LOD Navigator: Tracing Movements of Italian Shoah Victims
10.6092/issn.2532-8816/9050
In questo paper viene presentato LOD Navigator, uno strumento di ricerca e visualizzazione dei dati per la tracciatura dei percorsi delle vittime della Shoah in Italia. Per lo scopo è stato utilizzato il database LOD, pubblicato dalla Fondazione CDEC di Milano, contenente le informazioni sulla vita e la persecuzione di ciascuna vittima. Tale database è stato arricchito in maniera semi-automatica e caricato sul LOD Navigator. Questo strumento offre la possibilità di ottenere una nuova comprensione dei percorsi comuni della Shoah in Italia e le storie personali delle singole vittime. Le informazioni possono essere navigate in maniera intuitiva e interattiva.
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Sara Tonelli
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LOD Navigator: Tracing Movements of Italian Shoah Victims
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2019-02-04
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2019-12-18
Um. Dig.
Sara Tonelli
2019/03/01
10.6092/issn.2532-8816/9050
Fondazione Bruno Kessler, Trento
2532-8816
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biographical data
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LOD Navigator: Tracing Movements of Italian Shoah Victims
https://umanisticadigitale.unibo.it/article/view/9050/8948
     Umanistica Digitale - ISSN:2532-8816 - n.4, 2019
R. Sprugnoli, G. Moretti, S. Tonelli – LOD Navigator: Tracing Movements of Italian Shoah
Victims
DOI: http://doi.org/10.6092/issn.2532-8816/9050


  LOD Navigator: Tracing Movements of Italian Shoah
                       Victims

                     1
                      Rachele Sprugnoli, 2Giovanni Moretti and 3Sara Tonelli

                                 Fondazione Bruno Kessler, Trento, Italy
                                         1
                                           sprugnoli@fbk.eu
                                           2
                                             moretti@fbk.eu
                                         3
                                           satonelli@fbk.eu



       Abstract. In this work, we present LOD Navigator, a data visualisation and exploration
       tool to track the lives and trajectories of Italian Shoah Victims. We take advantage of the
       work done at the Contemporary Jewish Documentation Center in Milan (CDEC),
       leading to the publication of a database of Linked Open Data (LOD) containing
       information about the life and persecution of each victim. Such database was then
       enriched semi-automatically and uploaded in the LOD Navigator, giving the possibility of
       getting new insight into collective traits of the Italian Shoah tragedy and into personal
       stories of victims. Information is now available and can be navigated in an intuitive and
       interactive way.
       In questo paper viene presentato LOD Navigator, uno strumento di ricerca e
       visualizzazione dei dati per la tracciatura dei percorsi delle vittime della Shoah in Italia.
       Per lo scopo è stato utilizzato il database LOD, pubblicato dalla Fondazione CDEC di
       Milano, contenente le informazioni sulla vita e la persecuzione di ciascuna vittima. Tale
       database è stato arricchito in maniera semi-automatica e caricato sul LOD Navigator.
       Questo strumento offre la possibilità di ottenere una nuova comprensione dei “percorsi”
       comuni della Shoah in Italia e le storie personali delle singole vittime. Le informazioni
       possono essere navigate in maniera intuitiva e interattiva.




       Introduction

The Contemporary Jewish Documentation Center in Milan (CDEC) has recently developed a
database with information on Italian Shoah victims and, following a data sharing policy, has
made it freely available as Linked Open Data (LOD). The database was built starting from
information collected in Picciotto Fargion 10. and is accessible through a web portal, i.e. the




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CDEC Digital Library,1 and a SPARQL endpoint.2
In order to provide a novel way to navigate this database taking advantage of the available high-
quality records, we developed the LOD Navigator, a system that allows users to explore the
trajectories of victims during their persecution both at micro and at macro level. The goal of
the application is to enhance the value of the original database with a user-friendly interface
focusing on an important research field in Shoah studies, i.e. the geographies of the Holocaust.
Information necessary for implementing the LOD Navigator was collected using the SPARQL
endpoint: this information includes biographical data together with details about the
persecution and deportation of each victim. The places of birth, arrest, detention, deportation
to a Nazi camp, transfer, and return after liberation (if available) were then semi-automatically
georeferenced and associated with the corresponding date. We then considered a movement as
a trajectory from one georeferenced place (associated with a dated event) to another
georeferenced place. All the movements are then displayed in the LOD Navigator through an
interactive interface made freely available as a standalone tool.3
We decided to focus our attention on movements because the Holocaust was characterized by
many spatial processes. Concentration, deportation, dispersal, dislocation are all geographical
components involved in the implementation of the Nazis' genocidal policy. Plotting data about
these spatial processes on a map and giving them a temporal dimension allows the
identification of spatio-temporal patterns at the macro-level but also at the micro-level, to
reconstruct individual experiences.
The remainder of this paper is structured as follows. Related Work presents background
information about past studies. Workflow describes how we obtained, cleaned and integrated
the data. Details on the interface are also given. Discussion about the data visualised in the
LOD Navigator is provided in Quantitative and Qualitative Data Analysis. Finally, in
Conclusions and Future Works we draw some conclusions and we list possible future
developments.


