Authoring Assistance in Technical Communication Authoring Assistance in Technical Communication...
Transcript of Authoring Assistance in Technical Communication Authoring Assistance in Technical Communication...
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Authoring Assistance in
Technical Communication
White Paper
Version: V4.0 09.09.2013 Created by: Mareike von der Stück Pages: 2
Authoring Assistance On Everyone's Lips Where standardization of formulations was previously preached to increase 100% matches in translations and thus reduce the cost of translations, a new trend is rapidly gaining a foothold – Authoring Assistance. What is "authoring assistance" and what objectives can you achieve with "authoring assistance"?
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Gender note
The use of the masculine or feminine is intended to simplify readability and always means
the other gender as well as long as nothing to the contrary is expressly stated.
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Content
1 What is "Authoring Assistance"? .......................................................................... 4
2 Implementation of authoring assistance .............................................................. 6
2.1 System-independent authoring assistance ............................................................... 6
2.2 Variants of authoring assistance software ................................................................. 7
2.3 Methods for determining sentences to be suggested ............................................... 9
3 Summary ................................................................................................................ 11
4 Sources ................................................................................................................... 12
Authoring Assistance in Technical Communication What is "Authoring Assistance"?
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1 What is "Authoring Assistance"?
Definitions
The term "authoring assistance" has established itself in technical communication primarily
for software that assists the user with selection of the desired sentences and words. This
assistance can be provided just-in-time, i.e., while writing, or in a step that follows the written
text yet still applies to it.
We want to understand authoring assistance in terms of information that is useful for an
author at work – this includes, e.g. an authoring guideline or naming rules. This information
can be printed out on paper, provided as online help, Wiki or be deployed in other forms.
Authoring assistance in its general form is not as new as the current German neologism
would have you believe. However, the question arises as to whether this general form of
authoring assistance has been rendered out-of-date by developments in the field of software.
Text quality in the eyes of authoring assistance
In terms of authoring assistance it is not the phrases and words which are the most beautiful
or the most pleasant for the user that have the highest quality. Rather, quality as understood
in terms of authoring assistance means standardized and economical preparation and
possibly automated processing afterwards (through translation) of texts. The most
economical / rational formulation is supported.
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What is the promise of authoring systems software?
The premise underlying authoring assistance software is simple: With traditional authoring
assistance based on an authoring guideline, the user must generate the input and, through
use of formulation rules, always describe the same subject matter in the same way. Small
differences such as changing the position of a word in a sentence already affects the cost of
translation. Authoring assistance software offers a tempting alternative: the user can save
the time that it takes to formulate a sentence according to the writing rules; instead, on the
basis of a sentence or sentence fragment entered, the software searches for a suitable
sentence in the existing inventory of text for the user. By accessing existing data, it should
be possible
To reduce translation costs by increasing the number of 100% matches,
To generate text faster,
To ensure consistency in the source language.
Objective of the white paper
The following text compares the characteristics of different authoring assistance approaches
and evaluates their usefulness in terms of translation costs and consistency in the source
language. How much faster text is generated depends on how a specific authoring
assistance approach is implemented and this question cannot be given a general answer
here.
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2 Implementation of authoring assistance
2.1 System-independent authoring assistance
An authoring guideline or naming rules can be called system-independent authoring
assistance, for instance. An editorial guideline documents the appropriate formulation and
writing rules for editing. The inventory of text data is analyzed and suitable rules are selected
(e.g., systematically through use of functional design®). A good set of formulation and writing
rules is readily recognized and easy to apply, offers sufficient depth of control to avoid
formulation variants and flexible enough to allow even complex editorial problems to be
resolved.
Observing the rules is the responsibility of each individual author. For this reason, it makes
sense to incorporate the rules of the authoring guidelines as tightly as possible into the
writing process. This can be accomplished in different ways, e.g., by integrating the
authoring guideline into the writing environment, by using authoring assistance software that
checks whether the rules are observed or by assisting the author to observe the rules.
Fig. 1: System-independent authoring assistance (excerpt from a PDF editorial guideline)
Fig. 2: System-independent authoring assistance (excerpt from an HTML editorial guideline)
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2.2 Variants of authoring assistance software
Authoring assistance as a component of a content management system
As a rule, authoring assistance software that is part of a content management system uses
existing sentences and words as a database. Frequently, the database is limited to data from
texts that have a specified status, e.g., "approved/released".
When there are several users who are working independently, different formulation variants
of sentences having the same meaning can occur in the content management system.
Formulation variants can already be contained in sentences and words that were created
before the use of authoring assistance software was introduced.
This means that the user must not only select from among sentences with similar meanings
("Press the [Esc] button." vs. "Press the [Enter] button."), but also from among sentences
having the same meaning ("Press the [Esc] button." vs. "The [Esc] button must be
pressed."). Each user will make their own selection, and it is not possible to achieve
consistency in the source language.
Fig. 3: Authoring assistance as a component of a content management system (Example: SCHEMA ST4 Authoring Assistance)
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Authoring assistance as a component of a translation memory system
Authoring assistance that is incorporated into a translation memory system uses the source-
language part of the segment datasets as the database. In this way, only sentences that
have already been translated are used for comparison, not all sentences ever written. This
type of authoring assistance is targeted specifically at reducing translation costs.
