Facilitating cross-organisational workflows with a workflow view approach

Interconnecting business processes across systems and organisations is considered to provide significant benefits, such as greater process transparency, higher degrees of integration, facilitation of communication, and consequently higher throughput in a given time interval. However, to achieve these benefits requires tackling constraints. In the context of this paper these are privacy-requirements of the involved workflows and their mutual dependencies. Workflow views are a promising conceptional approach to address the issue of privacy; however this approach requires addressing the issue of interdependencies between workflow view and adjacent private workflow. In this paper we focus on three aspects concerning the support for execution of cross-organisational workflows that have been modelled with a workflow view approach: (i) communication between the entities of a view-based workflow model, (ii) their impact on an extended workflow engine, and (iii) the design of a cross-organisational workflow architecture (CWA). We consider communication aspects in terms of state dependencies and control flow dependencies. We propose to tightly couple private workflow and workflow view with state dependencies, whilst to loosely couple workflow views with control flow dependencies. We introduce a Petri-Net-based state transition approach that binds states of private workflow tasks to their adjacent workflow view-task. On the basis of these communication aspects we develop a CWA for view-based cross-organisational workflow execution. Its concepts are valid for mediated and unmediated interactions and express no choice of a particular technology. The concepts are demonstrated by a scenario, run by two extended workflow management systems. (C) 2004 Elsevier B.V. All rights reserved.

How do practitioners use conceptual modeling in practice?

Much research has been devoted over the years to investigating and advancing the techniques and tools used by analysts when they model. As opposed to what academics, software providers and their resellers promote as should be happening, the aim of this research was to determine whether practitioners still embraced conceptual modeling seriously. In addition, what are the most popular techniques and tools used for conceptual modeling? What are the major purposes for which conceptual modeling is used? The study found that the top six most frequently used modeling techniques and methods were ER diagramming, data flow diagramming, systems flowcharting, workflow modeling, UML, and structured charts. Modeling technique use was found to decrease significantly from smaller to medium-sized organizations, but then to increase significantly in larger organizations (proxying for large, complex projects). Technique use was also found to significantly follow an inverted U-shaped curve, contrary to some prior explanations. Additionally, an important contribution of this study was the identification of the factors that uniquely influence the decision of analysts to continue to use modeling, viz., communication (using diagrams) to/from stakeholders, internal knowledge (lack of) of techniques, user expectations management, understanding models' integration into the business, and tool/software deficiencies. The highest ranked purposes for which modeling was undertaken were database design and management, business process documentation, business process improvement, and software development. (c) 2005 Elsevier B.V. All rights reserved.

Extending choreography with business contract constraints

Business contracts play a central role in governing commercial interactions between organizations. It is increasingly recognized that business contract conditions need to be closely linked to internal and external business processes, both to reduce the risk of contract violations and to ensure compliance with legislative regimes. Recent research has proposed contract languages allowing the specification of obligations, permissions and prohibitions in business contracts. Business processes that cross-organizational boundaries can be specified in choreography and coordination languages but these do not provide appropriate abstractions for contract constraints. In this paper, we examine the transformation of contract constraints in a business contract language into expressions in a choreography language. An example cross-organizational process is presented, along with a specification of the process in a choreography language and a specification of a set of contract conditions for the process in a business contract language. The contract terms are then translated into choreography expressions that govern the process to ensure compliance. Subsequent discussion explores a number of business and technology issues related to the results. We conclude that cross-organizational business processes can be monitored and enforced according to business contract specifications through the transformation of a contract definition to constraints on process behavior.

Selecting optimal instantiations of data models - Theory and validation of an ex ante approach

The schema of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. Obtaining quickly the appropriate data increases the likelihood that an organization will make good decisions and respond adeptly to challenges. This research presents and validates a methodology for evaluating, ex ante, the relative desirability of alternative instantiations of a model of data. In contrast to prior research, each instantiation is based on a different formal theory. This research theorizes that the instantiation that yields the lowest weighted average query complexity for a representative sample of information requests is the most desirable instantiation for end-user queries. The theory was validated by an experiment that compared end-user performance using an instantiation of a data structure based on the relational model of data with performance using the corresponding instantiation of the data structure based on the object-relational model of data. Complexity was measured using three different Halstead metrics: program length, difficulty, and effort. For a representative sample of queries, the average complexity using each instantiation was calculated. As theorized, end users querying the instantiation with the lower average complexity made fewer semantic errors, i.e., were more effective at composing queries. (c) 2005 Elsevier B.V. All rights reserved.