       Related Work

The ability to move groups of people separating them from their original social context is a
crucial strategy in every genocide 18.. In the case of Nazism, the genocidal policies were
characterised by radical spatial acts, euphemistically represented in Schutzstaffel's bureaucratic
jargon with terms such as Auswanderung (emigration), Aussiedlung (resettlement) and
Wohnsitzverlegung (change of residence) 17.. The literature reports on a number of works
dealing with this territorial dimension of the Holocaust and thus belonging to what Knowles et
al. call the “spatial turn in Holocaust studies” 9..
Theoretical and historiographical aspects of Nazism seen as a spatial project are discussed in the

1   http://digital-library.cdec.it/cdec-web/
2   http://dati.cdec.it/
3   http://dh.fbk.eu/technologies/lod-navigator


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                                                                                     Victims

papers collected in Giaccaria and Minca 19.. In particular, Stone 8. highlights how Holocaust
affected the entire continent: it was not just a matter related to specific places such as
extermination camps, but the violence was widespread in both small and big sites in every
nation.
In 5. and 7. the focus is on the use of GIS (Geographic Information System) and
geovisualisation as means to rethink the Holocaust at different levels of analysis. The former,
for example, presents a prototype visualisation of the journeys of eight Hungarian Jews, while
the work by Giordano and Holian 6. analyses the patterns of arrests of Jews in Italy from a
spatio-temporal perspective, using “Libro della Memoria” as their source of data. This last
analysis is paired with an interactive visualisation showing the distribution of arrests per month
during the period 1943-1945.4 This representation focuses solely on the arrest, seen as the
starting point of the whole persecution process that determines the status of “victim”, while it
does not take into consideration all the other persecution stages. Furthermore, not all victims
are included in the analysis: for example, those killed in massacres or arrested outside Italy are
excluded.
With respect to these examples of previous work, our application differs in at least 3 aspects: (i)
it follows the lives of the largest possible number of victims, so as to provide information
representative of the phenomenon; (ii) it represents all the major events related to the
persecution of Jews; (iii) it offers novel insight not only by aggregating data according to several
categories, but also by allowing the close reading of individual stories.


       Workflow

To develop the final system version, we performed 4 main tasks: we manually analysed the
available data, we extracted the data that were interesting for our aim, we manipulated them to
remove inconsistencies and add missing information. Finally, we implemented the data
visualisation functionalities in the LOD Navigator. These phases are detailed in the next
subsections.


       Data Observation
First of all, we manually analysed the data available in the CDEC digital library and the
corresponding RDF browser to select the information we should focus on to build the
application.
In the RDF browser, biographical information is given for each person, identified by a unique
ID, together with information about his/her persecution. This information is structured on the
basis of the Shoah domain ontology that formally describes concepts and relationships
characterizing the process of persecution of Jews in Italy between 1943 and 1945 [2.,3.]. In
particular, the ontology Class called Persecution describes the arrest, detention, deportation to a
4   http://web.stanford.edu/group/spatialhistory/cgi-bin/site/viz.php?id=383&project_id=0


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Nazi camp, the transfer to another camp but also the liberation and massacre. This class is
related to the Person class that includes properties connected to biographical information, such
as the date and place of birth and death. Other information, for example family relations
between victims, was present in the database but was not considered relevant in this phase of
the development.


