Offline personal wiki tool ConnectedText is ideal for college students, researchers, writers, and anyone else who needs the ability to mix freeform text with keywords and structure, or to perform queries and aggregations based on arbitrary criteria. The new version 6 adds long-needed enhancements to content aggregation, display, and searching.
A new version of ConnectedText (the personal or desktop wiki that I use as my main notes database and qualitative data analysis tool) was released last week. The complete list of new features, improvements and other changes is here. I have been using the beta version for some months now but I still haven’t had time to try everything out yet. Nevertheless, here is a list of the new features that I find the most significant from my perspective as an academic researcher and writer.
- Floating windows – now it’s possible to see multiple topics (CT’s word for “document”) in freely positionable windows, while editing another topic. You can also preview the topic you are editing, if you wish.
- Named blocks – effectively a qualitative data analysis feature to mark up passages and gather them in another topic. It expands CT’s abilities as a CAQDAS alternative, although to run it on big projects one would need a powerful computer (but isn’t that the case with most CAQDAS?). I’m still trying to figure out how to make the most of this new feature, but I’m excited about the possibilities.
- Table of Contents pane – acquired some outlining capabilities, as it now works as a two-pane outliner in conjunction with the edit window. One is able to edit headings in the TOC pane and use keyboard shortcuts to move them around, and their associated text will also move with them in the editor pane.
- Outliner pane – one is now able to drop files and folders onto the tree, and save outlines as templates to be used in the edit window. Ctrl+C and Crtl+V shortcuts are now working within the Outliner.
- Ability to disable inclusions (transclusions) for a project (a CT database), which enable faster navigation of complex projects with long daisy-chains of inclusions that require a lot of processing time.
- Navigator – ability to remove nodes (topics) from the Navigator view allows for purposeful analysis of the network relationships between linked topics (by eliminating unimportant links from the picture, to reduce ‘noise’). I also like the new “Back” button, which allows you to backtrack in the network tree if you had wandered too far down into a branch.
- Auto-numbering (legal numbering) of headings in the editor.
- Conversion of imported OPML outline headings into hierarchical bullet-point outline in the editor.
Here is Manfred Kuehn’s selection of his favourite new features in CT v. 6.
Just heard it through the grapevine that the forthcoming version 6 of ConnectedText will be able to have an unlimited number of view-only windows open.This is great news, as up to now the main limitation of ConnectedText was its inability to have more than one topic (document) displayed either in edit or view mode. It was one of the reasons why I needed another software for the actual writing, as it’s inconvenient to have to keep switching back and forth between the topics I’m writing and the ones I need to refer to during writing. Multiple view-windows will solve this problem.
Here is a screenshot of CT 6 with several floating windows open (hat tip Prof. Kuehn):
In an earlier post I have discussed how to set up your desktop layout in ConnectedText, as part of getting started with CT. In this post I will offer a few more tips on setting up CT for general use but also for our intended purpose here as a CAQDAS tool.
One of the things that puts people off from using wikis in general and CT in particular is the need to use (and having to learn) markups. Especially if you have never learnt or used a markup before, it may seem too technical and daunting and even unnecessary in this day and age of icons and touch screens.
The good news is that CT makes it relatively easy to use markups. First, it uses a simplified markup language, so there is no need to learn a huge amount of markups. I only use maybe 4 or 5 markups on a regular basis. CT also reduces the need to type markups in a number of ways.
Second, you can just drag and drop certain items, such as URLs from your browser and file links from your Windows Explorer, rather than having to type the associated markup. Some markup also gets inserted automatically for you if you are starting a list, such as a bulleted or numbered list or a list of comments. Finally, there is also something called “completion proposal,” which means that if you start typing a certain markup, it brings up a pull-down menu of options, and you just click on the markup you need to insert it automatically.
One complaint about having to use markups is that they disrupt the flow of writing or reading in edit mode. As far as the speed of writing is concerned, I think this might be more of an issue of perception stemming from the habit of clicking buttons and selecting menu items in the headers of standard office applications. While it may seem that it is easier or quicker to highlight a piece of text, go to the menu, select a command, and click on it, in reality that also disrupts your flow of writing because you need to take your hand off the keyboard, grab the mouse, move it, click on things, and then move your hand back to the keyboard. If you know the markup, it’s much quicker to just type the markup and achieve the same result, without your hand having to leave the keyboard.
But it is true that the presence of markup in the text itself may disrupt the comprehension of the text you are writing, after all you might be inserting some notation that looks like gibberish (at least until you get used to it, which is another way of dealing with this problem: use it long enough for it to become second nature).
