by the “knowledge workers”, such as professors, managers, researchers. They are often scarcely formalised or completely unknown a priori, and depend on the skills, experience, and judgment of the primary actors. Artful processes have goals and methods that change quickly over time, making them difficult to codify in the context of an enterprise application. Knowledge workers cannot be realistically expected to instruct the assistive system by modelling their artful processes: it would be time-consuming both in the initial definition and in the potential continuous revisions. To make things worse, time is the crucial resource that usually knowledge workers indeed lack. Despite the advent of structured case management tools, many enterprise processes are still “run” over emails. Thus, reverse engineering workflows of such processes and their integration with artefacts and other structured processes can accurately depict the enterprise’s process landscape. A system able to infer the models of the processes laying behind the email messages exchanged would be valuable and the result could materialise almost freely. This is the purpose of our approach, which is the core of this thesis and is named MailOfMine. Its investigation mainly resides in the Machine Learning area. More specifically, it relates to Information Retrieval (IR) and Process Mining (PM). We adopted well-known IR techniques in order to extract the activities out of the email messages. We propose a new algorithm for PM in order to discover the temporal rules that the activities adhere to: MINERful. The set of such rules, intended as temporal constraints, constitute the so called declarative modelling of workflows. Declarative models differ from the imperative in that they do not explicitly represent every possible execution that a process can be enacted through, i.e., there is no graph-like structure determining the whole evolution of a process instance, from the beginning to the end. They establish a set of constraints that must hold true, whatever the evolution of the process instance will be. What is not explicitly declared to be respected, is allowed. The reader can easily see that it is better suited to processes subject to frequent changes, with respect to the classical approach. From a more abstract perspective, this work challenges the problem of discovering highly flexible workflows (such as artful processes), out of semi-structured information (such as email messages)

On the discovery of declarative control flows for artful processes

Artful processes are those processes in which the experience, intuition, and knowledge of the actors are the key factors in determining the decision making. They are typically carried out by the "knowledge workers," such as professors, managers, and researchers. They are often scarcely formalized or completely unknown a priori. Throughout this article, we discuss how we addressed the challenge of discovering declarative control flows in the context of artful processes. To this extent, we devised and implemented a two-phase algorithm, named MINERful. The first phase builds a knowledge base, where statistical information extracted from logs is represented. During the second phase, queries are evaluated on that knowledge base, in order to infer the constraints that constitute the discovered process. After outlining the overall approach and offering insight on the adopted process modeling language, we describe in detail our discovery technique. Thereupon, we analyze its performances, both from a theoretical and an experimental perspective. A user-driven evaluation of the quality of results is also reported on the basis of a real case study. Finally, a study on the fitness of discovered models with respect to synthetic and real logs is presented

A novel framework for visualizing declarative process models

The declarative approach to business process modeling has been introduced to deal with the issue of managing flexible processes. Instead of explicitly representing all the allowed enactments of a process, the approach describes the constraints that limit its behavior. However, current graphical notations for declarative processes are prone to be difficult to understand, thus hampering a widespread usage of the approach. To overcome this issue, we present a novel notation framework for visualizing declarative processes, which is devised in compliance with well-known notation design principles

ALGORITMOS PARA EL DESCUBRIMIENTO DE PROCESOS. ESTADO DEL ARTE

Las técnicas de la minería de procesos permiten la extracción de conocimientos de diversas fuentes de información, el descubrimiento de modelos es una de las etapas que componen la minería de procesos. En esta etapa los algoritmos convencionales parten inicialmente de un registro de eventos y descubren modelos de procesos.En situaciones prácticas la mayoría de los casos contienen varios procesos que colaboran y en su mayoría se encuentran almacenados en bases de datos relacionales. En este sentido, algunos investigadores asumen que un proceso puede tener diferentes perspectivas, cada una de ellas con su propio espacio de estados, de esta forma han podido descubrir modelos de procesos en entornos colaborativos. En varias investigaciones se plantean diferentes métodos enfocados en el procesamiento de los datos en bases de datos relacionales, existen artículos donde se hace referencia a una técnica basada en identificar un modelo centrado en artefactos, partiendo de un esquema relacional obtenido de una base de datos. Las relaciones existentes en el esquema son extraídas y organizadas con el uso de algoritmos de grafos