       Data Extraction
We queried the SPARQL endpoint to retrieve all the information we needed and we chose to
obtain results in CSV format.
In this way we extracted the content of 26 properties (see Figure 1) for 9,042 people identified
as Italian victims of the Shoah. These properties include basic personal information such as
gender and place of birth and death, but also details on the different events related to Shoah in
each person's biography, for example the date and place of arrest, the date of transfer to the
Nazi camp and the type of death. Overall, we selected all properties necessary to trace the
personal trajectories of the victims along a timeline.




   Figure 1: Properties whose content was extracted from CDEC LOD dataset



       Data Manipulation and Integration
In the third step, we performed a semi-automatic check of the data formats to fix
inconsistencies. Since the information had been manually recorded, possibly by different
persons, in some cases data formats and conventions were not homogeneous. Besides, we
decided to simplify some information associated with each biography and add details that can
help the user's navigation.
A particularly challenging case was the format of dates, which we found in 14 different variants


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                                                                                      Victims

including at least the year (e.g., 19250315, 1900, 16/06/1944, 1944.02.26). These date
versions have been converted, using a Python script, in a unique format: YYYY-MM-DD. We
also found 8 different conventions to express the lack of temporal information, such as 0 or ?.
In this case, we could not give a temporal anchor to the corresponding event, therefore we had
to remove the event from the database.
We also decided to modify people occupations by clustering the available options into coarse-
grained categories to simplify navigation for end users. While in the LOD database we found
168 occupations, we observed that some of them were only little different, for example
“calzettaia” / female hosier and “calzettaio” / male hosier. So we used Wikipedia classification of
occupation types5 and we selected 27 coarse-grained categories, onto which we mapped the
original ones. In this way “calzettaia / calzettaio / calzolaio” were clustered all under the
category “Craft occupations”. For all victims without an associated occupation, the unknown
category was added.
In case the place_of_death property had no value, we automatically extracted the places
mentioned in the free-text descriptions of the field deathDescriptionIntegration. This was
performed using The Wiki Machine 11., a system that links the concepts mentioned in a
document to the corresponding Wikipedia page describing them. By selecting only the pages
referring to a place, we automatically identified geographical mentions. For instance, giving as
input the sentence “Ucciso in tentativo di fuga a Milano”/Killed in an attempt to escape in
Milan, the tool links “Milano” to the corresponding Wikipedia page, and annotates the word as
a location, more specifically as an administrative region, as shown in Figure 2.




    Figure 2: Example of output of the Wiki Machine


Another integration we performed semi-automatically was adding the country of origin of each
victim. This information was obtained by looking up the abstract property, which always
contains a sentence such as: “She was born in France...”.

5    https://en.wikipedia.org/wiki/Category:Occupations_by_type


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Since the final goal of LOD Navigator is to display the places on a map, another crucial step
involved georeferencing place names, that is finding the coordinates of locations. In total we
found 1,493 unique places in the data and we used Nominatim 6 to automatically retrieve their
latitude and longitude. In 15% of the cases this automatic process failed and we had to
manually correct wrong coordinates (for example, Nominatim locates Siena in China) or we
had to georeference places by hand because Nominatim could not find any coordinate.
Sometimes this was due to the presence of some non-standard spelling but through spelling
normalization it was possible to map different versions to the correct name and to precise
coordinates (e.g. spelling variant: Gross-Meseritz -- standard spelling: Gro ß Meseritsch). For
other locations, we could only make an approximation by using latitude and longitude of the
country they should belong to, inferring this information from the content of other fields. For
example, we could not locate Choumbla, but it was possible to associate it to the coordinates of
Bulgaria, taking this information from the content of the abstract property: Menachem
Levi, son of Haim Levi and Veneziana Benveniste. He was born in Bulgaria, in Choumbla, on July
23 1876.
At the end of the step, all retrieved data were corrected and harmonised, and they were
converted in JSON format. Each victim was associated with biographical information and the
list of his/her movements.


       Data Visualization
The last step involved building a tool to support data visualization and navigation. To this end
we employed standard open-source technology: i.e., Node.js 7 as JavaScript run-time
environment, Electron8 as framework for the development of the graphical user interface,
Leaflet9 to built the interactive map. Moreover, trajectory arches are rendered in a vector image
format (SVG) that facilitates interactivity by easily managing user interface events such as click
and mouse-over.
The interactive interface of LOD Navigator allows users to search by name or place using an
auto-complete function, to refine the search by temporal constraints with a timeline, to filter
victims by country of origin, occupation, gender and death description (e.g. Dead in massacre
or Dead in extermination camp). If a specific person is selected, a fly-over functionality enables
users to display the trajectories from one location to the other, recreating a victim's story. Each
movement is paired with a sentence automatically generated by combining the type of event
(e.g. arrest), the corresponding date and place and, as for the arrival to the Nazi camp, the
number of the convoy. e.g. Primo_Levi-5002 - Arrived in Auschwitz on February 26, 1944 with
convoy number 8.
In addition, for each person there is a direct link to the corresponding entry in the CDEC