Fortunately CT has a feature that can somewhat alleviate this effect of disruption. If you select custom colours for specific mark-ups, they become more easily recognisable in the text, and your eyes will learn to skip over them and ignore them when you want to concentrate on the content of your writing in edit mode (and of course you can always just switch to view mode, if you don’t want to see any markup at all).
Here is how to select the custom colours for your markup: go to Tools > Options (or hit CTRL+O) > Editor, and you will see a box called “Colors,” as well as a corresponding preview box at the bottom that will show you the colours you have chosen. You can change both the foreground colour (the font colour) and the background colour (which works as highlighting) for your given markup or feature. You will also need to tick the box “Use syntax highlighter” for this to show in the edit mode.
Following on from my previous post on “getting ConnectedText,” here are my suggestions on how to get started with CT if you are brand new to it.
- Download and install the software. (If you have special needs for installing things in a particular folder or if you need to sync files with other computers, read the relevant sections (“Changing user data location” and “Project synchronization tips”) of the Help file first, which is available here [2.9MB], as you may need to do some things differently then. But these are fairly advanced issues. If you are not sure what these are about, just go with the standard installation process.)
- Read (or rather, work through – see point 5) the “First steps” section in the Welcome project (which is CT’s Help file). A ‘project’ is CT’s term for a database, within which ‘topics’ (documents) reside. Keep the Welcome project always open in a tab for easy access. You may even want to load it onto your smartphone or tablet (using a CHM reader app, so you can read it when you are out and about). The Welcome project has over 300 topics, so probably few users read it from “cover to cover,” but it’s there for you to search when you need specific help.
- Sign up to the CT Forum. Search it for issues for which CT’s Welcome project may not have an answer to. If you can’t find an answer, post your question, and you are likely to get a quick reply.
- Note that CT’s main window has two modes: an edit mode for creating content in a topic, and a view mode for viewing the content. Learn how to toggle between them (e.g. type ALT+E or click the Edit button).
- Create a new project (database) file, call it “Test”, and try out the various features as you are learning about them. Make sure to select “Auto Backup” for any new project you create in the Project wizard, otherwise you won’t be able to recover deleted topics. You can download a cheat sheet with the basic mark-up commands here [PDF]. Use the Welcome project to practice on how to navigate an existing fair-sized project.
- Go through all the menu items in the pull-down menus, to learn the main commands. Similarly, check out all the buttons in the toolbar, to become familiar with them. Also check the commands in the right-click context menu, e.g. when you select some text in the topic editor window.
- Read some of the existing tutorials online: Steve Zeoli on some of the basic features of CT and Prof. Manfred Kuehn on the basic mark-ups he uses in CT.
- Develop your preferred desktop configuration for the various panes. Go to “View” pull-down menu and try out the various options. The most important panes for me are the “Table of Contents,” “Topics,” “Categories,” “Outline,” “Notes,” and “Navigator.” As the Navigator allows you to view a map of your topic relationships, it’s best to use it undocked as a standalone window in a separate monitor (using Windows’ Extended Desktop feature). Make sure to save your favourite desktop configuration by going to View > Desktop > Save Desktop. You can save a variety of desktop configurations for different scenarios (such as reading, writing, annotating, outlining etc.).
- Practice docking the panes because it can get tricky and it can happen that you end up in a mess (with panes stuck where they shouldn’t be and there not being an obvious way to return to the previous state). That’s the time to go to your saved desktop and load it.
- If you have already messed up your desktop and need a fresh start (just like I did early on), download this desktop template [ZIP file] from the Forum, courtesy of one of the users. Here are his or her instructions: “Put it into your user settings folder, where you keep CT’s icon folder, dictionary folder etc. The First_Aid.lay should go on the same level where CT stores your bookmarks.xml, fulltext.xml, filters.xml etc. After you put the file there, call it up via View > Desktop > First_Aid.” Below is what the First_Aid desktop layout looks like, once called up. It’s the swiss army knife of CT desktop layouts. You can just close the panes that are not needed.
- My preferred desktop configuration (for the qualitative data analysis that I will discuss in future posts) is the following: view/edit window in the middle, Table of Contents and Outline docked on the left (as tabs in the same pane), and Topic List, Categories, and Notes docked on the right (as tabs in the same pane), with Navigator undocked in a separate monitor. If you don’t have a separate monitor, you can still have it undocked, but you will need to call it up by F7 or clicking on the Navigate button and then close it, otherwise it will cover your main CT window. Alternatively you can dock the Navigator on either the left pane (like in this YouTube video) or the right pane.