Formulation variants having the same meaning can arise from texts that were translated
considerably after they were first written. Any number of formulation variants can occur over
this period of time. In addition, the author can consider which formulation variant has already
been translated into which language when making a decision as to the most suitable
sentence to select ("DE: Taste [Esc] drücken. "FR: appuyez sur la touche [Esc]", "DE:
Drücken Sie die Taste [Esc]. EN: Press the [Esc] button."). How do users reach a decision
when they do not know the language into which their text will be translated? The decision
becomes a game of roulette. There is no way to ensure that the author makes the most
economical selection.
Moreover, a translation memory system, like a content management system, is seldom
empty when starting to work with authoring assistance software, but rather is already filled to
a great extent with a certain inventory of text data. Existing formulation variants for
sentences having the same meaning must also be assumed to exist.
Fig. 4: Authoring assistance as a component of a translation memory system (Example: crossAuthor)
Authoring assistance as a component of a controlled language checker
In controlled language checkers, authoring assistance software does not access an existing
database without filtering. There are two ways of generating a database here:
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Manual creation of the desired formulations.
Analysis of a given database (CMS data, TMS data, word processing documents, …) on
the basis of the style rules used by the controlled language checker, automatic grouping
of formulation variants having the same meaning, manual specification of the preferred
formulation.
In this way, authoring assistance software prevents the presentation of several formulation
variants to the user and the continued existence of old or out-of-date formulations. What is
needed here is a set of rules that contains the desired formulation and writing rules. This
once again creates a link to the authoring guideline as a form of system-independent
authoring assistance.
Fig. 5: Authoring assistance as a component of a controlled language checker (Example: acrolinx IQ™)
2.3 Methods for determining sentences to be suggested
Determining sentences to be suggested through use of fuzzy matching
With fuzzy matching, two character strings are compared for formal similarity. When this
method is used, e.g., the two sentences "Press the [Esc] button." and "Press the [Alt]
button." are assigned a high relevance (= formally very similar). In contrast, the two
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sentences "Press the [Esc] button." and "Press [Esc]." are assigned a low relevance or no
relevance at all (= formally little similarity).
Thus, authoring assistance software that employs this method does not find formulation
variants or it finds those with lower relevance.
Determining sentences to be suggested for use of linguistic matching
With linguistic matching, two character strings are compared for similarity in meaning. When
this method is used, e.g., the two sentences " Press the [Esc] button to exit the dialog." and
"To exit the dialog, press the [Esc] button." are recognized as having the same meaning. The
sentences "Turn on the stove." and "Turn off the stove.", on the other hand, are recognized
as opposites.
Authoring assistance software that employs this method finds formulation variants and
recognizes differences in meaning.
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3 Summary
Authoring assistance software alone neither improves the consistency of the resulting text
nor reduces its translation costs.
This is true especially of authoring assistance software that accesses databases in content
management or translation memory systems without filtering.
Specification of formulation and writing rules is a basic prerequisite for using authoring
assistance software as part of a controlled language checker.
With the aid of an authoring guideline, you develop the appropriate formulation and
writing rules for your editorial work. You can employ this authoring guideline
independently of any tool.
Furthermore, you can use the authoring guideline as the basis if you decide to use authoring
assistance software as a tool to ensure quality. You can only ensure the quality that you
have defined – in an authoring guideline.
Maintain your authoring guideline and keep the formulation and writing rules in it up to date.
It is only in this way that you can ensure the formulation of sentences that you can re-use
appropriately and consistently also in the future.
Authoring Assistance in Technical Communication Sources
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4 Sources
Literature
Ališić, E.: „Der rote Faden im System“. In technische kommunikation, Vol. 31, Issue 4/2009,
p. 33.
Berns, K.: "Vom Translation Memory zum Authoring Memory". In: Produkt Global, Issue
02/2008, pp. 26-28.
Lehmann, S.; Siegel, M.; Collmann, O.: "Intelligente Wiederverwendung statt blinden
Kopierens". 2010. URL:
http://www.acrolinx.de/uploads/documents/whitepapers/de/Whitepaper_DE_IntelligenteWied
erverwendung.pdf. Accessed on 01/20/2012.
Siegel, M.; von der Stück, M.: "Standardisierungskonzepte 2.0: Das Zusammenspiel von
Redaktionsleitfäden und Autorenunterstützung". In: Conference proceedings of the tekom
spring convention 2010, pp. 100-102.
Schäflein-Armbruster, R.: "Ohne Leit kein Freud". In: technische kommunikation, Vol. 30.,
4/2008, p. 25.
von der Stück, M.: "Regeln für mehr Informationsqualität entwickeln und prüfen". 2009. URL:
http://www.schmeling-
consultants.de/fileadmin/user_upload/dokumente/Sprachregeln_ms.pdf. Accessed on
01/20/2012.
Illustrations
Fig. 1: Example of editorial guideline – Schmeling + Consultants
Fig. 2: Example of editorial guideline – Schmeling + Consultants
Fig. 3: http://www.schema.de/images/autorenunterstuetzung_en.png. Accessed on
09/09/2013.
Fig. 4:
http://www.across.net/documentation/onlinehelp/Across_de/Grafik/acrossNews38_2_image0
02.jpg. Accessed on 01/20/2012.
Fig. 5:
http://www.acrolinx.de/uploads/img2011/graphics/Reuse/Acrolinx_IQ_Reuse_plugin.png.
Accessed on 01/19/2012.