6   https://nominatim.openstreetmap.org/
7   https://nodejs.org/
8   https://electron.atom.io/
9   http://leafletjs.com/


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                                                                                     Victims

Digital Library,10 where users can find additional information related to the victim (e.g. family
relations, images, documents).




Figure 3: Screenshot of the interface: movements of Jews having a craft occupation and survived to the
Shoah


The different properties extracted from the CDEC LOD dataset can be used in the Navigator
to set filters and view aggregated data. For example, Figure 3 shows the movements of all the
Shoah survivors having sales occupations: filters are displayed on the right, victims resulted
from the query are listed below the filters and places can be searched using the search field at
the top of the map. Furthermore, a timeline is at the bottom of the interface together with a
legend explaining the match between trajectory color and the value of the
death_description property. Trajectories have a black arrow indicating the route
destination. The marker flagging each location can be clicked to see the list of people that
passed through that place. Aggregated information can also be zoomed in to analyse the life
and destiny of a single person. For example, Figure 4 presents how the content related to
Primo Levi is displayed by using a metro-like visualisation. The fly-over functionality is
activated by clicking on a single event in the list, which automatically displays a detailed view
of the place where the event occurred.



10 For example, in case of Primo Levi, there is a direct link to his personal page in the Digital Library:
   http://digital-library.cdec.it/cdec-web/persone/detail/person-5002/levi-primo.html


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                       Figure 4: Metro-like visualization




       Quantitative and Qualitative Data Analysis

The LOD Navigator contains information about 8,712 victims (4,470 males, 4,239 females,
and 3 of unknown gender) that, according to the analysis described in Related Work, were
found to have at least one dated movement between two georeferenced places. This means that
the application displays the lives of 96.3% of all the victims recorded in the CDEC LOD
dataset. Most of them (89.8%) do not have a specified occupation: among the others, the most
common category is Sales occupations with 407 people having jobs such as salesperson, peddler
and shop assistant. As for the country of origin, victims were born in 37 different nations: Italy
is the most represented country (4,276 people) however the remaining 36 countries cover 49%
of all the victims. This shows that, although we deal with Italian Shoah, around half of the
victims were either arrested, detained or dead in Italy, but were originally from other countries.
In many cases, for example for many French and Eastern European Jews, Italy was the country
where they fled in the hope to escape from Nazi threat, while others lived in Italian possessions
that, after the Armistice of Cassibile, were occupied by German troops.
Victims' fate is described by the value of death_description property, used as a filter in
the application. We report in Table 1 some statistics extracted with the help of LOD Navigator:
sadly, the great majority of victims in the database (84.2%) died in an extermination camp, and
only 12% survived the Shoah.
We also show in Table 2 the locations displayed in the Navigator interface that are more
frequently associated with specific events. Each row in the table can be explained by connecting
it to the history of Jewish communities in Italy and in Europe in the XX Century. For example,
many victims were born in Rome, Trieste and Venezia, because at the time they had the largest
Jewish communities in Italy. Rhodes was also the birthplace of many victims, because it had
been under Italian control since 1912 and in the 1920s the local Jewish community was very
important, including around one-third of the total population. Rhodes is also the place



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                                                                                    Victims

witnessing the highest number of arrests (1,758 out of 7,960), confirming that the Shoah led to
the deportation and the death of most of the community members. Despite being a small city,
also Borgo San Dalmazzo is among the places where most of the arrests were carried out. This
is because it hosted a Nazi concentration camp, where foreign-born Jews from France were
arrested trying to escape the Vichy regime. Also Fossoli is just a small village in Emilia
Romagna, but it was the place of detention for most of the recorded victims because there was
a transit camp where Jews were detained before being sent to Auschwitz. The latter is the camp
where most of the victims in CDEC database were deported and died. In addition to two other
extermination camps (i.e., Monowitz and Flossenburg), many Jews died in massacres as in
Rome (Fosse Ardeatine) and at Lake Maggiore. Information about the return after liberation is
available only for 136 people. The proportion between Shoah victims that were born in Rome
and those that returned to the city after liberation (1,526 vs. 86) shows, as an eloquent
example, the impact of this tragedy on local Jewish communities.



