Special Issue MEDES 2009 on Collective Information and Knowledge Management: Guest Editorial Note

Epaminondas Kapetanios

University of Westminster,

School of Electronics and Computer Science,

London, United Kingdom

National Insitute of Informatics

Tokyo, Japan

 

Richard Chbeir

Bourgogne University, LE2I CNRS

Computer Science Department

Dijon, France

 

 In order to adhere to the evolutionary and cultural impact of computer science in society and organizations, we need to re-visit memory and organizational models within a universe of discourse where entity participation and connectionism are of paramount importance. Data, information and knowledge management principles and techniques need to be conceived as contributing to the creation of a huge associative memory, which could enable a collectively, eventually truly, intelligent society and organization. Within such a Collective Intelligence (CI) Universe of Discourse, coping with and harnessing complexity and diversity remains a key challenge, which can be met by conceiving data and knowledge engineering and management as an ecosystem underlying synergy and natural selection processes.

 

In this special issue, we solicited five visionary as well as theoretical and application papers among the best papers submitted and presented to the international conference on Emergent Digital Ecosystems 2009 (MEDES’09). All five papers have been extended of 30% of additional materials and rigorously reviewed by a dedicated peer review. The solicited papers address data and knowledge engineering principles and techniques in a CI Universe of Discourse. Particular emphasis has been given to principles and techniques underpinning all processes from ergonomy, conceptualization and conceptual modeling to querying, retrieval and storage of data and knowledge as integral parts of a larger associative memory. The special issue is organized as follows.

 

The first paper entitled The Computing of Digital Ecosystems, authored by Gerard Briscoe and Philippe de Wilde, discusses the fundamental properties of self-organization, scalability and sustainability, which are of paramount importance for harnessing complexity in large scale systems, in open social-technical system by using the metaphor of a Digital Ecosystem, inspired by natural ecosystems. The paper, however, gives a critical overview of digital counterparts for the behavior and constructs of biological ecosystems, instead of simulating or emulating such behavior or constructs. It also considers what parallels can be drawn. For instance, Multi-Agent Systems are discussed in order to explore the references to agents and migration. This is followed by evolutionary computing and Service Oriented Architectures for the references to evolution and self-organization in computing and computational environments rather than natural and environmental ones.

 

Having discussed the digital counterparts of self-organization, sustainability and scalability as desirable properties of an ecosystem, the second paper entitled An Autonomous Agent Approach to Query Optimization in Stream Grids, authored by Saikat Mukherjee, Srinath Srinivasa and Krithi Ramamritha, discusses optimization of queries where nodes in a grid act as local agents trying to optimize stream grid queries based on their local interests. In such an ecosystem, it becomes apparent that there cannot be any global optimization strategy, but one emerging out of local optima and choices among alternative strategies. Stream grids are grid computing environments that are fed with streaming data sources from instrumentation devices like cameras, RFID (radio-frequency identification) sensors, network monitoring or other applications. Queries by users or applications seek to tap into one or more such streams. The main costs for such queries include bandwidth costs and bookkeeping costs at each grid node. In such scenarios, there are conflicting optimization requirements.

 

In the context of Peer-to-Peer (P2P) system architectures, the third paper entitled Managing Collective Intelligence in Semantic Communities of Interest (CoIs), authored by Stefano Montanelli, Silvana Castano, Alfio Ferrara, and Gaia Varese, discusses how queries can be supported and once Semantic CoIs as a form of community level CI have been established.  The discussed approach departs from traditional P2P approaches in that there is a shift from a network of units to a network of coalitions where the community itself (and not the peers on their own) has the role to support effective query execution and data availability. The paper also discusses creation and maintenance of a community-level collective intelligence in order to push a novel attention to the critical aspects of distributed knowledge management in the P2P environment, where the goal of establishing a shared agreement among a set of peers conflicts with the intrinsic P2P nature that pursues peer autonomy, communication scalability, and rapid change propagation.

 

The discussion of how to improve information management and querying is taken further in a collective setting of multimedia sensor networks, where handling of voluminous amount of multimedia sensor data is of paramount importance. The fourth paper A 3D Real-Time Reconstruction Approach for Multimedia Sensor Networks, authored by Ahmed Mostefaoui and Benoit Piranda, discusses a new approach to handle the huge and voluminous data generated by an ecosystem of multimedia sensors in a video surveillance context (e.g., super market environment). The key idea behind the authors' proposition is to “continuously” construct a 3D representation of the monitored area, in which video streams originating from the video sensors are fused. In other words, the “views” of the sensor nodes are merged in the 3D scene of the monitored region. This approach presents many interesting advantages, in particular for resources limited environments like those of sensor networks. Another advantage of the proposed approach is its ability to answer some spatio-temporal requests that are very hard to handle with raw video data.

 

Finally, the fifth paper entitled An Experimental Performance Comparison for Indexing Mobile Objects on the Plane, authored by S. Sioutas, G. Papaloukopoulos, K. Tsichlas and Y. Manolopoulos, discusses some of the challenges and problems for indexing and querying objects on the move with particular interest on predictively querying their future position. In an ecosystem of data, information and knowledge where data or queries are being migrated or moved across networks of communication for the sake of query optimization and effectiveness of information provision, new indexing and querying techniques are requested.

 

As a closing remark, we would like to warmly thank all the authors and the reviewers for their continuous effort to make this special issue happen. We also express our warmest thanks to the editor-in-chief and the publisher for accommodating this special issue in this Journal.