=Paper=
{{Paper
|id=Vol-3110/paper6
|storemode=property
|title=TEI Beyond XML - Digital Scholarly Editions as Provenance Knowledge Graphs
|pdfUrl=https://ceur-ws.org/Vol-3110/paper6.pdf
|volume=Vol-3110
|authors=Andreas Kuczera
|dblpUrl=https://dblp.org/rec/conf/graph/Kuczera20
}}
==TEI Beyond XML - Digital Scholarly Editions as Provenance Knowledge Graphs==
https://ceur-ws.org/Vol-3110/paper6.pdf
TEI Beyond XML – Digital Scholarly
Editions as Provenance Knowledge
Graphs
Andreas Kuczera
University of Applied Sciences (THM)
Gießen, Germany
Abstract
This paper proposes to detach TEI semantics – a widely accepted stand-
ard for the description of textual phenomena – from its hierarchical
XML framework in order to integrate its descriptive structures into a
digital scholarly edition (DSE) of Hildegard von Bingen’s Liber epis-
tolarum based on a knowledge graph enriched with provenance inform-
ation.
To which problem is digitization the solution?
(Nassehi, 2019)1
1 Introduction
The search for origins is a quintessential human activity. Scholars in the hu-
manities – especially historians – engage in this activity by examining cul-
tural artefacts such as texts, objects, and images. In so doing, they make use
Creative Commons License Attribution 4.0 International (CC BY 4.0).
In: Tara Andrews, Franziska Diehr, Thomas Efer, Andreas Kuczera and Joris van Zun-
dert (eds.): Graph Technologies in the Humanities - Proceedings 2020, published at
http://ceur-ws.org
This long paper is based on research presented at “Graph Technologies in the Humanities
2019” (January 18-19, Academy of Sciences and Literature | Mainz, Germany).
1
Translation by the author
101
of consensus-based techniques and methods, which enable a common un-
derstanding of their findings once they are published, for example, in the
form of a critical edition. And yet these scholarly standards are themselves
subject to a constant process of alteration and development: historical re-
search is now increasingly permeated by digitization and the possibilities that
come with it. Digital technology has significantly extended the methodolo-
gical repertoire of researchers in the humanities, and the fact that scholars
are no longer bound to paper as a medium means that a rich variety of new
interpretative approaches have emerged – a state of affairs that is clearly at
odds with Barbara Bordalejo’s contentious assertion that “there is no such
thing as digital scholarly editing” (Bordalejo, 2018, pp 24).
The majority of today’s digital scholarly editions (DSEs) use the Text En-
coding Initiative (TEI) standard in combination with XML and its inher-
ent hierarchies, as it is widely considered to be “a well-documented format
for archival long-term preservation” which allows researchers to describe “a
large number of textual phenomena in general ways” (Cummings, 2018).
But research data in general, and the data of DSEs in particular, is highly con-
nected and far from easy to express within a hierarchy (Witt, 2018, pp 222-
223); a point to which I will return in Section 4. James Cummings certainly
does not exaggerate when he states that the notion that “XML has difficulty
with overlapping hierarchies is not, in itself, strictly a myth” (Cummings,
2018, pp i70). And things become even more complex if we begin to in-
clude the divergent perspectives of researchers concerning the transcription
and edition of a given text. One crucial step towards addressing this issue
is to move from the text-as-document paradigm toward what Zundert and
Robinson refer to as the text-as-work paradigm (van Zundert, 2016, p. 103-
104). But as I will argue in what follows, we ought in fact to go one step fur-
ther by fully recognizing that researchers in their various roles as transcribers,
editors, annotators, and users are themselves a key factor in the system of tex-
tual editing. Such an approach follows Niklas Luhmann’s observation that
[t]he inclusion of the observer and the instruments of observation in the
objects of observation themselves is a specific characteristic of universal
theories.2
It goes without saying that this essay is not about presenting a universal the-
ory – the point is that we would be well advised to think of editors and users
as integral parts of an interconnected system. Everything contributors do, all
their observations and decisions, become part of the DSE as a work (Kuczera
and Kasper, 2019). Jeffrey C. Witt has already suggested to conceive of DSEs
2
(Luhmann, 1987, 164) (translation by the author).
102
as multipartite networks (Witt, 2018), which is essentially a way of describ-
ing a graph. For Witt, however, researchers themselves do not form part of
this network: on the textual level, he models “each text as an Ordered Hier-
archy of Content Objects (OHCO)” (Witt, 2018, p. 231).3
What I would like to propose instead is to model a DSE as a proven-
ance knowledge graph which contains the entire critical apparatus, one or
more transcription(s) and, if applicable, details concerning the relationships
among them, as well as information on the origin of every statement. De-
scribing textual phenomena (including the actions of the editor or editors)
by means of TEI semantics has the advantage of maintaining semantic in-
teroperability, as TEI is the established standard in the field. Moreover,
TEI renders the connection between researchers and their work transparent.
