The information environment is an aggregation of individuals, organizations, and systems that collect, process, disseminate, or act on information.
The information environment is made up of three interrelated dimensions:
The physical dimension is composed of the command and control systems, and supporting infrastructures that enable individuals and organizations to conduct operations across the air, land, sea, and space domains. It is also the dimension where physical platforms and the communications networks that connect them reside.
The informational dimension is where information is collected, processed, stored, disseminated displayed, and protected. Actions in this dimension affect the content and flow of information.
The cognitive dimension encompasses the mind of the decision maker and the target audience. This is the dimension in which people think, perceive, visualize, and decide. It refers to individuals' or groups' information processing, perception, judgment, and decision making. These elements are influenced by many factors, to include individual and cultural beliefs, norms, vulnerabilities, motivations, emotions, experiences, morals, education, mental health, identities, and ideologies. Defining the cognitive influencing factors in a given environment is critical for understanding how to best understand the mind of a given audience and create desired effects accordingly.
One of the more interesting aspects of information management is when placing the data in the context of organizational development. In this context, organizations are open systems that exist in and interact with the environment. ‘Smart’ organizations are distinguished by the ability to read the environment and to adapt accordingly – they are learning organizations, proficient at creating, acquiring, organizing, and using knowledge to develop desirable behaviours, improve competitive position, or achieve objectives.
The application of communication and information technologies to support work processes, including technology-enhanced communication networks, computer-supported collaborative work, decision-support systems, interactive systems, and systems analysis in an organisation could be extremely valuable in the process of organizational learning (sensing the environment, perceiving change, interpreting the significance of the change, and developing appropriate organizational strategies and responses) being perceived as a cycle of activities rather than a single event.
Community analytics and policy specialization focuses on the nature of developing local data infrastructures designed to promote civic engagement at the community level, and the roles that information technology and digitalized assets can play in supporting that engagement. It studies the nature of open data and information; the ability of the public to be informed about local issues through open government and data; the ways in which information professionals can serve as key community-based intermediaries between governments, the public, and local issues; the curation and management of digital assets, particularly datasets; the ability to create and foster data-driven communities of practice; and the role of the political process and information policy in shaping the development of community data.
LIBRe Foundation considers the implications of the widespread sharing and exploitation of publicly released datasets by governments on the freedom of information. While open data have the benefit of making governments’ activities ‘visible’ to the whole society, such datasets per se do not contribute to the freedom of information. Their technical complexity and the lack of sufficiently adequate digital skills in regular citizens to manipulate such datasets on their own, could be seen as an obstacle to their exercising of FOI rights. Our research aims to find a balanced approach whereby open data would contribute to the establishment of a culture of sharing ‘actionable’ information that could easily be translated into contextualized knowledge to the benefit of the society.
Social context information has been used with encouraging results in developing socially aware applications in different domains. However, users' social context information is distributed over the Internet and managed by many different proprietary applications, which is a challenge for application developers as they must collect information from different sources and wade through a lot of irrelevant information to obtain the social context information of interest. On the other hand, it is extremely hard for information owners to control how their information should be exposed to different users and applications. Combining the social context information from the diverse sources, incorporating richer semantics and preserving information owners' privacy could greatly assist the developers and as well as the information owners.
LIBRe Foundation focuses its research activities on the nature of information and the different information behaviour and mental models, searches for characteristics of problems, task analysis, problem solving, and decision making, and methods for determining information behaviour and user needs. We are interested in the process of acquisition of raw social data from multiple sources; creation of an ontology-based model for classifying, inferring and storing social context information, including social relationships and status; ways for information owners to control access to their information; etc.