Integration and Data Sharing between WS-Based Workflows

In this paper we present a workflow portal for Grid applications, which supports different workflow languages and workflow optimization. We present an XSLT converter that converts from one workflow language to another and enables the interoperation between different workflow languages. We discuss strategies for choosing the optimal service from several semantically equivalent Web services in a Grid application. The dynamic selection of Web services involves discovering a set of semantically equivalent services by filtering the available services based on metadata, and selecting an optimal service based on real‐time data and/or historical data recorded during prior executions. Finally, we describe the framework and implementation of the workflow portal which aggregates different components of the project using Java portlets. Copyright © 2007 John Wiley & Sons, Ltd.

Because of the strong request for data exchange under information environment, the existing information needs to be integrated and shared. And, the popularity of software-as-aservice (SaaS) caused that users need data integration. Traditional approach of data integration cannot accord with the complex information environment and cannot provide SaaS users with efficient data exchange and application integration. The paper proposes data integration as a service for Applications Deployment on the SaaS Platform that can hide heterogeneous data. It highlights the user's capability of accessing data. Compared with the traditional approach of data integration, it has many characteristics, such as expansibility, load balancing. It makes real-time data exchange and application integration possible. It improves the development of information resources and the integration of work flow.

A problem in most of the organizations is to find the best way to mature their business processes. Process maturity can make the organizations more profitable and competent for other competitors. The problem can be solved by aligning service oriented architecture (using web services) with business processes within the organization. The purpose of this paper is to design a conceptual framework for aligning business processes with the Service Oriented Architecture and then prove the framework’s validity using simulation. An organization is working in education sector and wants to integrate its multiple web applications to allow data flow from one system to another. The framework will help the organization to align business process of service oriented architecture and to easily mold their business process according to business needs. The framework’s validity will be proved by simulating the entire process using Yet Another Workflow Language (YAWL).

Pagers, cellular phones, smart appliances, and Web services - these products and services are almost omnipresent in our world, and are stimulating the creation of a new breed of software: applications that must deal with inputs from a variety of sources, provide real-time responses, deliver strong security - and do all this while providing a positive user experience. In response, a new style of application programming is taking hold, one that is based on multiple threads of control and the asynchronous exchange of data, and results in fundamentally more complex applications.

