app/templates/_base/_modals/_manual/01_introduction.html.j2

@@ -1,27 +1,9 @@
 <h3 class="manual-chapter-title">Introduction</h3>
-<h4>Introduction</h4>
 <p>
-  Nopaque is a web application that offers different services and tools to support 
+  nopaque is a web-based digital working environment. It implements a
-  researchers working with image and text-based data. These services are logically 
+  workflow based on the research process in the humanities and supports its
-  connected and build upon each other. They include:
+  users in processing their data in order to subsequently apply digital
+  analysis methods to them. All processes are implemented in a specially
+  provided cloud environment with established open source software. This
+  always ensures that no personal data of the users is disclosed.
 </p>
- <ol style="list-style-type:disc; margin-left:2em; padding-bottom:0;">
-  <li><b>File setup</b>, which converts and merges different data  (e.g., books, letters) 
-  for further processing.</li>
-  <li><b>Image-to-text conversion tools:</b></li>
-    <ol style="list-style-type:circle; margin-left:1em; padding-bottom:0;"><li><b>Optical Character Recognition</b> converts photos and 
-    scans into text data, making them machine-readable.</li>
-    <li><b>Transkribus HTR (Handwritten Text Recognition) Pipeline</b> 
-    also converts images into text data, making them machine-readable.</li>
-    </ol>
-  <li><b>Natural Language Processing</b> extracts information from your text via 
-  computational linguistic data processing (tokenization, lemmatization, part-of-speech 
-  tagging and named-entity recognition.</li>
-  <li><b>Corpus analysis</b> makes use of CQP Query Language to search through text 
-  corpora with the aid of metadata and Natural Language Processing tags.</li>
- </ol>
-
-Nopaque also features a <b>Social Area</b>, where researchers can create a personal profile, connect with other users and share corpora if desired.
-These services can be accessed from the sidebar in nopaque.
-All processes are implemented in a specially provided cloud environment with established open-source software. This always ensures that no personal data of the users is disclosed.
-

