--- /dev/null
+\documentclass[10pt]{article}
+
+% \usepackage{fguidi}
+\addtolength{\textheight}{2.5cm}
+\addtolength{\oddsidemargin}{-1.0cm}
+\addtolength{\evensidemargin}{-1.0cm}
+\addtolength{\textwidth}{2.0cm}
+\addtolength{\topmargin}{-1.0cm}
+
+\newcommand{\MathQL}{\textsc{mathql-1}}
+\newcommand{\RDF}{\textsc{rdf}}
+\newcommand{\RDFS}{\textsc{rdf schema}}
+\newcommand{\HELM}{\textsc{helm}}
+\newcommand{\POSIX}{\textsc{posix}}
+\newcommand{\XML}{\textsc{xml}}
+\newcommand{\CAML}{\textsc{caml}}
+\newcommand{\SQL}{\textsc{sql}}
+\newcommand{\PostgreSQL}{\textsc{postgresql}}
+\newcommand{\Galax}{\textsc{galax}}
+\newcommand{\XQuery}{\textsc{xquery}}
+
+\title{MathQL-1.4}
+\author{Ferruccio Guidi}
+
+\begin{document}
+
+\maketitle
+
+\section{Overview}
+
+{\MathQL} is a query language for {\RDF} databases, developed in the context
+of the {\HELM} project. Its name suggests that it is supposed to be the first
+of a group of query languages for retrieving information from distributed
+digital libraries of formal mathematical knowledge, but no other languages of
+this group have been implemented yet except for {\MathQL} that is not
+Mathematics-oriented. So the name is a bit misleading.
+
+{\MathQL} is carefully designed for having the following features:
+
+\begin{enumerate}
+
+\item
+compliance with the main requirements stated by the {\RDF} community;
+
+\item
+native support for post-processing the query results;
+
+\item
+{\HELM}-independent implementation of the query engine.
+
+\end{enumerate}
+
+We will briefly analyze these features in the remaining part of this section.
+
+\subsubsection*{The main requirements from the RDF community}
+
+As a query language for {\RDF} databases, {\MathQL} has a well-conceived
+semantics, defined in term of an abstract metadata model, according to which
+queries return exhaustive solutions.
+The language provides facilities for imposing query constraints based on
+{\RDFS} and for the traversal of compound values of properties.
+It also provides a full set of Boolean operators to compose the query
+constraints and facilities for selecting resources or literals by means of
+{\POSIX} regular expressions.
+Moreover the language allows to customize the query results specifying what
+part of a solution should be preserved, and supports a machine-processable
+{\XML} syntax as well as a human-readable textual syntax to achieve the best
+usability.
+
+The two syntaxes concern both queries and results, making {\MathQL} usable in
+a distributed environment where query engines are implemented as stand-alone
+components. This is because in this setting both queries and query results
+must be exchanged by the system's components and thus need to be encoded in
+clearly defined format.
+
+{\MathQL} provides a graph-oriented access to the {\RDF} metadata, based on
+tree instantiation.
+This approach has the advantage of providing an abstraction over the
+concrete representation of the {\RDF} database (that can consist of {\RDF}
+triples and {\XML} files simultaneously) at the user level, and this is
+definitely desirable especially in a distributed context.
+
+{\MathQL} query results are meant to capture the structure of trees coming
+from an {\RDF} graph and for this purpose a standard $1$- or $2$-dimensional
+organization (as provided by most {\RDF}-oriented query languages) is not
+satisfactory. Here {\MathQL} approach is to use a $4$-dimensional organization
+for its query results.
+
+\subsubsection*{Post-processing and code generation capabilities}
+
+The {\MathQL} query engine, that is written in {\CAML} for an easy integration
+with the {\HELM} software, provides two ways of processing the query results:
+at {\CAML} side and natively.
+
+At {\CAML} side, an application issues a query calling a function of the
+engine and manipulates the result either operating directly on its internal
+representation (that is placed in the public scope), or using a set of
+dedicated functions specifically designed to manage the query results.
+This set of functions includes a basic library but is extensible depending
+on the {\CAML} modules included in the engine at compile-time. In this way
+an expert user can write a {\CAML} module with new dedicated functions and can
+include it in the engine recompiling it.
+
+{\MathQL} supports native post-processing of the query results including the
+standard constructions of an imperative Turing-complete programming language,
+whose aim is definitely not that of being all-purpose (the user can work at
+{\CAML} side for that), but of being optimized for the management of the
+query results.
+In this context an {\SQL}-like ``select-from-where'' construction is provided
+(as required by the {\RDF} community) as well as a mechanism for accessing the
+post-processing dedicated functions available to the engine.
+
+Moreover the language provides access to an extensible set of code-generating
+functions (also available at {\CAML} side) that the expert user can define
+writing suitable {\CAML} modules for the engine.
+Note that the generated code is always {\MathQL} code.
+
+The code generation features allow to build complex queries incrementally and
+in an automatic manner, as required by the needs of the {\HELM} project.
+Using the native programming language, instead, queries can include the
+post-processing algorithms on their results so the querying code and the
+subsequent processing code (if needed) are treated together as a
+self-contained object that can be computed by a single engine.
+In this sense the alternative of performing a complex query on a remote
+component issuing some {\MathQL} querying code followed by some {\CAML}
+post-processing code is really infeasible in a distributed context.
+
+\subsubsection*{Physical organization of the RDF database}
+
+The implementation of the {\MathQL} query engine does not depend on any
+software developed within the {\HELM} project, nor it depends on the {\HELM}
+metadata model in any way.
+
+However the engine does make few assumptions on the way metadata are
+physically organized and needs some user-provided knowledge about the concrete
+metadata representation.
+Metadata stored as {\RDF} triples are accessed through a {\PostgreSQL} engine,
+while metadata stored as {\RDF}/{\XML} files are accessed through a {\Galax}
+{\XQuery} engine.
+
+\end{document}
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