International Conference on Knowledge Management and Information Sharing
Regular Paper Submission: April 17, 2012
Authors Notification (regular papers): June 12, 2012
Final Regular Paper Submission and Registration: July 4, 2012
From the call for papers:
Knowledge Management (KM) is a discipline concerned with the analysis and technical support of practices used in an organization to identify, create, represent, distribute and enable the adoption and leveraging of good practices embedded in collaborative settings and, in particular, in organizational processes. Effective knowledge management is an increasingly important source of competitive advantage, and a key to the success of contemporary organizations, bolstering the collective expertise of its employees and partners.
Information Sharing (IS) is a term used for a long time in the information technology (IT) lexicon, related to data exchange, communication protocols and technological infrastructures. Although standardization is indeed an essential element for sharing information, IS effectiveness requires going beyond the syntactic nature of IT and delve into the human functions involved in the semantic, pragmatic and social levels of organizational semiotics.
The two areas are intertwined as information sharing is the foundation for knowledge management.
Although all three conferences at IC3K 2012 will be of interest to topic mappers, the line:
Although standardization is indeed an essential element for sharing information, IS effectiveness requires going beyond the syntactic nature of IT and delve into the human functions involved in the semantic, pragmatic and social levels of organizational semiotics.
did catch my attention.
I am not sure that I would treat syntactic standardization as a prerequisite for sharing information. If anything, syntactic diversity increases more quickly than semantic diversity, as every project to address the latter starts by claiming a need to address the former.
Let’s start with extant syntaxes, whether COBOL, relational tables, topic maps, RDF, etc., and specify semantics that we wish to map between them. To see if there is any ROI. If not, stop there and select other data sets. If yes, then specify only so much in the way of syntax/semantics as results in ROI.
Don’t have to plan on integrating all the data from all federal agencies. Just don’t do anything inconsistent with that as a long term goal. Like failing to document why you arrived at particular mappings. (You will forget by tomorrow or the next day.)