app/templates/_base/_modals/_manual/02_getting_started.html.j2

@@ -1,76 +0,0 @@
-<h3 class="manual-chapter-title">Getting Started</h3>
-<h4>Getting Started</h4>
-<br>
-
-<div style="border: 1px solid; padding-left: 20px; margin-right: 400px; margin-bottom: 40px;">
-  <h5>Content</h5>
-  <ol style="list-style-type:disc">
-    <li><a href="#registration-and-login">Registration and login</a></li>
-    <li><a href="#preparing-files">Preparing files for analysis</a></li>
-    <li><a href="#converting-a-pdf-into-text">Converting a PDF into text data</a></li>
-    <li><a href="#extracting-linguistic-data">Extracting linguistic data from text</a></li>
-    <li><a href="#creating-a-corpus">Creating a corpus</a></li>
-    <li><a href="#analyzing-a-corpus">Analyzing a corpus</a></li>
-  </ol>
-</div>
-
-<p></p>
-
-<h5 id="registration-and-login">Registration and login</h5>
-<p>Before you can begin using nopaque, you will need to create a personal user account. 
-Open the menu (three dots) at the top right of the screen and choose “Register.” Enter 
-the required details listed on the registration page (username, password, email address). 
-After verifying your account via the link sent to your email, you can log in.</p>
-<h5 id="preparing-files">Preparing files for analysis</h5>
-<p>A few steps need to be taken before images, scans, or other text data are ready for 
-analysis in nopaque. The SpaCy NLP Pipeline service can only extract linguistic data 
-from texts in plain text (.txt) format. If your text is already in this format, you 
-can skip the next steps and go directly to <b>Extracting linguistic data from text</b>. 
-Otherwise, the next steps assume that you are starting off with image data.</p>
-<p>
-First, all data needs to be converted into PDF format. Using the <b>File Setup</b> service, 
-you can bundle images together – even of different formats – and convert them all into 
-one PDF file. Note that the File Setup service will sort the images based on their file 
-name in ascending order. It is thus recommended to name them accordingly, for example: 
-page-01.png, page-02.jpg, page-03.tiff.
-</p>
-<p>
-After uploading the images and completing the File Setup job, the list of files added 
-can be seen under “Inputs.” Further below, under “Results,” you can find and download 
-the PDF output.</p>
-<h5 id="converting-a-pdf-into-text">Converting a PDF into text data</h5>
-<p>Select an image-to-text conversion tool depending on whether your PDF is primarily 
-composed of handwritten text or printed text. For printed text, select the <b>Tesseract OCR 
-Pipeline</b>. For handwritten text, select the <b>Transkribus HTR Pipeline</b>. Select the desired 
-language model or upload your own. Select the version of Tesseract OCR you want to use 
-and click on submit to start the conversion. When the job is finished, various output 
-files can be seen and downloaded further below, under “Results.” You may want to review 
-the text output for errors and coherence.</p>
-<h5 id="extracting-linguistic-data">Extracting linguistic data from text</h5>
-<p>The <b>SpaCy NLP Pipeline</b> service extracts linguistic information from plain text files 
-(in .txt format). Select the corresponding .txt file, the language model, and the 
-version you want to use. When the job is finished, find and download the files in 
-<b>.json</b> and <b>.vrt</b> format under “Results.”</p>
-<h5 id="creating-a-corpus">Creating a corpus</h5>
-<p>Now, using the files in .vrt format, you can create a corpus. This can be done 
-in the Dashboard or Corpus Analysis under “My Corpora.” Click on “Create corpus” 
-and add a title and description for your corpus. After submitting, navigate down to 
-the “Corpus files” section. Once you have added the desired .vrt files, select “Build” 
-on the corpus page under “Actions.” Now, your corpus is ready for analysis.</p>
-<h5 id="analyzing-a-corpus">Analyzing a corpus</h5>
-<p>Navigate to the corpus you would like to analyze and click on the Analyze button. 
-This will take you to an analysis overview page for your corpus. Here, you can find a 
-visualization of general linguistic information of your corpus, including tokens, 
-sentences, unique words, unique lemmas, unique parts of speech and unique simple parts 
-of speech. You will also find a pie chart of the proportional textual makeup of your 
-corpus and can view the linguistic information for each individual text file. A more 
-detailed visualization of token frequencies with a search option is also on this page.</p>
-<p>From the corpus analysis overview page, you can navigate to other analysis modules: 
-the <b>Query Builder</b> (under <b>Concordance</b>) and the <b>Reader</b>. With the Reader, you can read 
-your corpus texts tokenized with the associated linguistic information. The tokens can 
-be shown as lemmas, parts of speech, words, and can be displayed in different ways: 
-visually as plain text with the option of highlighted entities or as chips.</p>
-<p>The <b>Concordance</b> module allows for more specific, query-oriented text analyses. 
-Here, you can filter out text parameters and structural attributes in different 
-combinations. This is explained in more detail in the Query Builder section of the 
-manual.</p>

app/templates/_base/_modals/_manual/02_registration_and_log_in.html.j2

@@ -0,0 +1,18 @@
+<h3 class="manual-chapter-title">Registration and Log in</h3>
+<div class="row">
+  <div class="col s12 m4">
+    <img alt="Registration and Log in" class="materialboxed responsive-img" src="{{ url_for('static', filename='images/manual/registration-and-log-in.png') }}">
+  </div>
+  <div class="col s12 m8">
+    <p>
+      Before you can start using the web platform, you need to create a user
+      account. This requires only a few details: just a user name, an e-mail
+      address and a password are needed. In order to register yourself, fill out
+      the form on the <a href="{{ url_for('auth.register') }}">registration page</a>. After successful registration, the
+      created account must be verified. To do this, follow the instructions
+      given in the automatically sent e-mail. Afterwards, you can log in as
+      usual with your username/email address and password in the log-in form
+      located next to the registration button.
+    </p>
+  </div>
+</div>

