\chapter{SEWASIE and MOMIS}
\label{c2bis:cap2bis}


\section{SEWASIE}
\label{s2bis:Sewasie}
\subsection{Overview} \textbf{SEWASIE}\footnote{http://www.sewasie.org/} stands for
``\textbf{SEmantic Webs and AgentS in Integrated Economies}''. It
is an European project inserted in the $5^{th}$ Framework IST
programme of the European Community within the Semantic Web Action
Line. The project is coordinated by Universit\`a degli studi di
Modena e Reggio Emilia (Italy), and the other partners are: CNA
SERVIZI Modena s.c.a.r.l. (Italy), Universit\`a di Roma ``La
Sapienza'' (Italy), Rheinisch Westfaelische Technische Hochschule
Aachen (Germany), The Victoria University of Manchester (UK),
Thinking Networks AG (Germany), IBM Italia SPA (Italy),
Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung
eingetragener Verein (Germany). It started in May 2002 and will
end in April 2005.\\


\textbf{SEWASIE} \emph{will design and implement an advanced
search engine enabling intelligent access to heterogeneous data
sources on the web via semantic enrichment to provide the basis of
structured secure web-based communication}.\\

The objectives are to develop a distributed agent-based
architecture of semantic search and communication using
community-specific multilingual ontologies; to equip ontologies
with an inference layer grounded in W3C standards; to develop
prototypes that meet the needs of SMEs in a EU context; to obtain
practical experience (user requirements, potential added value,
risks etc.). In particular the programme focuses on the question
how to assist networks of small and medium enterprises (so-called
Integrated Economies) in enhancing their intra-and
inter-organisational information management capabilities. The
project also includes novel techniques for semantic enrichment,
query management, and presentation techniques in multi-lingual
information acquisition from the web.


\subsection{The Business Scenario} Throughout Europe, much of the
industrial fabric is made of small and medium-sized agricultural,
manufacturing, commercial, and services firms (SMEs). For social
and historical reasons, they often aggregate into sectorial
clusters (that the economic literature names as industrial
districts); nowadays, this kind of economic organization is made
vulnerable by the globalisation and it will be more so in the
future.
\par In such a condition, to find (the adequate supplier, an
innovative working method, a new market, and so on) and to be
found (by possible customers, partners or sponsors) makes the
difference; the current Internet tools (e.g. search engines) are
inadequate since they are very difficult to use (small firms do
not necessarily have the required technological infrastructure and
know-how) and because a simple query produces pages and pages of
links, most of them worthless. Suppose that a firm needs to know
about a topic (a product, a supplier, a fashion trend, a norm, and
so on): generally they have to make several quests. For example,
if they look for a new ``fabric dyeing process'' they need to find
who produces it and if there exist specific norms about the
disposal of the dyeing waste material. First of all they have to
make a quest using the term ``fabric dyeing''. Clearly, the search
engine will list links (540 in the case of www.google.com)
concerning not only manufacturers of fabric dyeing equipment, but
also the history of dyeing, the dyeing technology, and so on.
After having located a possible supplier, the company must find
relevant laws and norms about waste disposal and their related
interpretations. The search criteria can be, for example, the
number of the law, the term ``law'', the interpretation etc. Both
searches become more difficult when searching abroad, since there
can exist a specific terminology that the user might not be
familiar with.
\par Suppose instead that the user is a business
professional, and (s)he is interested only in the normative part.
In this case (s)he needs to retrieve rapidly not only the relevant
laws, but also references, connected issues and so on; all this by
searching both on free and subscribed web sites.
\par For this reason, users need to have at their disposal an
engine equipped with an easy-to-use query interface able to
extract the required information from the Internet and to show it
in an easily enjoyable format. If a step-by-step approach is
allowed, the following deductive reasoning steps are easy as well.
Easy-to-use means ``usable by lay users and by means of poor
infrastructures''.
\par The main requirement is to get structured
results obtained from an interpretation of vague queries followed
by some filtering techniques based on designer rules and the
acquired experiences. For instance, starting from a request simply
constituted by the keyword ``punch'' the engine should answer with
one or more documents containing information in an
easy-to-accessible format such as sellers, prices, manufacturers,
technical literature on its use, importer and so on. Particularly
interesting for products and manufactures is also to know if some
stock goods at low price exist or if there are any auctions or
other negotiation mechanisms for the construction or the purchase
(from e-procurement sites).