Made available in the form of a provenance knowledge graph, this crucial
information in effect turns research data into a collection of subjective de-
cisions made by researchers – it is then up to individual users to decide how
much they trust these decisions based on the expertise and academic profile
of the scholar(s) in question. To manage this highly connected trove of re-
search data, a labeled property graph (LPG) database can be used. With this
groundwork in place, the next step will be to connect individual knowledge
graphs either in part or in their entirety to a broader system of concurring
and/or diverging statements and interpretations.
2 The Rise of Connected Research Data
To better understand the desideratum articulated in this paper, let us con-
sider the process of digitization in the field of medieval history, a develop-
ment that has taken place in at least two distinct stages.
2.1 Image Digitization
The first stage, which lasted until the end of the 1990s, was characterized by a
strong focus on image digitization. In Germany, one important protagonist
in the field was the dMGH project, in the course of which the volumes of
the Monumenta Germaniae Historica (MGH) were scanned, saved as image
files, and made accessible on the internet (Sahle and Vogeler, 2013).
By way of example, Figure 1 shows the scan of a page from the MGH with
a transcription of a charter of Emperor Frederick Barbarossa. In most cases,
these early attempts at digitization did not allow for text to be copied out of
the images, but they were still a step in the right direction: a large amount of
research material was made available to researchers even if the paper copies
were absent from their library.
3
On OHCO, see DeRose et al. (1990).
103
Figure 1: Scan of MGH DDFI.2, p. 260 with a charter of Emperor Frederick Bar-
barossa (Source: dMGH https://www.dmgh.de/mgh_dd_f_i_2/index.htm#page/260/mode/1up)
2.2 Full Text Digitization
Around the turn of the millennium, this first stage evolved into a phase of
full text digitization with projects such as Regesta Imperii Online (Schulz,
2017). Having been personally involved in this project, I can vividly remem-
ber the discussions about whether image digitization or full text digitization
should be used. One major argument advanced by the proponents of image
digitization was that optical character recognition (OCR) was still in its in-
fancy and highly error-prone. We addressed this issue by linking every full
text item on our website to a scan of the corresponding book page in the
Regesta Imperii, which gave users direct access to the material that was being
digitized and allowed them to identify inaccuracies.
Figure 2: Full text version of the charter from Figure 1 (Source: http://www.
regesta-imperii.de/id/1162-09-07_2_0_4_2_2_587_1145)
With the advent of full text digitization, large-scale computer-based text
retrieval from historical documents became a possibility, and this major im-
104
provement brought with it entirely new ways of scholarly exploration.
2.3 Entities in Focus
Today, we are facing the next important step: it is now time to focus on the
entities in the text.
Figure 3: Fol. 341r of the Liber epistolarum
Identifying, annotating, and connecting these entities with data from au-
thority files like GND or Wikidata enables the interconnection of individual
research projects. It also becomes possible to model scholarly interpretations
and the various steps of the research process in machine-readable statements
– Section ?? will describe this process by example of a project dedicated to
Hildegard von Bingen’s correspondence.
3 “Myths and Misconceptions about the TEI” –
Thoughts From an Expert
In a recent article, Cummings (2018) shared his thoughts on what he per-
ceives to be widespread myths or misconceptions concerning the TEI.
3.1 “XML is broken or dead”
The first of these myths is that “the TEI is XML (and XML is broken or
dead).” As Cummings points out,
[t]he TEI Guidelines were first expressed in SGML as a markup lan-
guage and only as of TEI P4 moved to recommending XML, but even
this recommendation may change in the future (Cummings, 2018, i59).
With SGML, there had been no problems with overlapping markup –
only with the shift to XML did overlap create the need for various work-
arounds.4 On the other hand, however, the use of XML gave access to its
entire ecosystem, and XML was the rising star in the field of markup at the
time. Yet there is no reason why this arrangement has to be permanent:
4
https://www.tei-c.org/release/doc/tei-p5-doc/en/html/NH.html
105
[A]s new languages, technologies, and methodologies for text encod-
ing emerge in future, the TEI Guidelines may move to them or include
them as one of a set of ways to serialize digital text, so as long as they
meet the basic requirements for easy long-term preservation, expressive-
ness, validation, integration, and mass adoption that is seen with XML.
(Cummings, 2018, p. i59).
And this is precisely where our DSE of Hildegard von Bingen’s letters comes
into play: its core principle is to employ TEI semantics without the hierarch-
ical structure of XML.
3.2 The Future of XML as a Format for Text Encoding
At this juncture, I would like to share a personal observation regarding the
future of XML. When we started using the format in our project Regesta
Imperii Online in the early 2000s (Rübsamen and Kuczera, 2006), the pro-
ject involved only comparatively basic annotation, so that any of the large
number of freely available XML editors in plain XML mode was up to the
task. Nowadays, many edition projects in the digital humanities employ the
commercial software OxygenXML, often in combination with the virtual
research environment ediarum,5 which provides customizable GUI features.
