Abstract. In this paper we describe IRS-II (Internet Reasoning Service) a framework and implemented infrastructure, whose main goal is to support the publication, location, composition and execution of heterogeneous web services, augmented with semantic descriptions of their functionalities. IRS-II has three main classes of features which distinguish it from other work on semantic web services. Firstly, it supports one-click publishing of standalone software: IRS-II automatically creates the appropriate wrappers, given pointers to the standalone code. Secondly, it explicitly distinguishes between tasks (what to do) and methods (how to achieve tasks) and as a result supports capabilitydriven service invocation; flexible mappings between services and problem specifications; and dynamic, knowledge-based service selection. Finally, IRS-II services are web service compatible -standard web services can be trivially published through the IRS-II and any IRS-II service automatically appears as a standard web service to other web service infrastructures. In the paper we illustrate the main functionalities of IRS-II through a scenario involving a distributed application in the healthcare domain.

In this paper we describe IRS-III which takes a semantic broker based approach to creating applications from Semantic Web Services by mediating between a service requester and one or more service providers. Business organisations can view Semantic Web Services as the basic mechanism for integrating data and processes across applications on the Web. This paper extends previous publications on IRS by providing an overall description of our framework from the point of view of application development. More specifically, we describe the IRS-III methodology for building applications using Semantic Web Services and illustrate our approach through a use case on e-government.

The Center for Data and Knowledge Integration for Health (CIDACS) was created in 2016 in Salvador (Bahia, Brazil). This paper aims to present a profile of CIDACS, including its current databases. CIDACS aims to conduct interdisciplinary studies and research, develop new scientific methodology and promote professional training using linked large-scale databases and high-performance computational resources in a secure environment. Administrative data is at the core of the activities conducted by CIDACS. The advantages of administrative data include significantly larger sample sizes, an inherent longitudinal structure and high-quality information. The center’s research projects are primarily focused on enhancing the understanding surrounding the impact of social protection policies (e.g., public cash-transfer and housing programs) on health outcomes in low-income populations throughout Brazil. CIDACS’ primary data source is citizens who register with the Cadastro Único program, which encompasses individuals eligible to receive benefits from over 20 governmental social programs. CIDACS has two separate environments for data handling: 1) Data Production Center, a secure room housing the computational infrastructure for ingesting, storing, cleaning, processing and linking original databases, as well as extracting research-ready datasets and 2) Data Analysis Environment, a computational infrastructure based on data safe haven principles, which allows researchers to access and process requested datasets. Brazil has a large public health community that uses national health and social databases for research programs, and the linkage of different databases has been a widely employed practice in the country. CIDACS is the result of efforts by researchers, policymakers and public health officials to use and improve the quality of Brazilian health databases. CIDACS is expected to be an important resource for researchers and policymakers interested in improving the evidence base in different aspects of health, as well as with regard to the social determinants of health and the effects of social and environmental policies on health in general.

The next Web generation promises to deliver Semantic Web Services (SWS); services that are self-described and amenable to automated discovery, composition and invocation. A prerequisite to this, however, is the emergence and evolution of the Semantic Web, which provides the infrastructure for the semantic interoperability of Web Services. Web Services will be augmented with rich formal descriptions of their capabilities, such that they can be utilized by applications or other services without human assistance or highly constrained agreements on interfaces or protocols. Thus, Semantic Web Services have the potential to change the way knowledge and business services are consumed and provided on the Web. In this paper, we survey the state of the art of current enabling technologies for Semantic Web Services. In addition, we characterize the infrastructure of Semantic Web Services along three orthogonal dimensions: activities, architecture and service ontology. Further, we examine and contrast three current approaches to SWS according to the proposed dimensions. Service Registry Service Requester Service Provider Service Description Web Service Publish Find Bind HTTP XML-S XML SOAP WSDL UDDI BEPL4 WS URIthe meaning of the interface description (typically through the use of meaningful label or variable names, comments, or additional documentation) and binds to (i.e. includes a call to invoke) the discovered service within the application they are developing. This application is known as the service requester. At this point, the service requester can automatically invoke the discovered service (provided by the service provider) using Web service communication protocols (i.e. SOAP). Key to the interoperation of Web services is an adoption of a set of enabling standard protocols. Several XML-based standards ( fig. 2) have been proposed to support the usage scenario previously described.

Abstract. Semantic Business Process Management (SBPM) has been proposed as an extension of BPM with Semantic Web and Semantic Web Services (SWS) technologies in order to increase and enhance the level of automation that can be achieved within the BPM life-cycle. In a nutshell, SBPM is based on the extensive and exhaustive conceptualization of the BPM domain so as to support reasoning during business processes modelling, composition, execution, and analysis, leading to important enhancements throughout the life-cycle of business processes. An important step of the BPM life-cycle is the analysis of the processes deployed in companies. This analysis provides feedback about how these processes are actually being executed (like common control-flow paths, performance measures, detection of bottlenecks, alert to approaching deadlines, auditing, etc). The use of semantic information can lead to dramatic enhancements in the state-of-the-art in analysis techniques. In this paper we present an outlook on the opportunities and challenges on semantic business process mining and monitoring, thus paving the way for the implementation of the next generation of BPM analysis tools.