Modelling complex and flexible processes for smart cyber-physical environments

Distributed embedded computing differs itself from traditional computing by its great heterogeneous, dynamic and non-standardized nature. This requires more powerful technologies that enable us to develop systems with more flexible architectures. Workflow technology achieves this by managing collaborations between system elements explicitly. However, in distributed embedded environment, current workflow systems could not be used directly for the reason of very different supporting platforms. Distributed resource management technology could bridge this gap. In this paper, we classify distributed embedded systems into fundamental types of elements representing both basic structural components and relationship between them. Then we present an architecture based on the integration of workflow and DRM systems according to our classification and analyze important coordination mechanisms among workflow, DRM systems and other elements. Ideas, such as utilizing function model to customize and optimize the design of systems, also reflect important principles to design distributed embedded systems.KeywordsEmbed SystemInteraction PatternSystem ElementDistribute File SystemCollaborative ElementThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Background: The U.S. Medicare Annual Wellness Visit (AWV) offers a structured opportunity for cognitive screening and personalized prevention planning among older adults. Yet, implementation of AWVs, particularly for individuals with cognitive impairment, remains inconsistent across primary care or other diverse care settings. Methods: We conducted a scoping review using the Consolidated Framework for Implementation Research (CFIR) to explore multilevel factors influencing the implementation of the Medicare AWV's cognitive screening component, with a focus on how these processes support the detection and management of cognitive impairment among older adults. We searched four databases and screened peer-reviewed studies published between 2011 and March 2025. Searches were conducted in Ovid MEDLINE, PubMed, EBSCOhost, and CINAHL databases. The initial search was completed on 3 January 2024 and updated monthly through 30 March 2025. All retrieved citations were imported into EndNote 21, where duplicates were removed. We screened titles and abstracts for relevance using the predefined inclusion criteria. Full-text articles were then reviewed and scored as either relevant (1) or not relevant (0). Discrepancies were resolved through consensus discussions. To assess the methodological quality of the included studies, we used the Joanna Briggs Institute critical appraisal tools appropriate to each study design. These tools evaluate rigor, trustworthiness, relevance, and risk of bias. We extracted the following data from each included study: Author(s), year, title, and journal; Study type and design; Data collection methods and setting; Sample size and population characteristics; Outcome measures; Intervention details (AWV delivery context); and Reported facilitators, barriers, and outcomes related to AWV implementation. The first two authors independently coded and synthesized all relevant data using a table created in Microsoft Excel. The CFIR guided our data analysis, thematizing our findings into facilitators and barriers across its five domains, viz: (1) Intervention Characteristics, (2) Outer Setting, (3) Inner Setting, (4) Characteristics of Individuals, and (5) Implementation Process. Results: Among 19 included studies, most used quantitative designs and secondary data. Our CFIR-based synthesis revealed that AWV implementation is shaped by interdependent factors across five domains. Key facilitators included AWV adaptability, Electronic Health Record (EHR) integration, team-based workflows, policy alignment (e.g., Accountable Care Organization participation), and provider confidence. Barriers included vague Centers for Medicare and Medicaid Services (CMS) guidance, limited reimbursement, staffing shortages, workflow misalignment, and provider discomfort with cognitive screening. Implementation strategies were often poorly defined or inconsistently applied. Conclusions: Effective AWV delivery for older adults with cognitive impairment requires more than sound policy and intervention design; it demands organizational readiness, structured implementation, and engaged providers. Tailored training, leadership support, and integrated infrastructure are essential. These insights are relevant not only for U.S. Medicare but also for global efforts to integrate dementia-sensitive care into primary health systems. Our study has a few limitations that should be acknowledged. First, our scoping review synthesized findings predominantly from quantitative studies, with only two mixed-method studies and no studies using strictly qualitative methodologies. Second, few studies disaggregated findings by race, ethnicity, or geography, reducing our ability to assess equity-related outcomes. Moreover, few studies provided sufficient detail on the specific cognitive screening instruments used or on the scope and delivery of educational materials for patients and caregivers, limiting generalizability and implementation insights. Third, grey literature and non-peer-reviewed sources were not included. Fourth, although CFIR provided a comprehensive analytic structure, some studies did not explicitly fit in with our implementation frameworks, which required subjective mapping of findings to CFIR domains and may have introduced classification bias. Additionally, although our review did not quantitatively stratify findings by year, we observed that studies from more recent years were more likely to emphasize implementation facilitators (e.g., use of templates, workflow integration), whereas earlier studies often highlighted systemic barriers such as time constraints and provider unfamiliarity with AWV components. Finally, while our review focused specifically on AWV implementation in the United States, we recognize the value of comparative analysis with international contexts. This work was supported by a grant from the National Institute on Aging, National Institutes of Health (Grant No. 1R01AG083102-01; PIs: Tzeng, Kuo, & Raji).

The rapid growth of diverse clinical data, such as electronic health records (EHRs), lab results, and medical imaging, has opened new possibilities for data-driven decision-making in healthcare. However, issues with data quality, model interpretability, and workflow integration have hindered the safe and effective use of machine learning (ML) in clinical settings. This paper presents a clear multimodal ML framework for real-time clinical decision-making. It combines structured EHR data, lab tests, and imagingderived features to aid in diagnosis, risk prediction, and personalized treatment planning. The framework integrates supervised learning models, including Random Forest, Gradient Boosting Machines, Support Vector Machines, and Logistic Regression, along with unsupervised techniques like k-means clustering and Principal Component Analysis. This setup allows for both predictive modelling and patient grouping. We use strong preprocessing, feature selection, and cross-validation to manage missing data, reduce overfitting, and improve generalization. Model performance is measured using metrics such as accuracy, precision, recall, F1-score, and AUC-ROC, with Random Forest and Gradient Boosting showing the best results overall. To meet the important need for transparency, we include SHAP (Shapley Additive explanations) to provide explanations of model outputs, both globally and at the patient level. This helps clinicians understand the main factors behind predictions and builds trust in the system’s recommendations. The proposed framework is made for easy integration into current clinical workflows and allows for near real-time updates as new patient data come in. Overall, this work shows that a clear, multimodal ML framework can improve clinical decision-making and sets the stage for future evaluations and broader use in healthcare.