app/templates/_base/_modals/_manual/03_dashboard.html.j2

@@ -1,22 +1,15 @@
 <h3 class="manual-chapter-title">Dashboard</h3>
-<h4>About the dashboard</h4>
-<br>
 <div class="row">
   <div class="col s12 m4">
     <img alt="Dashboard" class="materialboxed responsive-img" src="{{ url_for('static', filename='images/manual/dashboard.png') }}">
   </div>
   <div class="col s12 m8">
     <p>
-      The <a href="{{ url_for('main.dashboard') }}">dashboard</a> provides a central 
+      The <a href="{{ url_for('main.dashboard') }}">dashboard</a> provides a central overview of all resources assigned to the
-      overview of all user-specific resources.
+      user. These are <a href="{{ url_for('main.dashboard', _anchor='corpora') }}">corpora</a> and created <a href="{{ url_for('main.dashboard', _anchor='jobs') }}">jobs</a>. Corpora are freely composable
-      These are <a href="{{ url_for('main.dashboard', _anchor='corpora') }}">corpora</a>, 
+      annotated text collections and jobs are the initiated file processing
-      created <a href="{{ url_for('main.dashboard', _anchor='jobs') }}">jobs</a>, and 
+      procedures. One can search for jobs as well as corpus listings using
-      model <a href="{{ url_for('main.dashboard', _anchor='contributions') }}"">contributions</a>. 
+      the search field displayed above them.
-      A <b>corpus</b> is a freely composable annotated text collection. 
-      A <b>job</b> is an initiated file processing procedure. 
-      A <b>model</b> is a mathematical system for pattern recognition based on data examples that have been processed by AI. One can search for jobs as 
-      well as corpus listings using the search field displayed above them on the dashboard. 
-      Models can be found and edited by clicking on the corresponding service under <b>My Contributions</b>.      
     </p>
   </div>
   <div class="col s12">&nbsp;</div>

app/templates/_base/_modals/_manual/06_services.html.j2

@@ -1,15 +1,13 @@
 <h3 class="manual-chapter-title">Services</h5>
-<h4>Services</h4>
-<br>
 <div class="row">
   <div class="col s12 m4">
     <img alt="Services" class="materialboxed responsive-img" src="{{ url_for('static', filename='images/manual/services.png') }}">
   </div>
   <div class="col s12 m8">
     <p>
-      Nopaque was designed to be modular. Its workflow consists of a sequence 
+      nopaque was designed from the ground up to be modular. This modularity
-      of services that can be applied at different starting and ending points. 
+      means that the offered workflow provides variable entry and exit points,
-      This allows you to proceed with your work flexibly.
+      so that different starting points and goals can be flexibly addressed.
       Each of these modules are implemented in a self-contained service, each of
       which represents a step in the workflow. The services are coordinated in
       such a way that they can be used consecutively. The order can either be

app/templates/_base/_modals/manual.html.j2

@@ -3,7 +3,7 @@
     <h2>Manual</h2>
     <ul class="tabs" id="manual-modal-toc">
       <li class="tab"><a href="#manual-modal-introduction">Introduction</a></li>
-      <li class="tab"><a href="#manual-modal-getting-started">Getting Started</a></li>
+      <li class="tab"><a href="#manual-modal-registration-and-log-in">Registration and Log in</a></li>
       <li class="tab"><a href="#manual-modal-dashboard">Dashboard</a></li>
       <li class="tab"><a href="#manual-modal-services">Services</a></li>
       <li class="tab"><a href="#manual-modal-a-closer-look-at-the-corpus-analysis">A closer look at the Corpus Analysis</a></li>
@@ -15,9 +15,9 @@
       <br>
       {% include "_base/_modals/_manual/01_introduction.html.j2" %}
     </div>
-    <div id="manual-modal-getting-started">
+    <div id="manual-modal-registration-and-log-in">
       <br>
-      {% include "_base/_modals/_manual/02_getting_started.html.j2" %}
+      {% include "_base/_modals/_manual/02_registration_and_log_in.html.j2" %}
     </div>
     <div id="manual-modal-dashboard">
       <br>