Intelligent agent supported personalization for virtual learning environments

Virtual learning environments (VLEs) are computer-based online learning environments, which provide opportunities for online learners to learn at the time and location of their choosing, whilst allowing interactions and encounters with other online learners, as well as affording access to a wide range of resources. They have the capability of reaching learners in remote areas around the country or across country boundaries at very low cost. Personalized VLEs are those VLEs that provide a set of personalization functionalities, such as personalizing learning plans, learning materials, tests, and are capable of initializing the interaction with learners by providing advice, necessary instant messages, etc., to online learners. One of the major challenges involved in developing personalized VLEs is to achieve effective personalization functionalities, such as personalized content management, learner model, learner plan and adaptive instant interaction. Autonomous intelligent agents provide an important technology for accomplishing personalization in VLEs. A number of agents work collaboratively to enable personalization by recognizing an individual's eLeaming pace and reacting correspondingly. In this research, a personalization model has been developed that demonstrates dynamic eLearning processes; secondly, this study proposes an architecture for PVLE by using intelligent decision-making agents' autonomous, pre-active and proactive behaviors. A prototype system has been developed to demonstrate the implementation of this architecture. Furthemore, a field experiment has been conducted to investigate the performance of the prototype by comparing PVLE eLearning effectiveness with a non-personalized VLE. Data regarding participants' final exam scores were collected and analyzed. The results indicate that intelligent agent technology can be employed to achieve personalization in VLEs, and as a consequence to improve eLeaming effectiveness dramatically.

An approach to ontology for institutional facts in the semantic web

Refinement in software engineering allows a specification to be developed in stages, with design decisions taken at earlier stages constraining the design at later stages. Refinement in complex data models is difficult due to lack of a way of defining constraints, which can be progressively maintained over increasingly detailed refinements. Category theory provides a way of stating wide scale constraints. These constraints lead to a set of design guidelines, which maintain the wide scale constraints under increasing detail. Previous methods of refinement are essentially local, and the proposed method does not interfere very much with these local methods. The result is particularly applicable to semantic web applications, where ontologies provide systems of more or less abstract constraints on systems, which must be implemented and therefore refined by participating systems. With the approach of this paper, the concept of committing to an ontology carries much more force. (c) 2005 Elsevier B.V. All rights reserved.

Vector Error-Correction Models in a consumer packaged goods category forecasting decision support system

A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.

An adaptive and dynamic dimensionality reduction method for high-dimensional indexing

The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approach to overcome degradation in performance with respect to increasing dimensions is to reduce the dimensionality of the original dataset before constructing the index. However, identifying the correlation among the dimensions and effectively reducing them are challenging tasks. In this paper, we present an adaptive Multi-level Mahalanobis-based Dimensionality Reduction (MMDR) technique for high-dimensional indexing. Our MMDR technique has four notable features compared to existing methods. First, it discovers elliptical clusters for more effective dimensionality reduction by using only the low-dimensional subspaces. Second, data points in the different axis systems are indexed using a single B+-tree. Third, our technique is highly scalable in terms of data size and dimension. Finally, it is also dynamic and adaptive to insertions. An extensive performance study was conducted using both real and synthetic datasets, and the results show that our technique not only achieves higher precision, but also enables queries to be processed efficiently. Copyright Springer-Verlag 2005

Specification and validation of process constraints for flexible workflows

Workflow systems have traditionally focused on the so-called production processes which are characterized by pre-definition, high volume, and repetitiveness. Recently, the deployment of workflow systems in non-traditional domains such as collaborative applications, e-learning and cross-organizational process integration, have put forth new requirements for flexible and dynamic specification. However, this flexibility cannot be offered at the expense of control, a critical requirement of business processes. In this paper, we will present a foundation set of constraints for flexible workflow specification. These constraints are intended to provide an appropriate balance between flexibility and control. The constraint specification framework is based on the concept of pockets of flexibility which allows ad hoc changes and/or building of workflows for highly flexible processes. Basically, our approach is to provide the ability to execute on the basis of a partially specified model, where the full specification of the model is made at runtime, and may be unique to each instance. The verification of dynamically built models is essential. Where as ensuring that the model conforms to specified constraints does not pose great difficulty, ensuring that the constraint set itself does not carry conflicts and redundancy is an interesting and challenging problem. In this paper, we will provide a discussion on both the static and dynamic verification aspects. We will also briefly present Chameleon, a prototype workflow engine that implements these concepts. (c) 2004 Elsevier Ltd. All rights reserved.

