Fruitful Synergies between Computer Science, Historical Studies and
Archives: The Experience in the PRiSMHA Project
Annamaria Goy
1
, Cristina Accornero
2
, Dunia Astrologo
3
, Davide Colla
1
, Matteo D’Ambrosio
3
,
Rossana Damiano
1
, Marco Leontino
1
, Antonio Lieto
1
, Fabrizio Loreto
2
, Diego Magro
1
,
Enrico Mensa
1
, Alice Montanaro
1,3
, Valeria Mosca
3
, Stefano Musso
2
, Daniele P. Radicioni
1
and Cristina Re
1,3
1
Dipartimento di Informatica, Università di Torino, Torino, Italy
2
Dipartimento di Studi Storici, Università di Torino, Torino, Italy
3
Fondazione Istituto Piemontese Antonio Gramsci, Torino, Italy
{annamaria.goy, davide.colla, rossana.damiano, antonio.lieto, fabrizio.loreto, diego.magro, enrico.mensa, stefano.musso,
Keywords: Intelligent Information Systems, Semantic Web, Multidisciplinary Approach, Digital Humanities, Historical
Archives.
Abstract: In this paper we present the mid-term results of the PRiSMHA project, aimed to contribute in building a
digital “smart archivist”, i.e., a web-based system providing an innovative access to historical archives. Such
a system is endowed with a semantic layer over existing archival metadata, including computational
ontologies and a knowledge base, containing a formal description of the content of the documents stored in
the archives. The paper focuses on the fruitful synergies employed to reach its goal. In particular, it explains
the steps of the “spiral” process implemented for creating a full-fledged formal semantic model, through the
interaction between computer scientists, historians, and archivists. The paper also presents some “core side-
effects” of this process: an analytical card for each document has been produced, all selected documents have
been digitized, OCR-ized (when possible), and linked to a record on the archival platform. This experience
enabled us to define a virtuous procedural model, from the paper documents up to the digital “smart archivist”,
based on a close collaboration between universities and cultural and historical institutions.
1 INTRODUCTION
In this paper we present the mid-term results of
PRiSMHA (Providing Rich Semantic Metadata for
Historical Archives), a three-year national project
(2017-2020), funded by Compagnia di San Paolo and
Università di Torino (Goy et al., 2017). PRiSMHA
(di.unito.it/prismha) involves the Computer Science
and the Historical Studies Departments of the
University of Torino (Italy), and relies on a close
collaboration with the Polo del '900
(www.polodel900.it), a cultural center in Torino, co-
funded by Compagnia di San Paolo, Comune di
Torino and Regione Piemonte. It involves nineteen
institutions and hosts a very rich set of archives, a
quarter of which is provided by the Fondazione
Istituto Piemontese Antonio Gramsci
(www.gramscitorino.it). The Polo del '900 archives
can be accessed through the online platform 9centRo
(www.polodel900.it/9centro).
In the following, we start by presenting the overall
framework in which PRiSMHA takes part (Section
2). Then we describe PRiSMHA's specific role and its
main results at the mid-term milestone, by focusing
on the fruitful synergies between different
perspectives: historical studies and computer science,
research institutions and cultural centers, automatic
and user-driven data production (Section 3). We
conclude the paper by indicating some future research
directions (Section 4).
2 THE FRAMEWORK
The overall goal is to build a digital “smart archivist”,
i.e., a web-based system providing an intelligent
access to historical archives.
Goy, A., Accornero, C., Astrologo, D., Colla, D., D’Ambrosio, M., Damiano, R., Leontino, M., Lieto, A., Loreto, F., Magro, D., Mensa, E., Montanaro, A., Mosca, V., Musso, S., Radicioni, D. and
Re, C.
Fruitful Synergies between Computer Science, Historical Studies and Archives: The Experience in the PRiSMHA Project.
DOI: 10.5220/0008343802250230
In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019), pages 225-230
ISBN: 978-989-758-382-7
Copyright
c
 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
225

Let us consider the case of a young researcher
looking for primary sources (leaflets, pictures, letters,
etc.) that report or comment on violent actions
performed by the police against students and workers
during the social protest in 1968. A digital “smart
archivist” would provide all documents somehow
referring to such kind of actions, independently from
the words actually used to report them in the primary
sources.
In order to reach such a result, a simple keyword
or tag-based search is not enough. As the long
tradition of studies in Knowledge Representation and
Reasoning  in the field of Artificial Intelligence 
tells us, in order to be “intelligent”, the system must
“know” the documents and grasp their content.