The reason for this is really quite simple: today’s annotation structures are of-
ten very complex, but OxygenXML’s author mode makes the intricate XML
elements editable while conveniently hiding them from the user’s view.
There is a good reason why, in the broader field of software technology,
XML is employed for purposes such as data exchange and the structuring
of data in configuration files, but not for the sophisticated annotation of
texts. Of course, publishers do use XML for their books, but these texts
are nowhere near as deeply annotated as the ones that we are dealing with in
the digital humanities today.
In fact, one could argue that the TEI community is in real danger of hit-
ting a dead end, unless viable alternatives to XML are found in a timely fash-
ion.
3.3 “XML (and TEI) cannot handle overlapping hierarchies”
Another myth discussed by Cummings is that “XML (and TEI) cannot
handle overlapping hierarchies” (Cummings, 2018, p. i70-i71). Clearly, this
is a bit of an overstatement: the TEI community has developed several mech-
anisms to deal with the issue of overlapping markup – at least to a certain
extent.6 But as the number of annotation hierarchies grows, these strategies
5
https://www.bbaw.de/bbaw-digital/telota/forschungsprojekte-und-software/ediarum
6
https://www.tei-c.org/release/doc/tei-p5-doc/en/html/NH.html
106
do run into increasing problems. In light of this, we could rephrase Cum-
mings’ statement as follows: “XML (and TEI) cannot handle a sufficient
number of overlapping hierarchies without complicated and ultimately inad-
equate workarounds.” In some projects, a single annotation hierarchy may
well be all that is needed – but being able to manage more of them should
the necessity arise gives researchers considerably more flexibility.
To give an example, our graph-based DSE environment Codex (Kuczera
and Neill, 2019) contains regions of text with up to 6 layers of annotation:
• Layout (page breaks, columns, alignment, etc.)
• Style (highlighted text, etc.)
• Entities (persons, places, concepts, etc.)
• Syntax
• Morphology
• Language
Customized annotation layers can easily be added to this list by the user.
The substantial benefits of flexible, multidimensional annotation hierarchies
in a DSE will be explained in detail in the following section.
4 Hildegraph: TEI without Hierarchies
In March 2020, a project based on the idea of using TEI semantics without
the accompanying XML hierarchy was inaugurated under the title The Book
of Letters of Hildegard von Bingen. Genesis – Structure – Composition.7
4.1 The Sources
The transmission history of Hildegard von Bingen’s (1098–1179) letters has
taken many twists and turns. Within this complex and convoluted story, the
so-called Riesen-Codex [’giant codex’]8 – a book of letters (Liber epistolarum)
which consists of brief epistolary texts arranged to form a cohesive theolo-
gical whole (see Figure 4 – the beginning of each letter is marked with larger
characters and red ink) – assumes a particularly prominent position. The
reason for this can be explained by two separate, albeit closely related, aspects
of its reception history: first, both medieval and modern audiences are un-
animous in their verdict that the Liber epistolarum is of equal importance to
Hildegard’s works of visionary theology; second, the Riesen-Codex can lay
claim to the special status of a last hand edition, as it was compiled by Hilde-
gard’s staff from the entirety of her correspondence during her own lifetime
and in accordance with her wishes.
7
The project is funded by the Deutsche Forschungsgemeinschaft (DFG) https://gepris.
dfg.de/gepris/projekt/429863245?language=en
8
https://tudigit.ulb.tu-darmstadt.de/show/Hild_R_Riesencodex
107
Figure 4: Fol. 341r of the Liber epistolarum Wiesbaden, Hochschul- und Landes-
bibliothek RheinMain (ehemals: Wiesbaden, HessischeLandesbibliothek) Hs 2
(„Riesenkodex“) urn:nbn:de:hebis:43-972.
108
Our project is the first to present the Liber epistolarum in the form of a
digital scholarly edition. As opposed to the existing critical edition of Hilde-
gard’s letters (van Acker and Klaes-Hachmöller, 1993-2001), which seeks
to reconstruct ’the correspondence that actually took place’ while combin-
ing different stages of transmission, our focus lies on the final authorized
form that Hildegard’s letters assumed during her lifetime. Moreover, the
individual letters found in the Liber epistolarum are not treated as mere his-
torical witnesses, but rather as constituent parts of a deliberate and highly
sophisticated theological-cum-literary composition.
Our edition of the Liber epistolarum is designed to be as media neutral as
possible, allowing parts of it to be printed in book form. The changes that
the text underwent over time can be traced by means of a graph model, in
which the genesis of the individual letters – from the oldest known version
to the form that appears in the Liber epistolarum – is modeled on the basis
of the pertinent manuscripts. By way of example, Figure 5 shows the inter-
dependencies of the various versions of letter #52 found in manuscripts Z,
W, M, Wr, and R.
