Distributed Global Transaction Support for Workflow Management Applications

Workflow management systems require advanced transaction support to cope with their inherently long-running processes. The recent trend to distribute workflow executions requires an even more advanced transaction support system that is able to handle distribution. This report presents a model as well as an architecture to provide distributed advanced transaction support. Characteristic of the transaction support system is the ability to deal with arbitrary distribution of business processes over multiple workflow management systems and the support for flexible rollbacks. The modularity of the architecture and the orthogonality with respect to the workflow management system allows the transaction system to be applied in other application areas as well. The high scalability of the architecture allows an arbitrary combination of transaction support systems and workflow management systems of which the locations are irrelevant. In the WIDE project, the developed echnology is applied to the FORO workflow management system

The AMIDA Automatic Content Linking Device: Just-in-Time Document Retrieval in Meetings

The AMIDA Automatic Content Linking Device (ACLD) is a just-in-time document retrieval system for meeting environments. The ACLD listens to a meeting and displays information about the documents from the group’s history that are most relevant to what is being said. Participants can view an outline or the entire content of the documents, if they feel that these documents are potentially useful at that moment of the meeting. The ACLD proof-of-concept prototype places meeting-related documents and segments of previously recorded meetings in a repository and indexes them. During a meeting, the ACLD continually retrieves the documents that are most relevant to keywords found automatically using the current meeting speech. The current prototype simulates the real-time speech recognition that will be available in the near future. The software components required to achieve these functions communicate using the Hub, a client/server architecture for annotation exchange and storage in real-time. Results and feedback for the first ACLD prototype are outlined, together with plans for its future development within the AMIDA EU integrated project. Potential users of the ACLD supported the overall concept, and provided feedback to improve the user interface and to access documents beyond the group’s own history

The development of the surgical treatment of deafness.

We present an approach to global transaction management in workflow environments. The transaction mechanism is based on the well-known notion of sagas, but extended to deal with arbitrary process structures including cycles and savepoints that allow partial compensation. We present a formal specification of the transaction model and transaction management mechanisms in set and graph theory, providing clear, unambiguous transaction semantics. The specification is straightforwardly mapped to a modular architecture, the implementation of which is applied in the prototype of a commercial workflow management system. The loosely-coupled nature of the resulting system allows easy distribution using middleware technolog

Influence of Controlled and Uncontrolled Interventions on Twitter in Different Target Groups

Abstract—In this paper the influence of interventions on Twitter users is studied. We define influence in a) number of participants, b) size of the audience, c) amount of activity, and d) reach. Influence is studied for four different target groups: a) politicians, b) journalists, c) employees and d) the general public. Furthermore, two types of interventions are studied: a) by all Twitter users (i.e., uncontrolled interventions), and b) those tweeted by an organization that benefits from any resulting influence (i.e., controlled interventions). As a case study, tweets about a large Dutch governmental organization are used. Results show a clear relation between the number of uncontrolled interventions and influence in all four target groups, for each of the defined types of influence. Controlled interventions show less influence: Significant influence was found for the general public, but influence for politicians and employees was only mildly significant, and no influence was found for journalists. The effect found for uncontrolled interventions however suggests that this influence is indeed reachable for some target groups, even when the number of interventions is small, and very well reachable for all target groups, provided the number of interventions is large enough. In addition to this we found that interventions influence groups to a different extent. Own employees were influenced strongest, differing significantly from the other groups

Graphical uncertainty representations for ensemble predictions

We investigated how different graphical representations convey the underlying uncertainty distribution in ensemble predictions. In ensemble predictions, a set of forecasts is produced, indicating the range of possible future states. Adopting a use case from life sciences, we asked non-expert participants to compare ensemble predictions of the growth distribution of individual children to that of the normal population. For each individual child, the historical growth data of a set of 20 of its best matching peers was adopted as the ensemble prediction of the child’s growth curve. The ensemble growth predictions were plotted in seven different graphical formats (an ensemble plot, depicting all 20 forecasts and six summary representations, depicting the peer group mean and standard deviation). These graphs were plotted on a population chart with a given mean and variance. For comparison, we included a representation showing only the initial part of the growth curve without any future predictions. For 3 months old children that were measured at four occasions since birth, participants predicted their length at the age of 2 years. They compared their prediction to either (1) the population mean or to (2) a “normal” population range (the mean ± 2(standard deviation)). Our results show that the interpretation of a given uncertainty visualization depends on its visual characteristics, on the type of estimate required and on the user’s numeracy. Numeracy correlates negatively with bias (mean response error) magnitude (i.e. people with lower numeracy show larger response bias). Compared to the summary plots that yield a substantial overestimation of probabilities, and the No-prediction representation that results in quite variable predictions, the Ensemble representation consistently shows a lower probability estimation, resulting in the smallest overall response bias. The current results suggest that an Ensemble or “spaghetti plot” representation may be the best choice for communicating the uncertainty in ensemble predictions to non-expert users

An Architecture for Nested Transaction Support on Standard Database Systems

Many applications dealing with complex processes require database support for nested transactions. Current commercial database systems lack this kind of support, offering flat, non-nested transactions only. This paper presents a three-layer architecture for implementing nested transaction support on a commercial multi-database environment. The architecture is directed at high portability and flexibility. The modular approach and the simple, event driven interfaces between the layers of the architecture enable the nested transaction support to be adapted to various applications, nested transaction models and database management systems. The architecture has been implemented to support a prototype of a commercial next-generation workflow management system

Graphical uncertainty representations for ensemble predictions

We investigated how different graphical representations convey the underlying uncertainty distribution in ensemble predictions. In ensemble predictions, a set of forecasts is produced, indicating the range of possible future states. Adopting a use case from life sciences, we asked non-expert participants to compare ensemble predictions of the growth distribution of individual children to that of the normal population. For each individual child, the historical growth data of a set of 20 of its best matching peers was adopted as the ensemble prediction of the child’s growth curve. The ensemble growth predictions were plotted in seven different graphical formats (an ensemble plot, depicting all 20 forecasts and six summary representations, depicting the peer group mean and standard deviation). These graphs were plotted on a population chart with a given mean and variance. For comparison, we included a representation showing only the initial part of the growth curve without any future predictions. For 3 months old children that were measured at four occasions since birth, participants predicted their length at the age of 2 years. They compared their prediction to either (1) the population mean or to (2) a “normal” population range (the mean ± 2(standard deviation)). Our results show that the interpretation of a given uncertainty visualization depends on its visual characteristics, on the type of estimate required and on the user’s numeracy. Numeracy correlates negatively with bias (mean response error) magnitude (i.e. people with lower numeracy show larger response bias). Compared to the summary plots that yield a substantial overestimation of probabilities, and the No-prediction representation that results in quite variable predictions, the Ensemble representation consistently shows a lower probability estimation, resulting in the smallest overall response bias. The current results suggest that an Ensemble or “spaghetti plot” representation may be the best choice for communicating the uncertainty in ensemble predictions to non-expert users

The homebots system and field tests: A multi- commodity market for predictive load management

Paper submission to PAAM’99