Laying the conceptual foundations for data integration in the humanities

The purpose of this paper is to promote the discussion
on what are the key dimensions of humanities’
scholarship, and how they can be best represented by
means of formal languages in the context of the Semantic
Web. Quite often, available formalizations of knowledge
domains and practices in the humanities have been
inspired by previous work on more rigorous scientific
domains. As a result, we believe that the models thus created
tend to oversimplify, if not totally misunderstand,
the complexity and peculiarity of the work of humanities’
scholars. In this paper, we want to highlight a number
of characteristics that need to be taken into account
when modeling humanities’ data. We argue that only by
keeping in mind such requirements we will be able to lay
out solid foundations for facilitating non-trivial information
integration in humanities domains. We are currently
testing these ideas in our department by reflecting upon
anumber of preexisting digital humanities projects. The
final paper will give a more extensive description of this
evaluation.
Introduction
In recent years we have seen a proliferation of research
and commercial projects aiming at the dissemination of
a large number of structured or semi-structured data.
On the academic side, for example, enterprises such as
the Semantic Web (Berners-Lee et al., 2001) have long
attempted to support the creation of a vast-scale layer
of machine-processable data, which should work as
an ‘extension’ of the traditional web. Less academic examples
are instead Freebase (Freebase, 2007), a web application
aiming at becoming an “open, shared database
of the world’s knowledge” which can be freely edited by
registered users, and the DBpedia (Auer et al., 2007), a
community effort to extract structured information from
Wikipedia and make it available on the web by means of
a public API1.
In this paper, we associate these developments in web technologies with the term ‘semantic web’ (SW), as they
all share the intent to encode formally (with varying degrees
of complexity) aspects of the meaning of the resources
or artifacts they refer to.
It is worth asking then, why should we as digital humanists
be adopting a semantic web approach? A primary advantage
of having structured data exposed on the web is
the possibility to integrate and reuse them in novel ways.
For example, we can imagine a scenario where data
coming from an archeological project about Tutankhamun
are being accessed by other archeologists interested
in pottery produced in Egypt in the same period. Pushing
it a little further, we could also think of a research group
in sociology of science examining the same data, looking
for anomalous patterns in the archeologists’ daily
data-collection practices.
From an examination of the most recent literature, it is
easy to conclude that semantic web technologies have already
been tested in a variety of domains. These include
both hard science domains, such as physics (Friedland
and Allen, 2004), biology (Bechhofer et al., 2006), mathematics
(Habel and Magnan, 2007), but also humanities’
disciplines such as history of art (Hildebrand et al.,
2006), literature (Nowviskie, 2005), music (Schraefel et
al., 2005).
However, this spectrum of experimentations leads us to a
further consideration. Since scientific domains are highly
structured they can more easily be mapped into formal
conceptual schemas, so as to be used in SW applications
-e.g., a gene ontology, or an ontology of hardware components.
This is not the case for all humanities domains,
especially where scholars give high value to processes
like the expression of subjective interpretations and the
debate on the subject in question, rather than aiming to
search for objective schemas or universal taxonomies. In
other words, the task of modeling knowledge domains
in the humanities through formal languages (so as to allow
computability and data integration) presents various
challenges which are still to be tackled by existing research
on the semantic web front.2
For example, it is our view that systems such as /facet
(Hildebrand et al., 2006) or CultureSampo (Eero
Hyvönen et al., 2007), although providing advanced interfaces
for exploring humanities’ data, do not investigate
enough the type of semantic ‘services’ humanities’
scholars often engage with in their research practices. In
fact, very often such systems make use of very ‘shallow’
semantic models (e.g., a ‘person’ who created a ‘work’
which belongs-to a ‘style’), thus oversimplifying the actual
discourse that makes a statement valuable within a
humanities discipline. As a consequence, data thus structured
can hardly be of use to the humanities scholar in
her research and activities.
If data sharing and integration in the humanities is recognized
to be worth pursuing, it is therefore necessary to
build some solid foundations for a truly useful semantic
web framework in the humanities. The first activity that
will help us in this respect is a thorough consideration of
the typical entities and practices emerging in humanities’
research. Accordingly, in section 3 we outline a number
of key requirements humanities’ semantic models should
support. In the following section we spend some words
on the approach that drivesour usage of ontologies for
data integration.
Ontology: a beauty or a beast?
A central notion in the semantic web and in the world of
data integration is that one of ontology. The widely used
definition by Gruber (Gruber, 1993) describes it as “an
explicit specification of a conceptualization”. Being a
conceptualization an ontology is therefore a stylized representation
of the world; secondly, since it is expressed
in a formal language, an ontology can be defined unambiguously.
As a consequence, ontologies are well suited
representation languages for describing data and sharing
information; their employment is also endorsed by the
W3C (W3C, 2004).
Besides this quite conventional view of what an ontology
is, the debate is ongoing about the status of an ontology
with respect to the world it represents. For example,
some authors such as Smith (Smith, 2003) hold a
realist position, while others such as the aforementioned
Gruber (Gruber, 2003) support a more pragmatic view.