  death_description                                                QUANTITY
  Dead in extermination camp                                       7,333
  Survivor of Shoah                                                1,037
  Dead in massacre                                                 202
  Dead in custody                                                  70
  Unknown                                                          28
  Dead en route to camp                                            15
  Committed suicide                                                10
  Dead of hardships and privations                                 6
  Killed in escape attempt                                         6
  Missing                                                          6
  Killed during arrest                                             1
  TOTAL                                                            8,712
Table 1: Division of victims on the basis of the death_description property



EVENTS                       #         TOP 5 PLACES
Birth                        8,340     Roma (1,526) - Rhodes (1,524) - Trieste (466) - Vienna
                                       (205) - Venezia (200)
Arrest                       7,960     Rhodes (1,758) - Roma (1,712) - Trieste (509) - Borgo



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                                        San Dalmazzo (329) - Milano (241)
Detention                    7,873      Fossoli (2,699) - Rhodes (1,712) - Roma (1,029) -
                                        Milano (872) - Trieste (661)
To Nazi Camp                 7,893      Auschwitz (7,338) - Bergen Belsen (405) -
                                        Ravensbrueck (89) - Flossenburg (27) - Buchenwald
                                        (25)
Nazi Camp Transfer           821        Vittel (107) - Monowitz (86) - Biberach (75) -
                                        Buchenwald (59) - Mauthausen (56)
Death                        4,332      Auschwitz (3,743) - Roma (81) - Monowitz (57) - Lago
                                        Maggiore (50) - Flossenburg (38)
Return after Liberation      136        Roma (86) - Milano (32) - Torino (7) - Tripoli (4) -
                                        Livorno (2)
TOTAL                        37,355
Table 2: Number of events dated and georeferenced in the LOD Navigator together with the five most
frequent locations for each event



        Conclusions and Future Works

In this paper we have presented the LOD Navigator, an example of digital history application,
whose contribution is manifold: it provides for the first time an interactive system, through
which part of the data collected by CDEC can be browsed, searched and visually displayed on a
map. This can benefit the community of researchers interested in studying the Shoah but also
the Jewish community and the broad public. We believe that the main innovative idea of the
LOD Navigator is to visually track movements that, when available only in LOD or plain text,
do not give the possibility to get an overview or to interact with the data. It addresses the needs
of researchers and scholars but also of the families involved in deportations and all the Jewish
community to support their effort in reconstructing stories of families and losses during the
Shoah. Besides, the navigation system is data-independent and can be used to view other
trajectories by uploading a simple JSON file containing georeferenced places and dates, thus
providing a useful tool to (digital) history scholars at large: for example, in Menini et al. 4., a
preliminary version of the interface was adopted to trace the motion trajectories automatically
extracted from Wikipedia biographies with the aim of providing important data for the analysis
of culture and society.
As for future work, many possible developments can be envisaged. First of all, we plan to
release a web-based version of the application to facilitate data navigation without requiring
any installation. From the point of view of the visualization, it would be important to find an
efficient way to deal with uncertainty. Indeed, some dates and places in the database are stored
as uncertain (associated with a question mark), thus it would be important to visually display
this lack of confidence. Moreover, new filters could be added for example to allow searching for


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                                                                                    Victims

specific events (e.g. to display only movements related to the detention event). Another
interesting extension would be to include information about family relations present in the
CDEC digital library, so to trace trajectories at family level and take advantage of our tool's
interactivity to easily spot whether its members followed the same path or were separated in
one of the stages of persecution 14.. An additional effort should also be made to evaluate the
usability and effectiveness of the tool, both explicitly with a questionnaire and implicitly by
tracking the searches performed by users, similar to the evaluation presented in 1.. Looking at
our application in a long-term perspective, we envisage the extension of current input data with
other information taken from similar databases developed in other Nations 11 or from
documents in plain text 12.. This would be a crucial step to extend the potential of LOD
Navigator to the story of other Jewish communities 15., 16..




         Acknowledgements

We wish to thank Laura Brazzo (CDEC) and Silvia Mazzini (regesta.exe) for publicly sharing
the data that we used to develop our application.




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