\subsection{The SEWASIE Idea} \emph{The goal of the SEmantic Webs and
AgentS in Integrated Economies project is the design and the
implementation of an advanced search engine allowing information
access via a machine-processable semantics of data in order to
provide the basis of structured web-based communication}.\\

Tools and methods will be developed to create/maintain
multilingual ontologies, with an inference layer grounded in W3C
standards (XML, XML Schema, RDF(S)), that are the basis for the
advanced search mechanisms and that provide the terminology for
the structured communication exchanges. Search results will be
personalised and visualised according to users' preferences.\\

\emph{SEWASIE will provide an open and distributed architecture
based on mobile, intelligent agents} (brokers, mediators and
wrappers) facing scalability and flexibility issues, i.e. the
ability to fit in changing and growing environments and to
interoperate with other systems, while offering one central point
of access to the user. \\

\emph{The user will be supported in querying heterogeneous web
information sources}. The user query will be sent to a \emph{query
agent} that processes and answers the query moving through the
SEWASIE information nodes in order to retrieve the information
requested by the user (see \mbox{figure \ref{SVN}}).\\

\emph{Information nodes are independent components that
semantically enrich existing data sources by linking the data to
ontologies and other metadata}. The \mbox{SEWASIE} project will
also allow for a real life business evaluation of the results,
striving to develop a system and tools which will not only solve
the problem, but do so in a usable, marketable way.
\begin{figure}[ht]
  \begin{center}
    %\epsfig{figure=sewasiearc.eps,width=12cm,angle=0}
    \epsfig{figure=SEWASIE.eps,width=12cm,angle=0}
    \caption{The SEWASIE Virtual Network}\label{SVN}
  \end{center}
\end{figure}
\par In particular, the SEWASIE project will pursue the following
aims:
\begin{itemize}
    \item To develop an agent-based secure, scalable and distributed
system architecture for semantic search (ontology based) and for
structured web-based communication (for electronic negotiation).
    \item To develop a general framework responsible for the implementation
of the semantic enrichment processes leading to the semantically
enriched virtual data stores, which constitute the information
nodes accessible by the users. The created ontology will be
multilingual accessible, founded on a logical layer and coded
using widespread W3C standards.
    \item To develop a general framework for query management and
information reconciliation taking into account the semantically
enriched data stores. In particular, first commonalities among
queries will be detected, then the relevant virtual data stores
responsible for answering parts of the queries determined and the
queries accordingly splitted, finally the sub-answers will be
combined together in order to provide the user with an overall
answer to the original query.
    \item To develop an information brokering component which will include
methods for collecting, contextualising and visualising
semantically rich data. To obtain this result, intelligent
information filtering and knowledge guidance services will be
developed on the basis of semantic web technologies; structured
data will be linked to semi- or unstructured data via ontologies;
for financial controlling applications collected data will be
visualised to show related documents and search result contexts.
    \item To develop structured communication processes that enable the use
of ontologies. The communication tool will enable structured
negotiation support for human negotiators engaging in
business-to-business electronic commerce and employing intelligent
software agents for some routine communication task.
    \item To develop end-user interfaces for both the semantic design and
the query management. The first is a tool supporting the design,
the management, and the storage of the semantic information
associated to virtual data stores together with a conceptual
modelling methodology associated to the devised data model. The
latter is a tool for end-user query management and intelligent
navigation exploiting the semantic information associated to
virtual data stores and to the global virtual view.
\end{itemize}
Another important aim of the project is to assess the economic and
organisational impact of a semantically rich web of information on
SME industrial systems. In particular the potential economic
benefits expected by the \mbox{SEWASIE} system and the internal
and external factors needed to achieve such benefits will be
analyzed, taking care to study the business and organisational
changes requested to the firms by the new tool. Since different
firms exhibit different features concerning the required type of
information, available information sources, own skills,
manufacturing technologies and so on, \mbox{SEWASIE} has selected
to conduct the business user requirement analysis and test in two
very distinct sectors, namely the industrial moulding sector and
the textile and clothing.

