Knowledge-intensive processes (KiPs) are driven by knowledge workers utilizing their skills, experiences, and expertise. As these processes are emergent and unpredictable, their support constitutes a big challenge. For coordinating and synchronizing the various tasks of a KiPs, knowledge workers still rely on simple task lists like, e.g., to-do list or checklists. Though task lists are intuitive, their current implementations are very ineective: tasks are neither made explicit nor are they personalized or synchronized. In addition, no task management lifecycle support is provided and media disruptions frequently occur. This tool demonstration presents the proCollab framework supporting a wide range of KiPs (e.g., projects and cases) through integrated, lifecycle-based task management. In particular, proCollab task trees support the provision of task list templates and to constitute digital task lists of any kind. For customization, it further allows integrating domain-specific methodologies as well as configuring task lists at design and run time. Overall, the proCollab framework shall improve coordination among knowledge workers, increase work awareness, and record valuable coordination eorts.
Residing in sensitive key business areas, such as research, healthcare, or engineering, knowledge-intensive processes (KiPs) have become the centerpiece for creating value in many companies [ ]. While driving KiPs, knowledge workers utilize their skills, experiences, and expertise to cope with sophisticated tasks. Thus, the systematic and sustainable support of KiPs constitutes a prerequisite for achieving business goals. KiP support, however, still poses a big challenge. KiPs can be characterized as non-predictable, emergent, goal-oriented, and knowledgecreating processes [ , ]. Consequently, KiPs have not been fully supported by contemporary process-aware information systems so far. Instead, knowledge workers still rely on simple task lists (e.g., to-do lists, checklists) to coordinate their work [ ]. But these instruments are error-prone and ineective. Moreover, knowledge workers suer from media disruptions and a lack of lifecycle-based task management preventing them from reusing existing artifacts (e.g., task lists) in similar KiPs [ ].
The proCollab framework aims at the systematic and sustainable support of KiPs. As tasks constitute the key objects regarding planning and quality assurance for knowledge workers, proCollab provides process- and lifecycle-based task management [ ], empowering knowledge workers to collaborate more eectively. To make use of best practices and knowledge gained in the context of comparable KiPs, proCollab provides process and task list templates, which knowledge workers may instantiate on demand. To foster the reuse of these templates, a contextaware approach for configuring task list templates is included as well. Knowledge workers may then easily configure task lists either at design or run time. To increase work awareness in addition, proCollab encompasses a flexible state management concept. The latter may be customized to optimally align KiPs, task lists, and tasks with domain-specific requirements. Finally, the proCollab framework aims to improve coordination among knowledge workers, prevent media disruptions, and record valuable coordination eorts and knowledge.
proCollab and its Significance to the BPM field To enable a generic, but customizable support for KiPs, the proCollab framework relies on processes, task trees, and tasks as the conceptual pillars for representing a wide range of KiPs as well as task-based artifacts used by knowledge workers. To establish and provide lifecycle-based task management support in the context of KiPs [ ], processes are refined to process templates and process instances, whereas task trees are refined to task tree templates (with task templates) and task tree instances (with task instances) respectively. Figure illustrates the relationship and interplay of those components.
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Process templates and task tree templates enable knowledge workers to accelerate planning of their tasks based on best practices. Every process template may have several subordinated process templates and feature various properties, Process-aware Support for Collaborative Knowledge Workers increase domain-specific support, proCollab employs a generic state management for its stateful key components. This enables us to integrate domain-specific methodologies as well as to manage dierent types of proCollab components in a controlled manner. Additionally, proCollab provides a configuration concept for task tree templates. The latter enables the ecient configuration of task list templates in accordance to the given application context. Due to a lack of space, both the state management and the configuration concept are presented in the screencast of this demonstration in more detail (cf. Section ).
Concerning the significance of proCollab to the BPM field, the design of a systematic KiP support still constitutes a big challenge. While predictable business processes can be well supported by process-aware information systems based on pre-specified process models (doing-by-design), unpredictable and emergent KiPs require a degree of flexibility traditional systems are not able to provide due to the limitations of model-driven approaches. In turn, the proCollab framework relies on the design-by-doing approach necessitating dierent concepts and functions to support a wide-range of KiPs in a generic, but still domain-specific way. In comparison to declarative process execution systems like Declare or DCR Graphs [ ] and approaches based on CMMN [ ], proCollab focuses on the stateful and flexible task (list) management support for KiPs and knowledge workers. In particular, knowledge workers themselves shall drive proCollab processes and, as a consequence, the management of tasks and task lists, too.
To prepare empirical studies and to evaluate the technical feasibility of the proCollab framework, we developed the proCollab tool. The latter is realized with Java EE and relies on a MVC-based architecture (cf. Fig. ). In particular, the application logic layer represents the core of the tool realizing the key services of the proCollab framework. The REST-based interface enables web and mobile applications to communicate with these key services. Finally, the web application based on AngularJS provides state-of-the art user interfaces (cf. Fig. ) to the knowledge workers interacting with the proCollab tool.
The current version of the proCollab tool enables knowledge workers to manage the proCollab key components, i.e., they may manage KiPs in the shape of common projects or cases (i.e., proCollab processes) including task trees embodied as, e.g., to-do lists or checklists. Moreover, knowledge workers may configure task tree templates or instantiate process/task tree templates on demand (see screencast). Furthermore, the proCollab tool allows integrating domain-specific state models for templates and instances of processes, task trees, and tasks. In turn, the assignment of users to tasks, the integration of process resources (e.g., documents, structured data), and the synchronization of tasks and processes are currently in development to be integrated in the web application. Based on its architecture and the technologies in use, the proCollab tool can scale up well and even be deployed in cloud-based environments to serve a significant amount of knowledge workers concurrently.
Web Applica on
Mobile Applica ons n o iitcan u m m oC Process Services
(Instances) Process Template
Repository
Finally, we prepared a screencast available on bpm demo.procollab.de to demonstrate proCollab. The screencast illustrates the key aspects of the proCollab framework using the scenarios of developing a website and conducting a surgery.
This demo presented the proCollab framework and its proof-of-concept tool. The latter is implemented as a scalable, cloud-ready, and web-based application platform. This allows users to collaborate in the scope of KiPs and to simultaneously manage proCollab key components to receive optimal KiP support. Based on the tool, user experiments will be conducted to systematically analyze whether KiPs can be successfully evolved when using the proCollab framework. Overall, we believe that the proCollab framework will improve coordination among knowledge workers, increase work awareness, and record valuable coordination eorts.