While information concerning the evolution of the Liber epistolarum over
time is stored in a graph model, the texts of the letters themselves will be tran-
scribed in a standoff property editor with the project name hildegraph.9 For
our purposes, standoff property (SPO) means that the texts are annotated
on an index base, whereas TEI-based XML markup is mainly inline. The
technical outline of SPO is explained in detail in (Kuczera and Neill, 2019).
The project began in April 2020 with a critical transcription of the text of
the Riesen-Codex. As hildegraph was not yet operational at that point, the
task was initially undertaken using an adapted version of the Leiden Conven-
tions,10 a system that employs various types and combinations of brackets to
express textual phenomena in plain text. Currently, we are working on the
transfer of these transcriptions into the hildegraph environment with the aid
of TEI semantics.
As noted above, our DSE uses TEI semantics without XML hierarchies
– in hildegraph, multiple annotation hierarchies can coexist in one system.
Table 1 shows a preliminary list of annotation types based on TEI semantics.
Here it is important to keep in mind that an annotation can be assigned to
multiple semantic spaces – Hildegraph is capable of managing several index-
ing systems at once. For example, the first line in Table 1 shows that text
between lines can be identified both by Leiden annotation leiden/supralin-
9
hildegraph is derived from the Codex system described in (Kuczera and Neill, 2019)
https://www.hildegraph.org/
10
https://en.wikipedia.org/wiki/Leiden_Conventions
109
Figure 5: The Liber epistolarum as a theological-cum-literary composition.
IS_FOLLOWED_BY edges connect letters, represented by nodes to the ones that follow in
the manuscript, IS_RELATED_TO edges connect letters to the respective reply forming a
pair of letters, and IS_COMPARABLE_WITH edges connect letters across various manuscripts
whose wording or style is very similar or identical) (Kuczera).
eam and by TEI annotation . This allows us to use dif-
ferent annotation layers as and when they are required, even if they violate
the hierarchical structures of XML – a flexibility that does not compromise
machine-readability in any way.
4.2 Do We Need Containment?
As the following example demonstrates, the process of translating annota-
tions based on the Leiden Conventions into the SPO format by means of
TEI semantics is not without its challenges. Figure 6 shows the end of one
letter and the beginning of another:
This is the transcription of the corresponding passage according to the
Leiden Conventions (transcription by Sr. Maura Zatony):
... neq(ue) odiu(m) alicui(us) p(er)sonę adtendemus! sed |
solius iusticię respectu equitate(m) iudicare |
proponimus.
110
Explanation Type Description TEI Coding
supra between eam: orange text
margin note leiden / mar-
to text text
leiden /
recensi additional
ZPA
start and
leiden / column:
end of text column
EOC “//”
column a-b
leiden / correc-
visible
corr. text tion: red under-
correction
line
original
spelling corrected and leiden / sic:
interpr.
(transcrip- to/sic! green underline
tion)
in rasura
been erased)
ition: pink un-
other line
derline
erased text through line
rubricated leiden / em-
letters) red
resolution � leiden / expan-
of abbrevi- interpr. expansion �� sion: styled in
ations blue
empty space white space
start of line text line : EOL “/”
Table 1: List of annotation types
111
Figure 6: Part of fol. 341r with rubricated text
\#52\# [ru[friderico imp(er)atori hildeg(ardis).]ru] |
[ru[A]ru] summo iudice. hęc uerba diriguntur |
ad te. Ualde admirabile est q(uo)d hanc ||
p(er)sona(m) homo habet necessaria(m)! scilicet quę |
tu rex es. Audi. Quida(m) uir stabat in excel
The manuscript’s red, or rubricated, characters and the capitalized ‘A’ are
a signal to the reader that a new letter is about to begin. In the transcrip-
tion, these parts of the text are represented by square brackets and the siglum
ru: [ru[A]ru] (for Rubrum), whereas the characters in round brackets spell
out the abbreviations used by the original scribes. As this system of annota-
tion unequivocally marks which start element belongs to which end element,
overlapping markup is possible.
But what is the best way to represent rubricated text by means of TEI ele-
ments? Which of the several options provided by TEI is the most promising?
In an effort to find an answer to this question, we reached out to two TEI
experts.
One suggestion was to use the element11 to highlight “words or
phrases which are stressed or emphasized for linguistic or rhetorical effect,”12
while the attribute could be employed to convey the information
that the text’s color is red. Here is what this approach would look like:
friderico imp(er)atori hildeg(ardis)
11
https://tei-c.org/release/doc/tei-p5-doc/en/html/ref-emph.html
12
The rhetorical aspect reminds me of Zundert’s idea of a computational edition with
performative texts (van Zundert, 2019).