Web service is a promising technology to efficiently integrate disparate software components over various types of systems and to exchange various business artifacts among business organizations. As many web services are nowadays available on Internet, quality of services (QoS) becomes increasingly important to distinguish different service providers. Performance mainly characterizes QoS especially in mission critical services. However, performance analysis is a very difficult job, since it involves nondeterministic networks, frequent changes on workload intensity and unexpected usage patterns. In this work, we introduce sPAC (Web Services Performance Analysis Centre) and show how customers can verify timeliness of their web services semi-automatically. sPAC 1) graphically describes the workflow of web services, 2) automatically generates test codes for the web services and invokes them for performance tests using Java threads, 3) automatically generates a simulation model for the specified workflow model, and conducts extensive simulations for various load conditions and usage patterns, and 4) reports analysis and estimation results to help customers determine if the composed web services can meet the performance requirements.

A new technological standard, called 'Web services' has recently made its first appearance in the Web technologies arena. Our question here is: what is the role of Web services for eGovernment? In the present contribution, the concept of 'political value chain' is introduced and the process of value reconfiguration is illustrated, evidencing one of the potential roles of IT on administrative activities: the facilitation of 'citizen value' creation activities connection. A brief illustration of the Web services technology is then given, finally exploring its potential for e-Government activities and the related research issues.

Brain Informatics is a new interdisciplinary field of science, which studies the mechanisms of human information processing and, in some cases, also mechanisms causing the development of cognitive and other mental disturbances. Like other e-Science disciplines, it is accompanied with collection of large distributed datasets, which have to be efficiently managed, processed and analyzed. The Grid is an appropriate platform allowing solution of such ambitious tasks. This paper presents a Grid-based infrastructure called GridMiner providing the kernel functionality, like workflow management, visualization, data preprocessing, filtering, transformation and integration, data mining and data warehousing services, etc., supporting analytical tasks required by the Brain Informatics research and applications.

A distributed system always runs on top of a computer network and cannot be separated from it. In many cases this network consists of hundreds or thousands of computers and processing nodes. An effective distributed system simulator needs to simulate the underlying network. Unfortunately a great majority of existing simulation tools are pure network simulators. Even though they are very effective for designing, and evaluating computer networks, they could not be used to simulate a distributed application like a web service based application. Many components in a distributed system are complex servers and software applications running on top of all network layers. Network simulators cannot simulate them. A higher-level simulator is required to simulate their behavior. This work introduces an agent-based simulation model that integrates the simulation of a computer network and higher-level components of a distributed application. The distributed nature of agents makes them suitable to model and simulate distributed architectures including computer networks and distributed systems. To evaluate this approach the behavior of a replicated web service application will be simulated to show how effectively multi- agent-systems could be used to simulate the behavior of a distributed system.

Key-word based researches of service discovery focus on direct match of userpsilas requirements and often neglect relations between services. While techniques based on conventional semantic offer many kinds of relations, considerable time is spent on reasoning. In this paper, we utilizes E-FCM (Element Fuzzy Cognitive Map) to describe services for the reason that E-FCM can keep the semantic information as much as possible and E-FCMs can be automatically created for web services. Furthermore, instead of reasoning, the semantic relations among E-FCM are built based on computation, therefore semantic relations among services can be found out quickly. We focus on the associated semantic relations among services because complex applications always comprise of services with associated functions. The associated link network (ALN) is constructed upon associated relations to generate associated web service flows, which can be used to create complex applications, thus to facilitate discovery efficiency and improve utilization of services.

Web services is a special case of a service-oriented architecture (SOA), which is, basically, a representation of web application‘s functionality. Web service is more of a generalized concept that implies whole functionality as a whole but Microservice handles only the single specific task. MSA is emerging as an excellent architecture style enabling the division of large and complex applications into micro-scale yet many services, each runs in its own process, has its own APIs, and communicates with one another using lightweight mechanisms such as HTTP. Microservices are built around business capabilities, loosely coupled and highly cohesive, horizontally scalable, independently deployable, technology-agnostic, etc. On the other side for the business dynamic requirement these microservices need to be composed for the realization of enterprise-scale, and business-critical applications. Service composition is combining various services together to provide the solution for the user dynamic queries. There are two methods for the microservice composition i.e. orchestration and choreography. In this paper,a health case study is performed for the selection mechanism of orchestration method and choreography method in various situation.

Web Services form a new, emerging paradigm to handle distributed access to resources over the Internet. There are platform independent standards (SOAP, WSDL), which make the developers? task considerably easier. This article discusses how web services could be used in the context of the Virtual Observatory. We envisage a multi-layer architecture, with interoperating services. A well-designed lower layer consisting of simple, standard services implemented by most data providers will go a long way towards establishing a modular architecture. More complex applications can be built upon this core layer. We present two prototype applications, the SdssCutout and the SkyQuery as examples of this layered architecture.