Using BWW model to evaluate building ontologies in CGs formalism

The Bunge-Wand-Weber (BWW) representation model defines ontological constructs for information systems. According to these constructs the completeness and efficiency of a modeling technique can be defined. Ontology plays an essential role in e-commerce. Using or updating an existing ontology and providing tools to solve any semantic conflicts become essential steps before putting a system online. We use conceptual graphs (CGs) to implement ontologies. This paper evaluates CG capabilities using the BWW representation model. It finds out that CGs are ontologically complete according to Wand and Weber definition. Also it finds out that CGs have construct overload and construct redundancy which can undermine the ontological clarity of CGs. This leads us to build a meta-model to avoid some ontological-unclarity problems. We use some of the BWW constructs to build the meta-model. (c) 2004 Elsevier Ltd. All rights reserved.

Communicative practices in online communication: A case of agreeing to disagree

Online communities have evolved beyond the realm of social phenomenon to become important knowledge-sharing media with real economic consequences. However, the sharing of knowledge and the communication of meaning through Internet technology presents many difficulties. This is particularly so for online finance forums where market-sensitive information and disinformation about exchange-traded stocks is regularly disseminated. The development of trust and the effect of misinformation in this environment are important in the growth of this communication medium. Forum administrators need to better understand and handle the development of trust. In this article, we analyze and discuss the communicative practices of a group of investors and members of an online community of interest. We found that conflict as a driver of knowledge sharing is an important consideration for forum administrators and designers.

A multiresolution terrain model for efficient visualization query processing

Multiresolution Triangular Mesh (MTM) models are widely used to improve the performance of large terrain visualization by replacing the original model with a simplified one. MTM models, which consist of both original and simplified data, are commonly stored in spatial database systems due to their size. The relatively slow access speed of disks makes data retrieval the bottleneck of such terrain visualization systems. Existing spatial access methods proposed to address this problem rely on main-memory MTM models, which leads to significant overhead during query processing. In this paper, we approach the problem from a new perspective and propose a novel MTM called direct mesh that is designed specifically for secondary storage. It supports available indexing methods natively and requires no modification to MTM structure. Experiment results, which are based on two real-world data sets, show an average performance improvement of 5-10 times over the existing methods.

Hierarchical indexing structure for efficient similarity search in video retrieval

With the rapid increase in both centralized video archives and distributed WWW video resources, content-based video retrieval is gaining its importance. To support such applications efficiently, content-based video indexing must be addressed. Typically, each video is represented by a sequence of frames. Due to the high dimensionality of frame representation and the large number of frames, video indexing introduces an additional degree of complexity. In this paper, we address the problem of content-based video indexing and propose an efficient solution, called the Ordered VA-File (OVA-File) based on the VA-file. OVA-File is a hierarchical structure and has two novel features: 1) partitioning the whole file into slices such that only a small number of slices are accessed and checked during k Nearest Neighbor (kNN) search and 2) efficient handling of insertions of new vectors into the OVA-File, such that the average distance between the new vectors and those approximations near that position is minimized. To facilitate a search, we present an efficient approximate kNN algorithm named Ordered VA-LOW (OVA-LOW) based on the proposed OVA-File. OVA-LOW first chooses possible OVA-Slices by ranking the distances between their corresponding centers and the query vector, and then visits all approximations in the selected OVA-Slices to work out approximate kNN. The number of possible OVA-Slices is controlled by a user-defined parameter delta. By adjusting delta, OVA-LOW provides a trade-off between the query cost and the result quality. Query by video clip consisting of multiple frames is also discussed. Extensive experimental studies using real video data sets were conducted and the results showed that our methods can yield a significant speed-up over an existing VA-file-based method and iDistance with high query result quality. Furthermore, by incorporating temporal correlation of video content, our methods achieved much more efficient performance.

ICICLE: A semantic-based retrieval system for WWW images

In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.

Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.