112
The other expert proposed to use the element13 to mark “a word or
phrase as graphically distinct from the surrounding text, for reasons concern-
ing which no claim is made,” a solution that would look like this:
friderico imp(er)atori hildeg(ardis)
The element appeared to be a fitting choice to mark a section of text
that had been highlighted for a specific purpose – but given that the red
characters were graphically distinct from the surrounding text, a strong case
could also be made for the element. Clearly, the rubricated text ful-
filled at least two different roles: in the context of the overall layout of the
page, the red characters mark the beginning of a new letter and thus serve a
rhetorical and structural function, yet they also identify the sender and re-
cipient of the letter in question. What, then, if we employed both elements
to represent the distinctive red ink? Which element should come first and
contain the other? And does this kind of containment even make sense?
In long discussions with various colleagues, no convincing arguments in
support of the need for containment were put forward. There is simply no
plausible need for it when it comes to accommodating different annotation
layers like layout or rhetoric: as our Hildegraph environment attests, all of
these layers can be combined in various ways without the application of hier-
archies.
4.3 “So what’s the text, then?”
The brief transcription from the Liber epistolarum discussed in the previous
section contains several expansions of scribal abbreviations employed in the
original text. The use of abbreviations in manuscripts was a very common
practice in the Middle Ages and posed few obstacles to contemporary read-
ers. A modern critical DSE, on the other hand, is expected to provide an
expanded and normalized version of the text for convenience and ease of ref-
erence.
But which version of the text should be displayed in Hildegraph’s plain
text field? As a medievalist, I am inclined to argue that the version of the text
that is as close as possible to the original should be shown in this prominent
location; on the other hand, the expanded versions are much easier for casual
users (and also for persons charged with maintaining the database) to read
and understand. In the end, there are good arguments in favor of each of
the two alternatives, and one of the major advantages of using SPO is that
it does not force us to make a choice: as all versions can easily be converted
13
https://tei-c.org/release/doc/tei-p5-doc/en/html/ref-hi.html
113
into one another, there is simply no need to decide once and for all whether
the plain text to be indexed in SPO is the original or the normalized version
– this decision can be made according to the specific requirements of the
individual use case.
5 Digital Scholarly Editions as Provenance Knowledge
Graphs
5.1 What is a Knowledge Graph?
If we continue along this line of thought, the whole DSE can be conceptual-
ized as a provenance knowledge graph, in which every piece of information is
stored together with information on where it comes from, who made which
statement and when, etc.
Broader scholarly interest in knowledge graphs began to arise when
Google discussed their own approach to the issue in a blog post, which es-
sentially described an enhancement of their search engine through semantics
without going into the technical details (Amit Singhal, 2012). Since then, a
fair amount of research has been carried out in this area, notwithstanding the
absence of a universally accepted definition of what constitutes a knowledge
graph (Ehrlicher and Wöß, 2016).
At times, the term has simply been used as a synonym for ontology. Ac-
cording to Paulheim (2016),
[a] knowledge graph (i) mainly describes real world entities and their
interrelations, organized in a graph, (ii) defines possible classes and rela-
tions of entities in a schema, (iii) allows for potentially interrelating ar-
bitrary entities with each other and (iv) covers various topical domains.
For Ehrlicher and Wöß (2016),
[k]nowledge graphs are large networks of entities, their semantic types,
properties, and relationships between entities,
whereas Pujara et al. (2013) point out that there are systems that
[u]se a variety of techniques to extract new knowledge, in the form of
facts, from the web. These facts are interrelated, and hence, recently this
extracted knowledge has been referred to as a knowledge graph.
Another common definition14 is that a knowledge graph represents a collec-
tion of interlinked descriptions of entities (real-world objects, events, situ-
14
See, for example, https://www.ontotext.com/knowledgehub/fundamentals/
what-is-a-knowledge-graph.
114
ations, or abstract concepts), while other scholars use the term to refer to
any knowledge base modeled as a graph.
As if this confusion was not enough, none of these definitions say any-
thing about the technical specifications of a knowledge graph: some expli-
citly mention RDF (Resource Description Framework) (Färber et al., 2016)
and some suggest node properties (Ehrlicher and Wöß, 2016), but as of yet,
no clear picture as to possible technical backgrounds of knowledge graph
systems has emerged.
5.2 The Provenance of a Statement
The various concepts of knowledge graphs discussed in the previous section
do have one thing in common: they treat information as objective truth. But
in the field of the (digital) humanities, the ‘truth’ is always a matter of in-
terpretation. The interpretative process begins the moment the very first
characters of a text are transcribed. Each of the editor’s decisions is open to
discussion and constitutes a subjective statement – and that is precisely the
point where provenance comes into play. Once we begin to model a DSE as a
knowledge graph that includes comprehensive provenance information, we
end up with a huge amount of statements. Expressing all of this information
in RDF would produce a huge and completely unmanageable graph, which
is why we have opted to use labeled property graphs (LPGs) in our DSE.
5.3 LPG vs. RDF
RDF is a W3C standard for data exchange in the web that represents data
as a graph, and this is the most important point of commonality it shares
with LPGs. RDF structures information in triples in the form of subject-
predicate-object, with the subject, predicate, and object being identified by
Uniform Resource Identifiers (URI) (Barrasa, 2016).
