Experiments were conducted by submitting queries
of five different types (Q1-Q5). Table 1 presents the
features of the test queries and the query execution
time for both the “stratum” and the “native” archi-
tectures. All the queries require structural support
(St constraint); types Q1 and Q2 also involve tex-
tual searches by keywords (Tx constraint), with dif-
ferent selectivities; type Q3 contains temporal condi-
tions (Tm constraint) on three time dimensions: trans-
action, valid and publication time; types Q4 and Q5
mix the previous ones since they contain both key-
word searches and temporal conditions. For each of
those query types, we also present a personalized ac-
cess variant involving an additional applicability con-
straint (denoted as Qx-A in Table 1).
Let us first focus on the upper part of the table,
and in particular on the comparison of the perfor-
mances offered by the two approaches. The native
approach shows to be faster in every context, provid-
ing a shorter response time (including query analysis,
retrieval of the qualifying norm parts and reconstruc-
tion of the result) of approximately one or two sec-
onds for most of the queries. Notice that, while the
response time of the stratum approach is not too dif-
ferent for query types Q1, Q4, Q5, for the other query
types the performance gap is quite important (for in-
stance, query Q2 is answered approximately 15 times
slower in the stratum approach). The reason is that
the selectivity of the query predicates strongly influ-
ences the performance of the stratum approach, seri-
ously impairing its performance when large amounts
of documents containing some (typically small) rele-
vant portions have to be retrieved, as it happens for
queries Q2 and Q3. On the other hand, the native
approach is able to deliver a faster and more reliable
performance in all cases, since it practically avoids
the retrieval of useless document parts. Further, con-
sider that, for the same reasons, the main memory
requirements of the Temporal XML Query Processor
embedded in the native approach are, on average, 5%
or less of the stratum approach. This property is also
very promising towards future extensions to cope with
concurrent multi-user query processing.
The lower part of the table presents the perfor-
mance of our second system with respect to the
queries involving additional applicability constraints,
enabling personalized access. Thanks to the proper-
ties of the adopted pre-order and post-order encoding
of the civic classes, the system is able to solve person-
alization problems by means of simple comparisons
involving such encodings and, thus, with a very high
efficiency. The time needed to answer the personal-
ized access versions of the Q1–Q5 queries is approx-
imately 0.5-1% more than for the original versions.
Moreover, since the applicability annotations of each
part of an XML document are stored as simple inte-
gers, also the size of the applicability annotated tu-
ples, as stored in the system, is practically unchanged
(only a 3-4% storage space overhead is required with
respect to documents without semantic versioning),
even with quite complex annotations involving sev-
eral applicability extensions and restrictions.
Finally, we only report a comment about the perfor-
mance of our current prototype in querying the other
two collections C2 and C3 and, therefore, concern-
ing the the scalability of the system. We ran the same
queries of the previous tests on the larger collections
and saw that the computing time always grew sub-
linearly with the number of documents. For instance,
query Q1 executed on the 10,000 documents of col-
lection C2 (which is as double as C1) took 1,366 msec
(i.e. the system was only 30% slower); similarly, on
the 20,000 documents of collection C3, the average
response time was 1,741 msec (i.e. the system was
less than 30% slower than with C2). Also with the
other queries the measured trend was the same, thus
showing the good scalability of the system in every
type of query context.
5 FUTURE DEVELOPMENTS
Our current research work is devoted to the extensions
of the current framework and to the development of
a complete technological infrastructure to enable our
approach to be self-contained and usable in a large
Web-based e-Government scenario, as envisioned in
(Grandi et al., 2004).
The adoption of a tree-like civic ontology –
that is based on a taxonomy induced by the IS-A
relationship– is sufficient to satisfy basic application
requirements as far as applicability constraints and
personalization services are concerned. However,
more advanced application requirements may include
a more sophisticated ontology definition. As a mat-
ter of fact, real-world norm corpora, if analyzed in
full detail, can lead to the formalization of complex
relationships between civic subclasses giving rise to
ontologies structured, in general, as a graph. Hence,
extensions to the framework are required in order to
overcome the limitations of dealing with a tree-like
civic ontology in our current approach: the XML stor-
age organization and the query processing algorithm
must be revisited, since the solutions adopted so far
rely both on the ontology and document tree structure
(e.g. decomposition in temporal tuples and exploita-
tion of pre- and post-order numbering).
On the other hand, the development of a com-
plete infrastructure is needed to make our approach
self-contained and fully operational in a real-world e-
Government environment. In fact, in addition to the
availability on the Web of the query answering sys-
tem and of the civic ontology, several other compo-
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