- Once you become comfortable with CT’s main features, make sure to install Python on your computer, so you can use some Python plugins that will help your work. Instructions for how to install Python are in the Welcome project. I use three Python scripts (all downloaded from the Forum) on a regular basis: one for doing word count in a topic, and the other two for creating bullet-point and numbered lists. There are also a lot of AutoHotKey scripts on the forum but I don’t use any at the moment. [Update (11/3/13): I do now…]
In my next post I will discuss my work flow regarding qualitative data analysis in CT.
In an earlier post I have outlined my reasons for switching to ConnectedText (CT) from NVivo 8 as my main CAQDAS tool. However, before I get into discussing how I use CT for qualitative data analysis, I need to tackle the delicate issue of “getting” or “not getting” ConnectedText. It is a common complaint by new or prospective users that there is a learning curve associated with CT or that they simply “do not get CT.”
I empathise with these comments because I was also one of these people. I had first encountered CT back in 2007 perhaps, and I ‘trialled’ it several times over the years. I say ‘trialled’ because most of the time I couldn’t get passed the first screen and I gave up on it very quickly. In retrospect I realise that there were a number of reasons why I didn’t get CT back then and why I get it now (at least for my purposes).
Some of the reasons have to do with the profile and the expectations of the prospective user. If you have never used a wiki or mark-up before, if you are not a programmer or blessed with an engineer’s mind, if you have been raised on the common fare of Microsoft Office type applications, if your background is in the humanities or social sciences, then encountering an idiosyncratic tool like CT may prove initially a challenge.
But some of the difficulties arise out of the characteristics of CT and the way it is initially presented to this non-programmer, non-techie type of user. CT’s main strengths are also its main weaknesses when it comes to selling these strengths to the uninitiated. At its heart it is a desktop wiki that is enhanced by a wide array of sophisticated tools that can turn that wiki into any number of specialist solutions (such as CAQDAS in my case).
The problem with ‘just’ being a wiki at its heart is that it makes CT into a highly generalist application, in the sense that a wiki can be whatever you make of it. A desktop wiki after all is your own mini internet or intranet, and as such it can be organised in a myriad different ways, as far as the content and the structure of the output are concerned. Therefore it might be more difficult to “get CT” if you come to it without a specific need to solve a particular information management problem. Just like with the case study method or practice-based learning, it helps to have a real-life problem at hand to which you can apply CT as the solution.
At the same time CT is also packed with some very sophisticated features, such as special ways of connecting the “web pages” (called ‘topics’ in CT), analysing them, visualising them, organising them, enhancing them with various add-ons and scripts etc., etc., which probably can also scare the novice away. At the moment the way information is presented on the website, in the software when it is first launched, and in the Welcome project (which is the Help file, 2.9MB), CT probably appeals to the sophisticated programmer-type audience more, than let’s say the humanities-type person with no experience in using mark-up. When I recommended CT to another PhD colleague of mine with a social science background, he said, “Wow, and I thought learning Scrivener was a challenge!”
For this reason I would like to recommend some strategies for this latter type of prospective users on how to increase the chances of “getting CT” because I think it is well worth the effort (in my experience). I will provide a particular way into CT in my next post. However, in the meantime let me emphasise that if you want to give CT a chance as your main database for your PhD (or any other type of) project and as a qualitative analysis tool, then you will need to become a member of CT’s forum because it is a live extension of CT’s Help file. There are not only some very helpful human beings on there but it is also a depository of existing knowledge, user case studies and Python and AutoHotkey scripts (more about those later).
This is my first post in what hopefully will become a series of posts on how I use ConnectedText (CT) for qualitative data analysis, as part of my Ph.D. project. You may ask: “Why bother using CT, a personal wiki, for qualitative data analysis when there are such long-standing dedicated CAQDAS tools on the market such as Atlas.ti and NVivo?” That is a legitimate question. Some people may indeed find that Atlas.ti or NVivo works better for them. However, based on my personal experience as a PhD student, I found that neither Atlas.ti or NVivo was quite right for me. Finding CT was a revelation, as it allowed me to overcome some problems (more about those later) that I couldn’t solve with NVivo, my CAQDAS of choice prior to CT.
How to select a CAQDAS for your study? Try several if you can. Test them on a pilot project. Take workshops on them. Although here I will be recommending CT as CAQDAS for particular qualitative analysis jobs, I still suggest you use either Atlas.ti or NVivo extensively for a prolonged period of time to learn about how mainstream CAQDAS work.