The statement that Emperor Frederick Barbarossa was a human being
would look like this:
(Emperor Frederick Barbarossa)-(INSTANCE_OF)-(human)
Here is the same statement translated into URIs:
(https://www.wikidata.org/wiki/Q79789)
(https://www.wikidata.org/wiki/Property:P31)
(https://www.wikidata.org/wiki/Q5)
Adding his place of death – Weingarten – would involve another triple:
115
(https://www.wikidata.org/wiki/Q79789)
(https://www.wikidata.org/wiki/Property:P19)
(https://www.wikidata.org/wiki/Q572427)
In principle, RDF understands the world as a network of connected en-
tities and literals. Its popularity surged with the rise of the Semantic Web15 ,
which operates on the basic idea that users should publish data in structured
formats with well defined semantics so that this data can be ‘understood’ by
machines. Originally, this structured information was to be contained in
RDF triple stores16 , a vision that soon evolved to quad stores which added
a named graph to each RDF triple. Today, the product of this evolution is
commonly referred to as “semantic graph database” (Barrasa, 2016).
In LPGs, each node and edge not only has a unique and distinctive ID, but
also a set of key-value pairs (or properties) that characterize it. Our example
of Emperor Frederick Barbarossa and his place of death could be expressed
like this:
(e:Entity{type:'human', wikidataId:'Q79789'})
-[r:PLACE_OF_DEATH {wikidataId:'P19'}]->
(p:Place {label:'Weingarten', wikidataId:'Q572427');
When comparing RDF triples with an LPG, it is important to keep in
mind that in the latter, nodes and relationships have an internal structure.
In RDF, on the other hand, a triple is composed of two nodes connected by
an edge (subject-predicate-object); the subject and the relationship are each
identified by a URI, and the object can be another node or a literal, so that
neither nodes nor relationships have an internal structure – they are merely
unique labels. It is evident from this that an RDF graph could easily reach
ten times the size of an LPG containing the same amount of information.
Another important difference is that RDF does not uniquely identify in-
stances of relationships of the same type, nor does it allow instances of rela-
tionships to be qualified. In an LPG, the information is stored in the graph
structure and in the internal structure of nodes and relationships. In RDF,
all of this must be expressed in simple RDF triples.
In light of this, Hildegraph uses an LPG to store all of the information
contained in the DSE as a statement, which allows us to explore and com-
pare diverse (and potentially competing) interpretations. The provenance
information – who made what statement when and where – is stored in the
properties. Here, the versioning of graphs as discussed in Martina Bürger-
meister’s contribution to this volume plays an important role.
15
https://www.scientificamerican.com/article/the-semantic-web/
16
https://en.wikipedia.org/wiki/Triplestore
116
5.4 Manuscript Structures in the Graph
The physical structure of the manuscript (and its relationship to its digital
descendants) can also be modeled as a graph. In Figure 7, the main manu-
script R is represented by the image in the upper part of the picture. This
node is then connected to the folio nodes, which correspond to the indi-
vidual folios that make up the manuscript, and which are connected by
IS_FOLLOWED_BY edges that model the order of the folios within the manuscript.
This part of the graph – or in other words, this subgraph – contains the in-
formation about the physical structure of the manuscript. One example of
the usefulness of this information is a manuscript in which the order of the
folios has been changed at some point – in a graph, both the original order
and the new order can easily be modeled.
Figure 7: Physical structure of the manuscript as represented by the graph
5.5 Transcription as Connected Parts of Text
A TEI/XML-based transcription aims at expressing the layout structure
of a manuscript with inline markup in one XML document. In Hilde-
graph, every distinct unit of text is assigned its own SPO node. The re-
117
lationships between the different text blocks are represented by means of
IS_NEIGHBOUR_OF edges, which encode the visual impression of vicin-
ity in the graph. In addition, the individual passages of text are linked to a
corresponding image of the folio in question.
Figure 8 shows two lines of text (initium libri Epistolarum et orationum
Sanctae Hildegardis) added by a later hand in the upper margin of fol. 328r.
Figure 8: Addendum by a later hand (fol. 328r.)
With XML/TEI, this text would be contained in the main body of
the letter in the XML document. In Hildegraph, the added text re-
ceives its own SPO node, and the two SPO nodes are connected with an
IS_NEIGHBOR_OF edge (Figure 11). While textual information is thus
stored separately from its visual arrangement on the folio page with all the
benefits such an approach entails, the combination of text and layout can
easily be examined if and when this is needed. Figure 9 shows the entire data
model of Hildegraph.
Figure 9: Data model for the digital scholarly edition of the Liber epistolarum
118
5.6 Text as a Graph
Given the continuing lack of technical solutions for managing text directly
as a graph (Kuczera, 2016), we developed our own set of standoff proper-
ties (Kuczera and Neill, 2019) based on Desmond Schmidt’s ideas (Schmidt,
2016, 63-69).
