Luiz Olavo Bonino da Silva Santos

The FAIR Guiding Principles for scientific data management and stewardship

There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

Towards a Goal-Based Service Framework for Dynamic Service Discovery and Composition

Service-Oriented Computing allows new applications to be developed by using and/or combining services offered by different providers. Service discovery and composition are performed aiming to comply with the client’s request in terms of functionality and expected outcome. In this paper we present a framework for dynamic service discovery and composition. This framework is based on goals and tasks as the means to represent the client’s expected outcome and functionality, respectively. The framework encompasses a goal-based service ontology, a set of domain and task ontologies and a supporting service platform with a service matching and composition algorithm. The client informs the platform about the goal to be fulfilled. The platform’s matching algorithm searches in the repository for services that can fulfill the client’s goal. Moreover, the platform gathers client’s contextual information to use as inputs for the services and thus, reduce the need for client interaction. If no single service is able to fulfill the user’s goal, a service composition is then performed.

Towards a BPM Cloud Architecture with Data and Activity Distribution

Nowadays, many organizations use BPM for capturing and monitoring their business processes. The introduction of BPM in an organization may become expensive, because of the upfront investments on software and hardware. Therefore, organizations can choose for a cloud-based BPM system, in which a BPM system can be used in a pay-per-use manner. Opting for cloud-based solutions may normally raise concerns in organizations such as privacy, security, legal constraints and control. By combining cloud-based and traditional BPM, organizations can benefit from the best of both worlds. This paper proposes a distribution solution in which a business process is separated into individual business processes to be executed in the cloud and on-premise. This solution gives users the freedom to place sensitive data and non-computation-intensive activities within the borders of their organization, whereas less sensitive data and computation-intensive activities can be placed in the cloud. In our proposed approach, the business processes for both on-premise and the cloud are created by performing a transformation on the original business processes, guided by a distribution list in which the placement of each activity and data element is defined. This paper discusses the challenges of implementing this transformation.

GSO: Designing a well-founded service ontology to support dynamic service discovery and composition

A pragmatic and straightforward approach to semantic service discovery is to match inputs and outputs of user requests with the input and output requirements of registered service descriptions. This approach can be extended by using pre-conditions, effects and semantic annotations (meta-data) in an attempt to increase discovery accuracy. While on one hand these additions help improve discovery accuracy, on the other hand complexity is added as service users need to add more information elements to their service requests. In this paper we present an approach that aims at facilitating the representation of service requests by service users, without loss of accuracy. We introduce a Goal-Based Service Framework (GSF) that uses the concept of goal as an abstraction to represent service requests. This paper presents the core concepts and relations of the Goal-Based Service Ontology (GSO), which is a fundamental component of the GSF, and discusses how the framework supports semantic service discovery and composition. GSO provides a set of primitives and relations between goals, tasks and services. These primitives allow a user to represent its goals, and a supporting platform to discover or compose services that fulfil them.

A Transformation-Based Approach to Business Process Management in the Cloud

Business Process Management (BPM) has gained a lot of popularity in the last two decades, since it allows organizations to manage and optimize their business processes. However, purchasing a BPM system can be an expensive investment for a company, since not only the software itself needs to be purchased, but also hardware is required on which the process engine should run, and personnel need to be hired or allocated for setting up and maintaining the hardware and the software. Cloud computing gives its users the opportunity of using computing resources in a pay-per-use manner, and perceiving these resources as unlimited. Therefore, the application of cloud computing technologies to BPM can be extremely beneficial specially for small and middle-size companies. Nevertheless, the fear of losing or exposing sensitive data by placing these data in the cloud is one of the biggest obstacles to the deployment of cloud-based solutions in organizations nowadays. In this paper we introduce a transformation-based approach that allows companies to control the parts of their business processes that should be allocated to their own premises and to the cloud, to avoid unwanted exposure of confidential data and to profit from the high performance of cloud environments. In our approach, the user annotates activities and data that should be placed in the cloud or on-premise, and an automated transformation generates the process fragments for cloud and on-premise deployment. The paper discusses the challenges of developing the transformation and presents a case study that demonstrates the applicability of the approach.

Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud

The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable. As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in reality was largely open to interpretation. As support for the Principles has spread, so has the breadth of these interpretations. In observing this creeping spread of interpretation, several of the original authors felt it was now appropriate to revisit the Principles, to clarify both what FAIRness is, and is not.

From User Goals to Service Discovery and Composition

Goals are often used to represent stakeholders objectives. The intentionality inherited by a goal drives stakeholders to pursuit the fulfillment of their goals either by themselves or by delegating this fulfillment to third parties. In Service-Oriented Computing, service clients requirements are commonly expressed in terms of inputs, outputs, pre-conditions and effects, also known as IOPE. End-users, i.e., human service clients, may have difficulties to express such requirements as they would have to deal with technical issues such as the requests language, and the type, format and coding of the IOPE. This paper presents the core concepts of the Goal-Based Service Ontology (GSO) that relates goals and services. By grounding GSO in a well-founded ontology we aim at clarifying the semantics for a set of relevant domain concepts that can support specialists in defining application ontologies based on goals and services.

A service-oriented middleware for context-aware applications

Context awareness has emerged as an important element in distributed computing. It offers mechanisms that allow applications to be aware of their environment and enable these applications to adjust their behavior to the current context. Considering the dynamic nature of context, the data flow of relevant contextual information can be significant. In order to keep track of this information flow, a flexible service mechanism should be available for the client applications. In this document we present a service-oriented middleware for context-aware applications. This middleware provides support to leverage the development of context-aware applications by providing a scripting-like approach for context-aware application development; allowing the subscription of rules containing context-based events and conditions and a notification to be sent when the specified context holds. Moreover, a domain-specific language has been developed to express these context-based rules.

An Approach to Dynamic Provisioning of Social and Computational Services

Service-Oriented Computing (SOC) builds upon the intuitive notion of service already known and used in our society for a long time. SOC-related approaches are based on computer-executable functional units that often represent automation of services that exist at the social level, i.e., services at the level of human or organizational interactions. With the increasing adoption of SOC, more complex scenarios mixing computational and social services are emerging, raising the need to better understand the relationship between social and computational services and to specify and model them accordingly. In this paper we present our ontology-based approach to dynamic service provisioning. Our approach aims at improving the current state of the art by allowing an explicit distinction between social and computation services and dynamic service provisioning support for these two types of services. We illustrate the applicability of our approach with a use case scenario in the health care domain.

Service Provisioning Support for Non-technical Service Clients

Recently paradigms such as Service-Oriented and Pervasive Computing are merging in scenarios where users are surrounded by a plethora of computing devices and available services. Dealing with this potentially large number of devices and services can become overwhelming to users without appropriate software support. Moreover, in the case of non-technical users, an additional difficulty is to express service requests using technical concepts such as data types, XML documents, etc. In this paper we present the architectural design of a software platform aiming at supporting the service provisioning for non-technical users. The platform also makes use of the surrounding computing devices to gather contextual information that helps in the tasks of service discovery, selection and composition.