Knowledge management and XML
Authors: Cannataro Mario , Guzzo Antonella , Pugliese Andrea 
Published: January 2007

One of the effects of the expansion of the World Wide Web is the
production of a huge amount of data, differentiated for type,
available to a large number of different users. Furthermore, the
constant progress of computer hardware technology in the past three
decades has led to the availability of powerful computers, data
collection equipments, and storage media; this technology provides
a great boost to the database and information industry by allowing
transaction management, information retrieval, and data analysis
over massive amounts of heterogeneous data. Moreover, the explosion
of Internet increases the availability of data in different
formats: structured (e.g. relational), semistructured (e.g. HTML,
XML) and unstructured (e.g. plain text, audio/video) data [2].
Thus, new data management systems, able to take advantage of these
heterogeneous data, are emerging and will play a vital role in the
information industry. Thus, heterogeneous database systems emerge
and play a vital role in the information industry.

Knowledge Management
is concerned with the technological,
economic and organizational aspects related to
(i)
the
creation, distribution, diversification and sharing of knowledge in
complex organizations and to
(ii)
the management of
informative flows, processes and interactions with external
Knowledge [8].

Figure 1 summarizes the steps (each represented on a different
level of the pyramid) through which knowledge is typically
extracted from basic data. The first three levels regard the
management of
explicit
knowledge (i.e. codified, structured
or semistructured and completely available). In particular,
starting from the bottom, the first level is concerned with storing
and exchanging "factual" knowledge, essentially corresponding to
basic data. Technologies used here comprise
Databases
[17],
Data Repositories, Archive Sharing
tools and the emerging
Extensible Markup Language (XML)
[18].

The second level regards "conceptual knowledge" modeling, i.e.
the definition of concepts and relationships among them. Such
knowledge is typically represented by means of diagram-based
formalisms for both information and related processes [9]. The
Unified Modeling Language (UML)
is currently one of the most
promising modeling languages, oriented towards the
specification,implementation and documentation of complex software
systems, but also used for modeling company processes not strictly
related to the software.

The third level is concerned with organization and integration
of information represented according to heterogeneous formalisms.
Techniques used here are essentially those concerning
Data
Warehousing (DW)
[10]. Data warehouses are integrated
repositories of data extracted from multiple heterogeneous sources,
organized under a unified schema and at a single site, in order to
facilitate management and decision making. Data Warehousing
technologies include data cleaning, data integration, and
Online
Analytical Processing (OLAP),
i.e. analysis techniques based on
aggregation and summarization.

The highest level regards
Knowledge Discovery,
i.e. the
uncovering of
new, implicit
and
potentially useful
knowledge from large amounts of data. The core phase of knowledge
discovery is
Data Mining
[10], an interactive, iterative,
multi-step process, comprising in particular pattern searching and
eventual refinements on the basis of domain experts' knowledge.

In the context of explicit knowledge management, the Extensible
Markup Language takes naturally place. XML is a language for
semistructured data [1, 5] of the
World Wide Web Consortium
(W3C)
[13] which is designed to allow marking, transferring and
reusing information by means of a standard method of definition of
the documents structure and format. Its metalanguage features have
been used in knowledge management typically for
(i)
the
semi-automatic production of documents,
(ii)
the reuse of
semistructured information and its integration in heterogeneous
systems,
(iii)
the creation of
knowledge maps
for the
organization and sharing of information.

The increasing quantity of available semistructured data and the
use of XML for their description and exchange discovers new
reaserch themes related to management and knowledge extraction over
XML data. In this scenario, our proposal consists of a system for
the
syntesization
of XML documents that attempts to extract
their semantics and to derive synthetic versions of them by means
of a
multidimensional interpretation
[10]. In the contest of
Knowledge Management, data synthesization can be regarded as a new
way for knowledge extraction, by discovering and aggregating
(useful) core information and by neglecting (useless) details.