Since SPOs are index based, one must select a base text for indexation. In
practice, however, every version of a text can be used as base text because they
can all be converted into one another. Indexing the base text makes every
character of the text addressable – they are strung out like pearls in a long row,
forming a chain of nodes in the graph which is given order by the direction
of the text. All additional information is then connected to these indexed
characters in a process that builds a bridge between the more transcription-
related sphere of the text and the predominantly semantic and interpretative
sphere of the graph. In this regard, Hildegraph goes well beyond Witt’s above
quoted proposition to model text as an ordered hierarchy of content objects
(OHCO).
5.7 Transcription with Annotations of Annotations
Another SPO is created whenever a user adds an annotation, which can then
be annotated again (most likely by another user) with yet another SPO, and
so on. With standoff properties, every annotation is stored together with a
Globally Unique Identifier (GUID) and can be traced back to the user who
added it (Kuczera and Neill, 2019). From this perspective, annotations can
be seen as a statements by a certain user – as users add these statements to
the base text (which is itself a statement), and as these statements are in turn
annotated by other users, the resulting knowledge graph continues to grow.
Figure 10 shows the subgraph concerned with transcription and interpret-
ation. The manuscript consists of letters from and to Hildegard. These let-
ters are assigned one SPO node each, which are connected with IS_PART_OF
edges to the corresponding folio nodes. A letter can belong to one or
more folio pages, and may have a predecessor or a successor connected with
IS_FOLLOWED_BY edges (See Figure 9). The red, blue, and green circles on the
right represent metadata, layout, and semantic content of the letters.
5.8 Annotations as Individual Statements
Figure 11 shows how provenance is stored. Every information is connec-
ted to a node which represents the user who created the statement.17 In
our example, the user Andreas Kuczera has transcribed a margin note. This
17
Using TEI semantics, this information can be stored with ( https://www.tei-c.
org/release/doc/tei-p5-doc/en/html/ref-resp.html, and .
119
Figure 10: Transcriptions with annotations, entities, described by other text nodes
and metadata.
Figure 11: Every annotation can be traced to the user
120
transcription is not stored in the SPO node of the corresponding letter, but
rather in a separate SPO node which is then connected with an IS_NEIGHBOUR_OF
edge to a zero point annotation in the letter text – it is this separate storage of
transcription and allocation that makes the modeling of multiple interpret-
ations possible.
6 Conclusion
By way of conclusion, I would like to return to the brief epigraph of my essay:
“To which problem is digitization the solution?” From my point of view, di-
gitization enables researchers to publish their findings with a maximum of
flexibility and transparency. Ideally, hierarchies should only be involved in
this process when they are actually needed, and not because they are forced
upon us by technological limitations. One of the fundamental properties of
research data in the (digital) humanities is that it is highly connected, and I
would argue that scholars should be granted the capacity to store every bit
of information concerning these connections even if, for the time being, a
standard or suitable ontology to express them might still be lacking. From
a technical perspective, graph technologies can provide us with the capabil-
ity to model multiple and multidimensional layers of information. TEI se-
mantics could be another important piece of the puzzle, but their practical
utility is dramatically reduced by the limitations of the XML hierarchies with
which they are currently yoked together. As the Hildegraph environment
shows, there is no reason why the problematic coupling of TEI semantics
and XML should continue.
References
Amit Singhal (2012). Introducing the Knowledge Graph:
Things, Not Strings. https://googleblog.blogspot.com/2012/05/
introducing-knowledge-graph-things-not.html.
Barrasa, J. (2016). RDF Triple Stores vs. Labeled Property
Graphs: What’s the Difference? https://neo4j.com/blog/
rdf-triple-store-vs-labeled-property-graph-difference/.
Bordalejo, B. (2018). Digital Versus Analogue Textual Scholarship or The
Revolution is Just in the Title. Digital Philology: A Journal of Medieval
Cultures, 7(1):7–28, DOI: 10.1353/dph.2018.0001.
Cummings, J. (2018). A World of Difference: Myths and Misconceptions
About the TEI. Digital Scholarship in the Humanities, 34(1):i58–i79,
DOI: 10.1093/llc/fqy071.
121
DeRose, S. J., Durand, D. G., Mylonas, E., and Renear, A. H. (1990). What
Is Text, Really? Journal of Computing in Higher Education, 1(2):3–26,
DOI: 10.1007/BF02941632.
Ehrlicher, L. and Wöß, W. (2016). Towards a Definition of Knowledge
Graphs. In Martin, M., Cuquet, M., and Folmer, E., editors, Joint Proceed-
ings of the Posters and Demos Track of the 12th International Conference
on Semantic Systems - SEMANTiCS2016 and the 1st International Work-
shop on Semantic Change & Evolving Semantics (SuCCESS’16), number
1695 in CEUR Workshop Proceedings. http://ceur-ws.org/Vol-1695/.
Färber, M., Bartscherer, F., Menne, C., and Rettinger, A.
