Making transcriptions of records is not as common amongst
genealogists as you might expect, but why is that? What do we need in order to
create useful transcriptions? If we’re part of the minority who do make them
then where should we attach them?
Because of the availability of online data sources, and the
ease with which digital copies can be created (owner permitting of course),
many people believe they do not need full transcriptions of records. They might
claim that since they can visit an online image, or they have a digital scan in
their own data collection, then they can read it perfectly well without having
it typed out. Whether it’s a baptism entry, a newspaper report, or a census
page, many genealogists therefore find they have a growing collection of
equivalent JPEG files sitting on the periphery of their data.
What I mean by this is that such a file can be pointed to,
or referenced, by other data, but it cannot reference anything itself[1] or
be textually searched. This means the information is not truly integrated into
your data. The arguments for adding mark-up to a transcription in order to
achieve this are almost exactly the same ones that I made for using mark-up in authored
narrative at Semantic
Tagging of Historical Data. This allows, for instance, references to
people, places, events, dates, etc., in that transcription to be connected to
the relevant entities in your data.
A transcription requires more though. It also requires a way
of indicating transcription anomalies — parts that deviate from the normal flow
— such as marginalia, footnotes, interlinear/intralinear notes, struck-out
text, and uncertain characters or words. Both the uncertain characters and the
uncertain words may require annotation to provide suggestions and
possibilities, both of which must be honoured during searches. A transcription
also requires an indication of any original emphasis, such as italics or
underlining. NB: the original use of italics, underlining, footnotes, etc., in
something being transcribed is different to their deliberate use in a written
report, and so must use a distinct form of mark-up.
Traditional editorial notations for transcriptions are not
well-suited to digital text as they do not facilitate efficient and accurate
searching. TEI has comprehensive sets of
mark-up for handling transcription issues but falls short when applied to genealogical
data, and probably historical data in general. It is certain that some
specialised mark-up is required, but how you visualise a transcription on-screen
is a separate consideration. The same mark-up could alternatively show
multi-coloured and hyper-linked text, or the plain editorial notation. That
sort of flexibility only comes from using a computerised annotation rather than
human annotation.
The fact that both transcription and authored narrative may
co-exist in the same written report led to STEMMA® unifying them in its own
mark-up. Those distinct usages — for transcriptions and for generating new narrative
(e.g. essays, reports, inference, etc.) — have some similar and markedly
different characteristics as follows:
- Transcription (including transcribed extracts) — requires support for textual anomalies (uncertain characters, marginalia, footnotes, interlinear/intralinear notes), audio anomalies (noises, gestures, pauses), indications of alternative spellings/pronunciation/meanings, indications of different contributors, different styles or emphasis, and semantic mark-up for references to persons, places, groups, animals, events, and dates. The latter semantic mark-up also needs to clearly distinguish objective information (e.g. that a reference is to a person) from subjective information (e.g. a conclusion as to whom that person is).
- Narrative work — requires support for layout and presentation. Descriptive mark-up captures the content and structure in a way that provides visualisation software with the ultimate control over its rendering It needs to be able to generate references to known persons, places, and dates that result in a similar mark-up to that for transcriptions. The difference here is that a textual reference is being generated from the ID of a Person entity, say, as opposed to marking an existing textual reference and possibly linking it to a Person with a given ID. Also needs to be capable of generating reference-note citations and general discursive notes.
As you can imagine, in order to generate a quality
transcription, and to incorporate semantic links and annotation, a very good
software tool is needed. It would be something like a specialised
word-processor tool, but most of us are left using general-purpose
word-processor tools that have none of the required facilities. This will be a
secondary reason why so few transcriptions are made.
So where do I attach transcriptions in my own data? In order
to explain, I first need to convey something of the structure of my data.
This simplified view of the rich connections in the STEMMA
tapestry doesn’t show its places, or groups, or lineage links between people,
or hierarchical/protracted events. That would be too complex! What it does show
is a network of multi-person events and the relationship of sources to those events.
Notice that the sources are attached to the events, and not to the people. As
already explained in Evidence
and where to Stick It, the vast majority of our evidence – if not all of it
– relates to events; things that happened in a particular place at a particular
time. In other words, our entire view of history rests on discrete and
disjointed pockets of evidence describing a finite set of events. Everything
else is inference and interpolation creating as smooth a picture as we can.
So what is the general form of these underlying source
entities in the data? Our real-life sources may be remote, such as a document
in an archive or a book in a library, or local, such as a family letter or a
photograph. In both cases, we may have a digital scan of the items. STEMMA[2]
has two important concepts that it employs for sources:
- Resource – This describes some item in your local data collection, including not just files on your disk, but also physical artefacts or ephemera.
- Citation – Despite the name, this is merely a link to some source of information. A traditional printed citation may be generated from it, but this software entity also incorporates collections, repositories, and even attribution; possibly chaining them together.
Either or both of these may apply,
therefore. A full transcription would be associated with the Resource entity that
would describe any physical or digital edition of the associated material. In
the case where you may have transcribed a document in an archive, or even from
one of the online content providers, the transcription should still be placed
in a Resource entity rather than a Citation entity, even though the latter is
possible.
Genealogist Janice Sellers, in her blog-post at Transcription
Mentioned on Television, explains how transcriptions of documents are
valuable for sharing the details with family and friends. She recounts how she
tried to convince a well-known British TV program to advise their guests to
make transcriptions of their historical documents and heirlooms.
STEMMA’s mark-up is primarily
about semantics. Shallow semantics would
mark an item as, say, a person reference but without forming a conclusion about
who the person was. Deep semantics
involve cross-linking references to persons, places, groups, events, and dates,
to the relevant entities in your data. I have previously tried to convey this using
the worked example of an old family letter at Structured
Narrative.
Genealogist Sue Adams has taken
the concept of semantic mark-up in transcriptions to a deeper level on her Family Folklore Blog.
Her worked examples clearly demonstrate the temporal nature of historical
semantics. Anyone with a passing interest in the Semantic Web and RDF is
encouraged to read about “temporal RDF” and consider why it doesn’t yet exist. You
may find a lot of theoretical work that considers things like temporal graphs but very few real
examples like hers. In an ideal world, the developers of such technology would
be working closely with the people who need to utilise it.
[1] I’m ignoring the
issue of meta-data held within an image until a future post. The issue here is
one of the text in an image making discrete references to its subjects rather
than anything to do with image cataloguing.
[2] STEMMA V2.2 — which includes
important refinements here — has
just been defined but, at the time of writing, I am still preparing to
painstakingly update the Web site. The landing page will indicate when this is
complete.
