Jano Moreira de Souza

Profiling and Matchmaking Strategies in Support of Opportunistic Collaboration

With the recent advances in communications technologies and decentralization of work practices, there has been an increase in distributed, remote, computerized work environments. In most systems, individuals work from their personal computer terminals, unaware of their peers. With the change from a physical to a virtual environment, opportunities for collaboration often go unnoticed. In this paper, we focus on how to bring unplanned collaboration about. We present an agent framework to encourage and support unplanned cooperation between people. Agents build user profiles through analysis of their documents and work environment and match them according to their interests, activities and opportunities for collaboration. By matching users’ work contexts, needs and resources, we expect to uncover opportunities for collaboration, filter down the information to be provided and determine the moment and recipients of the information. The notification of these opportunities should lead to more frequent collaboration between users. Resource sharing is facilitated in the hopes of stimulating collaboration.

Group and link analysis of multi-relational scientific social networks

Analyzing social networks enables us to detect several inter and intra connections between people in and outside their organizations. We model a multi-relational scientific social network where researchers may have four different types of relationships with each other. We adopt some criteria to enable the modeling of a scientific social network as close as possible to reality. Using clustering techniques with maximum flow measure, we identify the social structure and research communities in a way that allows us to evaluate the knowledge flow in the Brazilian scientific community. Finally, we evaluate the temporal evolution of scientific social networks to suggest/predict new relationships.

Coordination aspects in a spatial group decision support collaborative system

SPeCS a Spatial Group Decision Collaborative Support System intends to integrate Geographic Information Systems (GIS), Group Decision Support Systems (GDSS), Electronic Meeting Systems (EMS), and Workflow concepts in a framework based on Coordination premises. The coordination features should aid design team members to cope with their activities supporting the aspects of multi-criteria spatial analysis within a distributed GIS. Coordination aspects of SPeCS, which can vary from workflow facilities to integrated decision support tools can, intensively enhance the resolutions achieved that should represent the consensus in a decision-making process. This work presents a prototype, which explores the coordination in a spatial collaborative environment that supports the georeferencing of the argumentation just as they are being produced by the discussion involving the members of the design team. The main task of these groups is to produce a proposal for environmental preservations or changes considering social economics, climate and soil aspects.

GCC: a knowledge management environment for research centers and universities

Research centers and universities are knowledge-intensive institutions, where the knowledge creation and distribution are constant – and this knowledge should be managed. In spite of it, scientific work had been known for being solitary work, in which human interaction happened only in small groups within a research domain. Nowadays, due to technology improvements, scientific data from different sources is available, communication between researchers is facilitated and scientific information creation and exchange is faster than in the past. However, the focus on information exchange is too limited to create systems that enable true cooperation and knowledge management in scientific environments. To facilitate a more expressive exchanging, sharing and dissemination of knowledge and its management, we create a scientific knowledge management environment in which researchers may share their data, experiences, ideas, process definition and execution, and obtain all the necessary information to execute their tasks, make decisions, learn and disseminate knowledge.

An approach to requirements categorization using Kano's model and crowds

Despite advances in the requirements elicitation techniques, researchers show that even today software engineers cannot understand exactly what a product should offer to meet user needs and expectations. This paper aims to propose a new strategy to assist the process of requirements categorization, so that it becomes possible to extract from the user what he really expects of a product. The proposed framework is based on the concepts of requirements categorization established by Noriaki Kano, and on previous studies focused on collective intelligence, to propose different approaches to extract from the crowd the necessary knowledge to classify requirements and decide what should be prioritized and what should not, according to user expectations.

Crowdsourcing for music: Survey and taxonomy

Recent behavioral and cultural changes driven by the paradigm of mass collaboration highlighted the phenomenon of crowdsourcing as an innovative and promising production model, with positive effects in several business areas. In the field of music, the so called wave of crowds has fostered creative processes where people from anywhere in the world with Internet access can collaborate in different ways in musical productions, even not being practitioners. The present work is a study of crowd computing applications in the context of music, with an eye towards the crowdsourcing phenomena. We investigate forms of collaboration involving crowds and the available platforms. We also discuss the challenges coupled to this domain and propose a research agenda.

CSCWD: Five characters in search of crowds

According to some researchers, the wave of crowds we are witnessing in recent years is another example of the challenges for the CSCW community, a line of research that fights against the dilemma of fragmentation. The reflexes of this phenomena in projects of different branches have caused a change of paradigm in how products and services are idealized and how the projects are conducted in a collaborative way. Successful examples have attracted the attention of entrepreneurs in various areas and increased the business vocabulary with terms like crowd wisdom, crowdsourcing, crowdfunding and open innovation. It is a different reality from the one we are used to in the context of groupware systems, and it brings new challenges that leave some relevant open research questions. This paper proposes a characterization of crowd computing systems, contextualizing the design activity within this domain, presents a research agenda in the context of CSCW and discusses possible implications of the mass phenomena on the line of action of the community of Computer Supported Cooperative Work in Design.

i-ProSE

Scientific environments are known for being highly dynamic, subject to rapid evolution and demanding constant renewal and update. Additionally, science is a highly social arena. However, interpersonal collaboration and knowledge flow in scientific environments are usually more restricted. Collaboration is intense among small groups of people working on specific problems within a domain, but low between groups. As user profiling has been extensively used as a basis for recommendation, personalization and matchmaking systems, a better profile identification can improve interaction levels among researchers belonging to the same domain but working in different laboratories. Profiles may be constructed in two ways: either through explicit declaration by the user or through the observation of users’ actions. Many systems employ one approach to the exclusion of the other. We contend that a combined approach will yield better results, especially on scientific scenario, providing a mix of declared and inferred information. In this article, we present inference-based profiles in scientific environments (i-ProSE), an integrated system that dynamically creates and maintains scientific user profiles based both on declared information and on observed behaviour. The i-ProSE can be used to locate experts, deliver content, build communities, find collaborators for long-term projects or detect instantaneous opportunities for informal collaboration, which is presented with a short study case.

COE: A collaborative ontology editor based on a peer-to-peer framework

In this paper, we present COE, a peer-to-peer collaborative ontology editor, which supports the creation, editing, sharing, and reuse of ontologies, implemented on top of a general-purpose peer-to-peer framework, COPPEER. In large multi-disciplinary design projects, ontologies can be a critical success factor. Their collaborative creation leads to better understanding and increased information sharing between participants of a project, and economy of resources among projects. A peer-to-peer approach enables new modes of collaboration, while simplifying maintenance by propagating individual updates in shared models.

Approximate Query Processing in Spatial Databases Using Raster Signatures

A main issue in database area is to process queries efficiently so that the user does not have to wait a long time to get an answer. However, there are many cases where it is not easy to accomplish this requirement. In addition, a fast answer could be more important for the user than receiving an accurate one. In other words, the precision of the query could be lessened, and an approximate answer could be returned, provided that it is much faster than the exact query processing and it has an acceptable accuracy.