(2016). Linked Data Quality of DBpedia, Freebase, OpenCyc,
Wikidata, and YAGO. http://www.semantic-web-journal.net/content/
linked-data-quality-dbpedia-freebase-opencyc-wikidata-and-yago-0.
Kuczera, A. (2016). Digital Editions Beyond XML – Graph-Based Di-
gital Editions. In Düring, M., Jatowt, A., Preiser-Kappeller, J., and van
Den Bosch, A., editors, Proceedings of the 3rd HistoInformatics Workshop
on Computational History, number 1632 in CEUR Workshop Proceed-
ings, pages 37–46. http://ceur-ws.org/Vol-1632/.
Kuczera, A. and Kasper, D. (2019). Modellierung von Zweifel – Vorbild TEI
im Graphen. In Kuczera, A., Wübbena, T., and Kollatz, T., editors, Die
Modellierung des Zweifels – Schlüsselideen und -konzepte zur graphbasier-
ten Modellierung von Unsicherheiten, volume 4 Special Issue of Zeitschrift
für digitale Geisteswissenschaften. DOI: 10.17175/SB004_003.
Kuczera, A. and Neill, I. (2019). The Codex – An Atlas of Relations. In
Kuczera, A., Wübbena, T., and Kollatz, T., editors, Die Modellierung
des Zweifels – Schlüsselideen und -konzepte zur graphbasierten Modellier-
ung von Unsicherheiten, volume 4 Special Issue of Zeitschrift für digitale
Geisteswissenschaften. DOI: 10.17175/sb004_008.
Luhmann, N. (1987). Archimedes und wir : Interviews. Number 143 in
Internationaler Merve-Diskurs. Merve, Berlin.
Nassehi, A. (2019). Muster: Theorie der digitalen Gesellschaft. C.H.Beck,
München, 3rd edition.
Paulheim, H. (2016). Knowledge Graph Refinement: A Survey of Ap-
proaches and Evaluation Methods. Semantic Web, 8(3):489–508, DOI:
10.3233/SW-160218.
122
Pujara, J., Miao, H., Getoor, L., and Cohen, W. (2013). Knowledge Graph
Identification. In Hutchison, D., Kanade, T., Kittler, J., Kleinberg, J. M.,
et al., editors, Advanced Information Systems Engineering, number 7908
in Lecture Notes in Computer Science, pages 542–557. Springer, Ber-
lin/Heidelberg, DOI: 10.1007/978-3-642-41335-3_34.
Rübsamen, D. and Kuczera, A. (2006). Verborgen, vergessen, verloren?
Perspektiven der Quellenerschließung durch die digitalen ’Regesta Im-
perii’. In Hering, R., Sarnowsky, J., Schäfer, C., and Schäfer, U., editors,
Forschung in der digitalen Welt. Sicherung, Erschließung und Aufbereit-
ung von Wissensbeständen, number 20 in Veröffentlichungen aus dem
Staatsarchiv der Freien und Hansestadt Hamburg, pages 109–124. Ham-
burg University Press, DOI: 10.15460/HUP.STAHH.20.77.
Sahle, P. and Vogeler, G. (2013). Digital Monumenta Germaniae Historica
(dMGH). Digital Philology: A Journal of Medieval Cultures, 2(1):135–
139, DOI: 10.1353/dph.2013.0006.
Schmidt, D. A. (2016). Using Standoff Properties for Marking-up Historical
Documents in the Humanities. it - Information Technology, 58(2):63–69,
DOI: 10.1515/itit-2015-0030.
Schulz, J. (2017). A review Of: Regesta Imperii Online, Ed. By Deutsche
Kommission für die Bearbeitung der Regesta Imperii e.V., 2001-2017.
http://www.regesta-imperii.de/. RIDE, 6, DOI: 10.18716/RIDE.A.6.5.
van Acker, L. and Klaes-Hachmöller, M. (1993-2001). Epistolarivm.
[Hildergard von Bingen]. Brepols, Turnholti.
van Zundert, J. (2016). Barely Beyond the Book? In Driscoll, M. J. and
Pierazzo, E., editors, Digital Scholarly Editing: Theories and Practices,
pages 83–106. Open Book Publishers, DOI: 10.11647/OBP.0095.05.
van Zundert, J. (2019). Why the Compact Disc Was Not a Revolution And
«Cityfish» Will Change Textual Scholarship, or What Is a Computational
Edition? Ecdotica, 15:129–156, https://pure.knaw.nl/portal/en/publications/
why-the-compact-disc-was-not-a-revolution-and-cityfish-will-chang.
Witt, J. C. (2018). Digital Scholarly Editions and API Consuming Ap-
plications. In Bleier, R., Bürgermeister, M., Klug, H. W., Neuber,
F., et al., editors, Digital Scholarly Editions as Interfaces, volume 12 of
Schriften des Instituts für Dokumentologie und Editorik, pages 219–247.
BoD, Norderstedt, http://nbn-resolving.de/urn:nbn:de:hbz:38-91182.
123