Such positions affect inevitably the way ontologies are
developed and used. For example, in the first case (realist)
the implicit assumption is that the ontology should
approximate to a ‘true’ reality; as a consequence, multiple
ontologies about the same subject should ultimately
converge in their modeling choices. On the contrary, the
second class of ontology-design approaches (pragmatist)
seean ontology essentially as an engineering artifact:
thus, it does not hold any absolute value about the
reality it depicts, but it provides a practical solution to
the ‘problems’ it was designed to tackle (i.e. it is a mean
to an end).
Although in the SW world both approaches have many
followers, the context in which digital humanities practitioners
and researchers operate, in our opinion, is much
closer to the pragmatic approach. Indeed, the humanities
are often perceived as the place where all the voices
—provided they are respectful of certain argumentative conventions—can be heard, and where all the assumptions
can be questioned. Therefore, ontologies for the
humanities must support diversity and variety of viewpoints;
thus they cannot adhere to an underlying model
which neglects multiplicity in favor of a monolithic vision
of the world.
Following Gruber (Gruber, 2003), we therefore intend
to promote the concept of an ontology as the agreement
reached by multiple parties (e.g., programmers, scientists,
collaborators, librarians) with the aim of accomplishing
some objectives (e.g., data exchange between
applications, communication between people, integration
of disparate representations). Using a metaphor, ontologies
are contracts, they are the currency used to perform
some valuable operations. Thus, their importance is
ultimately related not to their truth or beauty, but to the
ease they bring to the collaboration among people3. To
use a less ‘commercial’ metaphor an ontology is a compromise
or a point of contact between specific and possibly
divergent models. The issue is therefore not only
to identify commonalities between projects, for instance,
but also to agree that the compromises so found won’t
diminish the value of the underlying idiosyncratic models,
the specificity of any single project or interpretation.
We believe that in the humanities this agreement is not
necessarily reachable once for all or hoped for, because it
may imply the negation of the interpretative efforts that
make a work or a project unique and the negation of the
evolutionary nature of scholarship. However, we also
think that the possibility to make two incommensurable
categorical systems communicate could be a challenge
worth pursuing.
Defining humanities’ research
As mentioned above, at a general level it is useful to
characterize humanities scholarship by highlighting the
points of contrast with the hard sciences. Humanities
scholars are traditionally engaged with the expression of
interpretative statements and the elaboration of debates
on a disparate range of sources of knowledge, rather than
with the seeking of firm objective schemas or universal
taxonomies. One of the authors analyzed more specifically
the characteristics of a humanities domain (Pasin
et al., 2007)—philosophy—and identified those key elements
that define its scholarship and make it hard to
model. Some of these elements are outlined below:
1. historical events, that is, events which are inherently
time-dependent (e.g., the publication of a book,
or an author’s subscription to a viewpoint);
2. generic uncertainty, that is the frequency of statements
about facts which cannot be located exactly
in the time and space dimensions (e.g., the birth of
Heraclitus);
3. information objects, i.e. texts in a semiotic sense
and especially language-based information objects
(e.g. a book), as they are the traditionally preferred
medium philosophical contents are expressed with;
4. interpretation events, intended as the process of
attributing an abstract content to an information object
(e.g., when we say that “Aristotle’s fourth book
of the Metaphysics states an ontological principle”);
5. coexistence of contradictory information, which is
a direct consequence of 4 (e.g., when people claim
different or opposing views on the same proposition);
6. viewpoints, and other non-material entities (“philosophical
ideas”), for they are the objects philosophers
are usually engaged with by studying and expressing
them.
Although philosophy has often been defined as the queen
of the sciences, these reflections on its nature as discipline
may not stand true for thehumanities as a whole.
In order to highlight all the dimensions that make the
modeling of humanities domains such a unique task, we
surely need a thorough investigation of other humanities’
domains too. Furthermore, for space reasons we
have deliberately not mentioned other works in the digital
humanities, such as (Jones, 2006) and (Eide, 2008),
where the issues tackled are remarkably similar to ours,
although the approach is not necessarily ontology-oriented.
We intend to elaborate more on these topics in the
final version of the paper.
Conclusions
In this extended abstract we addressed a number of problems
emerging from the employment of semantic web
technologies in humanities domains. In particular, we
focused on the notion of ontologies for data-integration,
highlighting the great challenges these technologies will
bring especially to the digital humanities’ practitioner.
To this aim we also provided some examples from our
previous research in the philosophical domain. In the
final paper we will expand this research also by drawing
from the results of a detailed analysis of the various
projects ongoing in our department. It is our hope
that this research will stimulate further discussions and
the formulation of a preliminary but comprehensive research
agenda. References
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Notes
1Application Programming Interface, that is, an access
point by which such data can be retrieved or manipulated
programmatically.
2It has to be noted that some of these challenges have
been faced in previous efforts (preceding the advent of
the web) of formalizations in the humanities: good examples
are the creation of domain-specific thesauri and
taxonomies, or the classification systems in library studies.
3Note that we are focusing on the conceptual implications
here rather than on thechallenges of an ontology
implementation by using specific computer languages.