Therefore, the goal is providing the system with
further machine readable knowledge than that
actually represented by words occurring in the
documents or in their textual metadata. Technically,
this means building a semantic layer over existing
archival metadata, including:
 Computational ontologies (Guarino et al., 2009)
representing the semantic “vocabulary” (Goy et
al., 2015);
 A knowledge base containing a detailed formal
description of: the events narrated in the
documents, the places where they happened,
people, organizations, and collectives involved in
them, together with the role they played.
In order to guarantee the needed computational
interoperability, the standards of the Semantic Web
must be employed: OWL 2 (Hitzler et al., 2012) for
the computational ontologies and RDF (Hayes and
Patel-Schneider, 2014) and the Linked Data
principles (Heath and Bizer, 2011) for the knowledge
base.
However, providing a system with a so deep and
complex knowledge is a well-known bottleneck for
knowledge-based systems (especially as regards as
the knowledge acquisition step), that can threaten the
sustainability of the approach. One main goal of
PRiSMHA is to provide a solution to solve this
problem.
3 PRiSMHA: FRUITFUL
SYNERGIES
The solution can be found by looking in two
directions:
 Crowdsourcing collaborative approaches, if a
digital version of the archival resources is
available (Ashenfelder, 2015) (Beaudoin, 2015)
(MicroPasts, 2018).
 Automatic Information Extraction techniques,
when full texts are available (Boschetti et al.,
2014). Note that automatic extraction techniques
from documents other than texts (images, videos,
audio recordings) are currently out of the scope of
the project.
Thus, the specific goal of PRiSMHA is to
verify/demonstrate the feasibility of a solution based
on the integration of these two approaches.
3.1 Building the Ontology
PRiSMHA relies on two modular ontologies: a
top/core ontology called HERO Historical Event
Representation Ontology), and a domain ontology,
called HERO-900. Overall, the OWL2 version of
HERO+HERO-900 counts more than 400 classes and
more than 350 properties; moreover, it is a strongly
axiomatized ontology (more than 4.000 logical
axioms).
We started from the definition of HERO,
representing the semantically rich common
vocabulary. “Common” means shared between:
 The system, the users of the crowdsourcing
platform, and final users querying the digital
“smart archivist”;
 Computer scientists and ontologists actually
designing and implementing the system, and
historians providing a historical, analytical
perspective on the documents.
This top-level semantic model contains concepts
such as place, time, event, organization, collective
entity, participant, different roles played in events,
etc. Table 1 shows the basic structure of HERO.
HERO is the result of the integration of an
analysis of existing models  (Agora, 2018) (CIDOC-
CRM, 2018) (Raimond and Abdallah, 2007) (Doerr
et al., 2010) (van Hage et al., 2009) (Nanni et al.,
2017) (Sprugnoli and Tonelli, 2017)  and the
outcomes of the dialog between computer scientists
and historians about the notion of event, its properties
(e.g., participation in events, roles played by
participants) and the relations between events (e.g.,
cause, influence).
Most of the existing models  the most famous of
which is probably CIDOC-CRM  are mainly
designed for representing production, preservation
and curation activities and has been employed in
several projects for describing documents types,
creators, geographical/temporal anchoring. Although
most of these models support the representation of
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events and their participants, their level of detail and
granularity does not make any of them the first
choice, when the focus is the fine-grained
representation of historical events and the relations
over them outside documents. By the way, for
interoperability reasons, PRiSMHA includes
mappings between HERO top level classes/properties
and the corresponding elements in the most used
existing ontologies.
We identified the students and workers protest
during the years 1968-1969 in Italy as the specific
domain to focus on in developing our proof-of-
concept. The available documents concerning this
period are mainly non-digitized typewritten leaflet
(often containing manual annotations or drawing),
newspaper or magazine articles, and some pictures
(see Figure 1).
The historians analyzed the documents, from the
Ist. Gramsci's archives, referring to this period, in
order to select the most relevant ones with respect to
our goal. The top-level semantic model defined in
HERO has guided the analysis and subsequent
selection of documents: For each document, an
analytical card has been built, structured on the basis
of the classes and properties defined in the top-level
semantic model.
Table 1: The basic structure of HERO.
HERO-TOP
Very general classes and properties,
e.g., concepts such as abstract entity,
(non)physical object, occurrence, and
properties such as being part of,
being a sub-concept of
HERO-EVENT
General classes and properties useful
for characterizing events, e.g., event,
state, action, coming into existence,
participating in an event, playing the
role of agent in an event, occurring
at a certain time or in a certain
place, causing
HERO-ROCS
(Roles,
Organizations,
Collections,
Sets)
General classes and properties useful
for representing roles, organizations,
collections, and sets, e.g., role,
organization, being affiliated to an
organization, playing a (social) role,
being a member of a collective/set
HERO-PLACE
General classes, properties (and
individuals) useful for characterizing
places, e.g., place, building,
inside/outside, close to, ...