What was my experience with CAQDAS? I took a couple of workshops in Atlas.ti, got a copy and trialled it repeatedly over the years. As far as I know, Atlas.ti was originally developed to implement grounded theory, and as I wasn’t completely convinced by its implicit research philosophy (which still seemed a bit positivist to me, although otherwise I’m all in favour of grounded theory’s bottom-up approach), I found some of the lingo, the design and the interface off-putting. I discovered that I was a visual learner and found that Atlas.ti wasn’t accommodating my type of learner. I found it difficult to visualise the conceptual linkages between Atlas.ti’s various commands and floating windows.
NVivo 8, on the other hand, immediately appealed to me the first time I laid my eyes on it. I could see how its different tools related to each other. At its heart there was a hierarchical folder structure that worked like many other Windows-based software. It also seemed more neutral from a research philosophy perspective. In the end I spent 6 months analysing my qualitative data in NVivo. I used it to code about half of my data (interviews, participant observations, and a variety of collected documents in a range of media and file formats). I enjoyed doing the coding with it. [The screenshots below are of the example database that comes with NVivo.]
Why did I abandon NVivo? The main reason had to do with the limitations of NVivo’s interface, or rather the way its tools are organised and the way this organisation forces you to follow a particular analytical logic. The underlying issue is the hierarchical organisation of folders and tools, which, ironically, was the reason I chose NVivo over Atlas.ti in the first place. The problem was that different elements of the work get separated into different folders, which can’t be viewed at the same time, thus breaking up the workflow and the analytical reasoning.
After all my coding I ended up with a hierarchical forest of codes (a lot more complex one than the example in the above image) and it was difficult to see how to bring them all together again in order to synthesise them into findings and a coherent answer to my research question. I was stuck and confused, as I also lost my overview of all the data that I had reviewed and stored in there. (In fact, in my desperation I took screenshots of my NVivo codes and pasted them into PowerPoint, and continued the rest of the work outside of NVivo. It helped to cut a Gordian knot but I still ended up needing another CAQDAS solution for the rest of my data).
I also realised that NVivo is a wiki forced into a hierarchical straight-jacket. You are essentially creating links between different documents and then these links are presented to you in a hierarchical organisation. This rekindled my interest in personal wikis again. Since the early days of my PhD I wished that there was a way to create a dashboard for my dissertation project, from which all my files (both data and my analysis and writings) would be linked in the manner of an intranet. I have experimented with Planz, WhizFolders and a range of desktop wikis but none of them were quite right. In fact I also checked out ConnectedText a few times over the years but I never managed to make sense of it. However, my problems with NVivo’s hierarchical structure convinced me to have another go with the wiki format. Fortuitously, there were a series of helpful posts on Outliner Software and on his blog by Steve Zeoli, which finally led me to an epiphany with CT. But more about that in my next post.
There were some other reasons too why I was happy to say good-bye to NVivo (and the same is true for Atlas.ti). One was the enormous price tag and their licensing regime. Although I got a very cheap, subsidised license from my university, it needs to be renewed annually, and after I graduate I may need to shell out some serious money if I want to have continued access to the data in the form it’s organised in NVivo. To me it seems that NVivo and Atlas.ti to some extent cornered the market and are taking advantage of the fact that PhD students are a captive audience, strongly influenced by the preferences of their supervisors, peers and academic tribes. This business attitude I find very unappealing.
Finally, there are the resource requirements of running a software like NVivo. When I installed my first NVivo copy onto my previous computer, a laptop, I wasn’t even able to launch it. It just simply wouldn’t budge and froze my entire machine. I was forced to buy a top-of-the-range PC in order to be able to run it, and even on the new machine it was sluggish. Waiting for files and windows to open for several seconds eventually adds up. Also, as far as I know, all the work in NVivo is saved into a single proprietary file. It is just asking for a lot of faith to put several years worth of data and effort into a single massive file and hope that it will work for 100% of the time forever, that it will never get corrupted etc., etc. I’m not a techie but it seems to me there are some risks associated with that approach.
Still, I’m glad that I had a proper go with NVivo. It was only by spending many months toiling with it that I had learned how CAQDAS work and what the features are that I like and the ones that I would like to have. I was only able to adopt CT as my new CAQDAS tool because I was able to model the processes that I learnt about – or wasn’t allowed to do – in NVivo.
In my next two posts I will introduce the key qualitative data analysis features of CT and I will also provide some tips on how to get started with it, especially if you had never worked with a wiki before.