\section{MOMIS}
\label{s2bis:Momis}

\subsection{Overview}
In the last years the need to have access to distributed
information and the problem of data integration coming from
heterogeneous sources have become more and more important.
Companies have equipped themselves with data storing systems
building up informative systems containing data which are related
one another, but which are often redundant, heterogeneous and not
always substantial. On the other hand, the web explosion, both at
internet and intranet level, has enlarged the need for the sharing
and retrieving of information located in different sources, thus
obtaining an integrated view so as to eliminate any contradiction
or redundancy. The problems that have to be faced in this field
are mainly due both to structural and application heterogeneity,
as well as to the lack of a common ontology, causing semantic
differences between information sources. Moreover these semantic
differences can cause different kinds of conflicts, ranging from
simple contradictions in names' use (when different names are used
by different sources to indicate the same concept), to structural
conflicts (when different models/primitives are used to represent
the same information). The integration problem is relevant also in
the E-Commerce environment. Electronic catalogs are a key
component of E-Commerce and they can be organized as individual
company catalogs or they can participate in a multicatalog
framework. In the second case, from a user point of view, it is
very important to have a uniform interface to search products,
that is a uniform view of data coming from different companies
catalogs and a unique query language. On the other hand, from a
company point of view it is important to guarantee both the
uniqueness of their catalogs and the participation in a
multi-catalog framework. Virtual Catalogs synthesize this approach
as they are conceived as instruments to dynamically retrieve
information from multiple catalogs and present product data in a
unified manner, without directly storing product data from
catalogs. Instead of having to interact with multiple
heterogeneous catalogs, customers can interact in a uniform way
with a virtual catalog.

%[SI-Designer: a tool for intelligent integration of information.
%hicss2001.pdf]

In this context the problem to face is the identification of
semantically related information, that is, information describing
the same real-world concepts in different sources having semantic
heterogeneity. In fact, information sources to be integrated are
usually preexisting and have been developed independently.
Consequently, semantic heterogeneity can arise for the aspects
related to terminology, structure, and context of the information,
and has to be properly dealt with during integration in order to
effectively and correctly exploit the information available at the
sources.

\textbf{MOMIS}\footnote{http://www.dbgroup.unimo.it/Momis/} stands
for ``\textbf{M}ediator envir\textbf{O}nment for \textbf{M}ultiple
\textbf{I}nformation \textbf{S}ources''. \mbox{MOMIS}
\cite{sigmod99,bergamaschi:vldb2000,dke99,IEEE2002} is a
mediator-based system for information extraction and integration
that works with structured and semistructured data sources.
\mbox{MOMIS} was developed as a joint collaboration among the
University of Modena and Reggio Emilia, the University of Milano
and the University of Brescia, within the INTERDATA national
research project, under the direction of Professor S. Bergamaschi.
Now the research activity continues within the \emph{D2I:
Integration, Warehousing, and Mining of Heterogeneous Data
Sources} national research project.

% Corni P.h.D. Thesis

\subsection{The Momis approach}
MOMIS \cite{bergamaschi:vldb2000,dke99,IEEE2002} follows a
``semantic approach'' to information integration based on the
conceptual schema (or metadata), of the information sources. In
the MOMIS system, each data source provides a schema and a global
virtual schema of all the sources is semi-automatically obtained.
The global schema has a set of mapping descriptions that specify
the semantic mapping between the global schema and the sources
schema.

The system architecture is composed of functional elements that
communicate using the CORBA standard. A data model, \langM, and a
language, \lang are used to describe information sources. \lang
and \langM have been defined as subset of the corresponding ones
in ODMG, augmented by primitives to perform integration. To
interact with a specific local source, MOMIS uses a Wrapper, which
has to be placed over each source. The wrapper translates metadata
descriptions of a source into the common \lang representation. The
Global Schema Builder (GSB) module (see Figure \ref{MPA})
processes and integrates descriptions received from wrappers to
derive the global shared schema by interacting with different
service modules: \textbf{ODB-Tools}, an integrated environment for
reasoning on object oriented database that relies on Description
Logics \cite{aiia97}; \textbf{WordNet} \cite{wordnet2}lexical
database that supports the mediator in building lexicon-derived
relationships; and \textbf{ARTEMIS} tool that performs the
clustering operation \cite{artemis}.