Generating Synthetic Event Logs based on Multi- perspective Business Rules

Traditsiooniline äriprotsesside modelleerimine kasutab imperatiivset lähenemist, kus äri-protsesse kirjeldatakse üksteise järel sooritatavate tegevuste abil. On näidatud, et imper-atiivne lähenemine on sobivam lahendus stabiilsete ja ennustatavate protsesside puhul. Deklaratiivsed mudelid seevastu sobivad muutuvate protsesside kirjeldamiseks. Deklaratiivne mudel sisaldab endas reeglite hulka mida ei tohi eirata protsessi käitamisel. Viimastel aastatel on arendatud mitmeid uusi meetodeid deklaratiivsete protsessimudelite leidmiseks sündmuste logidest. Meetodite testimiseks on vajalik tööriistade olemasolu, mis genereerivad sünteetilisi sündmuste logisid, mille peal neid meetodeid katsetada. Enamus olemasolevaid tööriistu kasutavad imperatiivseid protsessimudelid logide genereerimiseks. Selline lähenemine ei ole sobiv deklaratiivsete protsessimudelite avastamise meetodite tes-timiseks. Sarnaselt on olemas vajadus tööriistade järgi, mis genereeriks sündmuste logisid kasutades mitmeperspektiivseid Declare mudeleid. Käesolevas töös esitleme tööriista mitmeperspektiivsete Declare mudelite genereerimiseks. See töörist tõlgib Declare piirangud lõpliku olekumasina esitusse,et neid kasutada deklaratiivsete mudelite simu-leerimiseks. Tööriist võimaldab kasutajatel genereerida logisid eeldefineeritud omadustega ( näiteks protsessi instantside arv ja protsessi pikkus), mis on kooskõlas Declare mudeli-tega.\n\rMärksõnad: Declare, deklaratiivne protsessimudel, protsessi simuleerimine, logide gene-reerimine, mitmeperspektiive, lineaarne taisarvuline planeerimineTraditional business modelling is imperative in the sense that activities are provided step by step, from start to end, leading towards full business process. It has been proved that the imperative paradigm is most suitable in the context of stable and predictable processes. Declarative models are more suitable for variable processes. A declarative model is made of a set of constrains that cannot be violated during the process execution. In recent years, many techniques have been developed to discover declarative process model from event logs. To test these techniques it is sometime necessary to have tools that generate synthetic logs on which the techniques can be applied. However, majority of the existing tools avail-able in this field use simulation of an imperative process model to generate synthetic event logs. These approaches are not suitable for the evaluation of process discovery techniques using declarative process models. Additionally, there is a need for tools to generate event logs based on the simulation of multi-perspective declarative models. To close this gap, we developed a tool for log generation based on multi- perspective Declare models. This mod-el simulator will base on the translation of Declare constraints into Finite State Automata for the simulation of declarative processes. The tool will allows users to generate logs with predefined characteristics (e.g., number and length of the process instances), which is compliant with a given Declare model.\n\rKeywords: Declare, Declarative Process Models, Process Simulation, Log Generation, Multi-perspective, Integer Linear Programmin

MailOfMine - Analyzing mail messages for mining artful collaborative processes

Artful processes are informal processes typically carried out by those people whose work is mental rather than physical (managers, professors, researchers, engineers, etc.), the so called "knowledge workers". In this paper we propose the MailOfMine approach, to automatically build, on top of a collection of email messages, a set of workflow models that represent the artful processes laying behind the knowledge workers activities. © 2012 IFIP International Federation for Information Processing

Un Modèle basé sur les Grammaires Attribuées Gardées pour les Processus Dynamiques, Centrés sur l’Utilisateur, Distribués et Collaboratifs: Cas de la Surveillance Epidémiologique

Dynamic processes in which users need to work together and collaborate in myriad ways on process models defined on-the-fly are fast becoming the rule rather than the exception. This thesis presents the design of a purely declarative modelling approach for dynamic, collaborative, user-centred, and data-driven processes. First, we organize the work of a user into task hierarchies which we model as mindmaps, which are trees used to visualize, organize, and log information about tasks in which the user is involved. We introduce the model of guarded attribute grammars, or GAG, to help the automation of updating such maps. A GAG consists of an underlying grammar, that specifies the logical structure of the map, with semantic rules which are used both to govern the evolution of the tree structure (how an open node may be rened to a sub-tree) and to compute the values of some of its attributes. The map enriched with this extra information and with high-level constructs for task dependencies; collaborationand user-interactions is termed an active workspace or AW. Communication between AWs is essentially through the exchange of messages without a shared memory thus enabling convenient distribution on an asynchronous architecture. Lastly, we introduce a language syntax for GAG specification and design a prototype that includes an internal domain specific language (in Haskell) for their specification and a graphical user interface to simulate its execution in a distributed environment. We motivate our approach and illustrate its language syntax and features on a case study for a disease surveillance system.De plus en plus, les utilisateurs collaborent de multiples façons sur des processus dynamiques construit de manière progressive. Dans cette thèse, nous concevons une nouvelle approche d´déclarative de modélisation des processus dynamiques, centrés sur l’utilisateur et dirigés par les données. Tout d’abord, nous organisons le travail d’un utilisateur par des hiérarchies des taches, représentées par des cartes heuristiques (arbre de taches). Ces derniers sont utilisés pour visualiser, organiser, et sauvegarder les informations sur les tâches menés par l’utilisateur. Nous introduisons ensuite le modèle des grammaires attribuées gardées, ou GAG, pour faciliter l’automatisation de la manipulation de telles cartes. Une GAG consiste en une grammaire sous-jacente, qui spécifie la structure logique de la carte, avec des règles sémantiques qui servent à la fois a` gouverner l’évolution de l’arbre des taches (raffinement des nœuds ouverts) et a` calculer les valeurs de certains de ses attributs. La carte enrichie de ces informations supplémentaires et d’autres concepts de haut niveau pour les d´dépendances entre les taches, la collaboration et les interactions utilisateur est appelée Active Workspace ou AW. La communication entre AWs est essentiellement par échange des messages permettant ainsi une implémentation commode sur une architecture distribuée et asynchrone. Enfin, nous décrivons une syntaxe de langage pour la spécification des processus en utilisant les GAGs et concevons un prototype qui inclut un langage spécifique au domaine, interne `a Haskell, pour leur spécification et une interface utilisateur graphique pour la simulation de l’exécution dans un environnement distribué. Nous motivons notre approche et illustrons sa syntaxe et ses caractéristiques sur une étude de cas portant sur le processus de surveillance épidémiologique