Wanting to do research?
You would like to do research? Maybe your MSc or PhD? You love to discover new things? To propose new innovative ideas? You like the areas of Service Science, Business Process Management, Information Systems, and Semantic Web?
Then you should send me an e-mail (jcardoso hhatte dei.uc.pt) and/or we should have a chat (office D2.20). I always have a couple of interresting topics to be explored.
My current research interests
The Rise of Service Networks ...
Services have generated a tremendous interest and uptake by researchers and by the industry in recent years. However, the truth added value of services is still in its infancy. In particular, it is currently almost impossible to understand the underlying principles the govern service networks. A service network is a structure made up of a set of services (such as Web services, Software-as-a-Service, human-based services, etc.) and the relationships between these services. With the growth of the Internet, the study of networks, such as service network and social networks, is gaining a lot of attention.
Our research focuses on the particularly challenging task of reasoning about open service networks, i.e., on obtaining answers to questions which require accessing, retrieving, and combining information from different service models globally distributed. Service models can be (re-)constructed from the information present in the Web which describes, e.g., Web services or Cloud services. Understanding how services evolve as a system, the related risks and gains of different topologies of service networks is becoming increasingly critical for society. For example, an analysis can provide information on the tolerance level to failures and attacks. However, currently available techniques fall short of providing workable solutions as they are unable to deal with the lack of expressive service model representations, the absence of mechanisms to freely access to open and distributed service models, and the lack of scalable reasoning algorithms.
We take the challenge of developing a novel perspective on the global economy by linking service models representing transparent, open services. We propose an approach to discover open service networks and reason about their topology using scalable algorithms to better understand how global service markets operate. The difficulties faced in doing so differ significantly from those faced by prior work in global distributed information systems. We address them by using exploratory techniques for overcoming hidden service information and semantic heterogeneity including:
- Service Systems to model global service networks and their relationships. Identify richer, broader, and more relevant relationships between service models to enable a valuable service networks reasoning. Here, the models we have already developed and proposed, such as USDL and OSSR, to represent services and relationships, respectively, will be fundamental.
- Semantic Web and Distributed Systems to access and retrieve open service models at a global scale using semantics and massively parallel platforms to store and represent distributed service networks. The use of MapReduce and other programming models for processing large service sets will enable to create and analyze large servicesets.
- System Dynamics and Analytics to understand and reason about the dynamics involving service interactions that drive the topology of global service networks. Simulate the evolution of service networks in response to alterations of software architectures, software trends, and opportunities. The analysis of human-based service systems will also constitute an important undertaking.
As an overarching goal, we explore novel principals and theories for an entirely new challenge which was intensified with the rise of service-based economies. Our contributions will advance the state of the art in worldwide service networks understanding and reasoning with its unique characteristics and difficulties.
Please go to Genssiz, the Center for Service Systems Research, for more information on our work.
A good researcher says, "Lets find out", others say "Nobody knows". When a good researcher makes a mistake, he says, I was wrong", others say "It wasn't my fault". A good researcher works harder than others and has more time. Others are always "too busy" to do what is necessary.
- Adapted from Web page n. 1.236.784.322.345 of the Internet
Departamento de Engenharias Informática
Universidade da Coimbra
jcardoso [*.A._.T$] dei.uc.pt