HERO-TIME
General classes and properties useful
for representing time intervals, e.g.,
time interval, day, date, Allen's
relations between time intervals
(preceding, following, overlapping,
...), Monday, February, UTC+1:00
Figure 1: Examples of documents concerning the students and workers protest during the years 1968-1969 [copyright:
Fondazione Istituto Piemontese Antonio Gramsci].
Fruitful Synergies between Computer Science, Historical Studies and Archives: The Experience in the PRiSMHA Project
227

Figure 2: A fragment showing the analytical cards corresponding to four documents from the archive of the Fondazione
Istituto Piemontese Antonio Gramsci (fondo Giorgina Arian Levi).
The cards, besides some fields related to archival and
practical aspects (e.g., classification data; see the first
eight columns, in grey, in Figure 2), contain fields
describing the content of the document in terms of
events, people, organizations, collectives, social
roles, and places, referred to by the document itself
(see the last six columns, with white background, in
Figure 2).
The selected documents have been digitized,
OCR-ized (when possible), and linked to the archival
record on the 9centRo platform.
Moreover, the content of the cards, built by
historians analyzing documents, has been used, in
turn, to build the domain ontology (HERO-900), i.e.,
the specific semantic model that refines HERO and
contains concepts, properties, and relations
characterizing the chosen domain (e.g., Strike,
PoliceCharge, TradeUnion, …). In building HERO-
900, this source of domain-specific information has
been coupled with domain expertise directly provided
by historians.
This “spiral” process is a concrete demonstration
of one of the most important synergies the PRiSMHA
project is based on, i.e., the synergy between the
historical perspective, the computer science
requirements, and the archivists support: We started
from the dialog between computer scientists and
historians; we built the top-level ontology; we used it
as a lens to select and analyze archival documents; we
exploited the document analysis  together with
domain expertise  to build the domain ontology.
Moreover, this process provided us with the
needed experience on the field that enabled us to
define a virtuous procedural model, from the paper
documents up to the digital “smart archivist”, based
on a close collaboration between universities and
cultural and historical institutions.
3.2 Building the Knowledge Base
Following an iterative methodology based on rapid
prototyping, we designed and built a first prototype of
the crowdsourcing platform, implementing a limited
number of the functionalities that had emerged from
the elicitation of user requirements and the definition
of the use cases.
The current prototype offers a form-based User
Interface that enables users to “annotate” archival
documents with formal semantic descriptions of their
content. Figure 3 shows a screenshot of the prototype,
i.e., the page enabling the user to create a new entity
to be added to the semantic knowledge base. The
document lays in the background (relevant fragments
are highlighted); a modal window enables the user to
look for existing entities in the knowledge base or to
add a new entity by clicking on the corresponding
button: in this last case, a new modal window
overlays the previous one, thus enabling the user to
select the entity type (represented by a class in the
ontology) and provide a label for the new entity.
The process of associating formal semantic
representations to the documents is driven by the
underlying ontology HERO-900, and aims at
collaboratively building the knowledge base
(encoded as a RDF triplestore) used by the system.
Meanwhile, we are investigating the exploitation
of automatic Information Extraction on OCR-ized
archival documents. This is a very challenging issue,
due to the specific nature of texts in these documents
(Rovera et al., 2017), (Moretti et al., 2016). We aim
at studying how the output of such activity can
provide an effective support to the annotation process
on the crowdsourcing platform.
KMIS 2019 - 11th International Conference on Knowledge Management and Information Systems
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Figure 3: A screenshot of the UI enabling the user to create a new entity to be added to the triplestore.
4 CONCLUSIONS AND FUTURE
WORK
In this paper we have presented the mid-term results
of the PRiSMHA project, that aims at contributing to
the design and implementation of a web-based system
providing an intelligent access to historical archives.
In particular, we showed the products of the fruitful
synergies between historical studies and computer
science, as well as the results of the collaboration
between research institutions and cultural centers.
Such results include a top/core ontology (HERO) and
a domain ontology (HERO-900), which together
drive the User Interface of the prototype platform
devoted to the user-generated semantic KB.
Plans for the next activities within the PRiSMHA
project encompass:
 The evaluation of the mentioned prototype with
users, in order to get a feedback for implementing
the second version;
 The design of an enhanced interaction model for
the crowdsourcing platform aimed at integrating
suggestions coming from the Information
Extraction tools.
ACKNOWLEDGEMENTS
This work has been supported by Compagnia di San
Paolo and Università di Torino within the PRiSMHA
project.
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