\subsection{The architecture}
The MOMIS system is designed for schema integration. \mbox{Figure
\ref{MPA}} shows the architecture of the system in terms of
functional modules. The system is composed of several objects that
communicate using the CORBA\footnote{Object Management Group.
http://www.omg.org/} standard and it follows the \iii architecture
\cite{ARPA}.
\begin{figure}[t]
  \begin{center}
    %\epsfig{figure=momisarchitecture2.eps,width=12cm,angle=0}
    \epsfig{figure=MOMIS.eps,width=12cm,angle=0}
    \caption{MOMIS prototype architecture}\label{MPA}
  \end{center}
\end{figure}
The modules are on three levels:
\begin{description}
    \item[Data Level.] Here there are the \textbf{Wrappers}. They
are placed over each source and represent the interface
modules between the mediator and the local data sources. They
carry out a double function: in the integration phase, they
translate the description of the information held in the source.
This description is supplied through the \lang{} language; in the
query processing phase, they translate the query which has been
received by the mediator (expressed in the common query \langQ{}
language, derived by the OQL language) in a query expressed in the
source query language. The wrappers must also export query result
data, providing them to the mediator through the data common model
used by the system.
    \item[Mediator Level.] The mediator is the core module of the
system. It allows to create an homogeneous representation of the
information and an integrated access to the sources. It's composed
of two distinct modules:
    \begin{itemize}
        \item \emph{The Global Schema Builder} (GSB): its goal is to lead
        the designer from the schemata acquisition of sources to the
        tuning of the mapping table through the various steps of the
        integration. This module interacts with \mbox{ODB-Tools}
        (a framework for object-oriented database schema validation,
        preserving taxonomy coherence and performing taxonomic
        inference, and semantic query optimization) and with the
        lexical database WordNet to extract lexicon derived
        intensional relationships between attributes and
        classes.\\\textbf{SI-Designer} is the GUI (Graphic User Interface)
        for the Global Schema Builder.
        \item \emph{The Query Manager} (QM): it is the module that performs
        query processing and optimization. The QM generates \langQ
        queries to be sent to wrappers starting from each query
        posed by the user on the Global Schema. It automatically
        generates the translation of the query into a corresponding
        set of sub-queries for the sources and synthesizes a
        unified global answer for the user.
    \end{itemize}
    \item[User Level.] The designer interacts with the Global
    Schema Builder and builds the integrated view of the sources.
    The users pose the queries on the Global Schema then the QM
    performs the queries on the local sources and presents the
    users with an unified answer.
\end{description}

The MOMIS project aims at integrating data from structured and
semi-structured data sources. SI-Designer is a support tool for
semi-automatic integration of heterogeneous sources schema
(relational, object, XML and semistructured sources). It carries
out integration following a semantic approach which uses
intelligent OLCD Description logic-based techniques, clustering
techniques and an ODM-ODMG extended model

The MOMIS approach to perform Global Virtual View is articulated
in the following phases:
\begin{enumerate}
    \item \emph{Generation of a Common Thesaurus.} \\The Common
    Thesaurus is a set of terminological intensional and extensional
    relationships, describing intra and inter-schema knowledge about
    classes and attributes of sources schemas. We express intra and
    inter-schema knowledge in form of terminological and extensional
    relationships (\emph{synonymy, hypernymy and relationship})
    between classes and/or attribute names. In this phase the WordNet
    database is used to extract lexicon derived relationships.
    \item \emph{Affinity analysis of classes.} \\Relationships in
    the \emph{Common Thesaurus} are used to evaluate the level of
    \emph{affinity} between classes intra and inter sources. The concept
    of affinity is introduced to formalize the kind of relationships
    that can occur between classes from the integration point of view.
    The affinity of two classes is established by means of affinity
    coefficients based on class names, class structures and relationships
    in the \emph{Common Thesaurus}.
    \item \emph{Clustering classes.} \\Classes with affinity in different
    sources are grouped together in clusters using hierarchical clustering
    techniques. The goal is to identify the classes that have to be
    integrated because describing the same or semantically related information.
    \item \emph{Generation of the mediated schema.}\\Unification of affinity
    clusters leads to the construction of the predicted schema. A
    class is defined for each cluster, which is representative of all
    clusters' classes and is characterized by the union of their
    attributes. The global schema for the analyzed sources is composed
    of all classes derived from clusters, and is the basis for posing
    queries against the sources.
\end{enumerate}

A graphical tool, the Source Integration Designer, SI-Designer,
has been developed to support the designer during the source
integration phase. More details about SI-Designer will be
presented in section \ref{s3:SI-Designer}.


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