Kumu (Kumu.io) is a web-based software for exploring techniques and relationships between actors in a network. It may be used to map associated ideas, associated individuals, or actually anything that may be understood as “elements” and “connections between those elements.” In considered one of my courses final yr, I created an task where my college students used Kumu, a platform created to uncover connections and embrace complexity, to discover totally different sorts of relationships among cultural texts — adaptation, quotation, parody, pastiche, and so forth. The outcome was an enormous, messy, map that describes texts and displays their links by way of Kumu’s dynamic interface, and on this submit, I need to describe how I used this software and how it worked to help my pedagogical objectives for that class.
In a current submit, I wrote about one other device I’ve found useful in managing my class communications, however while many individuals find out about Slack, I discover fewer people who find themselves already acquainted with Kumu.
It was helpful to mirror about Slack while I’m within the midst of figuring it out, however it’s also helpful to assume again to one thing I’ve extra distance from, so in this publish I’m going to talk about that task.
Working with Kumu
1. Creating the Primary Models
Kumu has a extremely flexible structure with a fantastic many choices. I gained’t get into all of these options — and to be trustworthy, I haven’t absolutely explored all the options — however it’s in all probability worthwhile to nail down a number of key concepts. As I mentioned before, there are two elementary models:
- Parts — A node in the map, often represented as a circle.
- Connections — Vectors between nodes, often represented as a line or an arrow.
Each of those parts are created inside the map interface, but the minimal presentation of these two buttons hides secondary modalities for each.
The minimalist interface.
To create a new component, click on on the blue Add Aspect button, which can flip into an edit in place subject the place you sort the label for the brand new component you’re creating. Listed here are two parts:
Two parts in Kumu.
To connect these two parts, I’d choose on one of the parts, which can be indicated with a pink circle, then in the Add Connection field, start typing some… until an inventory of autocomplete strategies drops down, permitting me to pick the label of the factor I need to hook up with.
Now they’re related.
And word, connections might look like a simple, bi-directional line, but actually they do have directionality. The image above exhibits a connection from One thing to One thing Else. Adding a new connection with the reverse process (from Something Else back One thing) creates another line. In the example under, I chosen the “directed” choice to modify on the arrows. (Entry this attribute from the button.)
Two directed connections.
The connection vectors will curve as they need to to be able to maintain these parts related whereas they float across the map area to seek out their natural clusters. If two related parts are “fixed” in place (access this setting with the icon), then the strains between them might be locked into straight strains. Simple “decorations” can be found by way of the icon which helps you to modify the dimensions, colour, and outline of parts, or the width, colour and line sort of connections.
Connections and parts may also be grouped into logical arrangements referred to as “loops”. I haven’t used these but, but I can see the potential. To create a loop, hold shift and click on to pick a number of connections and parts, after which the Add Loop button will under the Add Connection button.
2. Adding Metadata or Organizing Particulars
To date, I’ve been talking about easy methods to work with parts and connections in the map interface, however there’s much more out there in a sidebar that pops out to reveal details about the lively selection: a component or connection.
The sidebar for a component in Kumu.
Discover all the choices here: component sort, description, tags, a picture, and attributes. These fields are also out there for connections, besides you select a “connection type,” and you may’t add a picture to a connection.
The outline lets users write text in paragraphs using Markdown, and it supports a number of kinds of media embedding.
For connections, parts, or loops, the sort is a single selection (an item can solely be assigned a single sort at a time) where you decide from radio buttons of previously-entered sort values or add a new one.
As with many such taxonomies, tags are multiple, repeatable, and rather more unfastened.
Lastly, attributes are user-defined identify/value pairs, the place picture is a pre-defined attribute that allows you to assign a picture (by URL) to seem as the background to a component. Adding an attribute identify in a single aspect makes it out there for all other parts, connections, and loops. Aside from that, I don’t assume attributes do something aside from present further hooks for stylization or filtering.
3. Giving it Type
Finally, it’s potential so as to add type to a connection or factor with the aforementioned “decorate” function (), but I find it simpler to think about fashion as a function of a particular person map’s “perspective.” It’s analogous to how you can, in HTML, either add types on to a component by way of a method=”” attribute, or you possibly can create a separate stylesheet document in your CSS. Kumu’s styling follows a reasonably comparable syntax to plain stylesheets, for those who view it in superior mode. The standard mode is identical factor, just a bit friendlier.
To entry these decorations, you first click off any parts or connections in order that the sidebar exhibits the overall map’s info. Then within the sidebar, toggle from “map” to “perspective.” (It’s slightly confusing, but a single challenge can have a number of maps, and a single map can have multiple views.)
The essential “decorations” editor in this perspective’s sidebar.
These settings make all parts blue and all connections orange. Access a wizard-like interface for both parts or connections with the two buttons in the midst of the sidebar, after which work by means of these steps to filter for the forms of belongings you need to embellish. Like in CSS, you possibly can filter ornament settings for any of the traits I’ve described before: varieties, tags, pictures, and any attributes you’ve created, in addition to variable properties like the variety of incoming connections.
The superior editor appears lots like common previous CSS.
In addition the blue parts and the orange connections, I added a rule that sets all the things a by worth matching znw to have a gray bullseye. All the perspective-specific settings and features obtainable via menus and widgets can be outlined within the Superior views language, and there are a couple of other issues that I feel are solely out there via this interface.
One factor I’ve discovered notably useful for very giant maps like the one we made for this task is the quality worth. Set it to quality: regular, and the map may have all of the floating parts, gracefully-curving connections, and customized background pictures that you simply anticipate. Or set it to quality: quick, and all parts will turn into squares and all connections straight strains. Beneath normal operation, Kumu is fairly resource intensive, putting lots of demand on reminiscence and GPU, and I’ve discovered that some older laptops can solely handle Kumu in high quality: fast mode.
There’s far more to find with Kumu, together with all types of things that I’ve never actually delved into. Fortuitously, they’ve good documentation, and their help has been very responsive once I’ve had a question or drawback.
The Map of Intertextuality
Before I speak concerning the task, I need to present you the thing we produced. I’ll embed it under, however it’s simpler to view it in its personal window. (If that or the embedded version runs too slowly, do this quicker loading perspective of the identical map.) There’s so much right here; it’s an fascinating mess. You possibly can transfer by way of it by clicking on the circles (parts — what we used for describing a selected text) or strains (connections — what we’re using to elucidate the relationships between these texts). When you’re desirous about different views of the map, you should use the tools on the backside to run numerous metrics or find topical patterns like “communities” or any of several options for “clustering”.
As you’ll find in the event you explore it for very lengthy, a few of the descriptions are incomplete or inconsistent, tags aren’t all the time explanatory, and pictures or different embeds may be merely damaged. As I say, it’s a multitude, however it’s fascinating mess: a quivering, tentacular blob of intertextual exploration created by me and the 47 college students that took that class means back in Fall 2014.
This class is a lower-division “topics in literature” course that I name merely “ENGL 252: Adaptation.” It’s meant for non-English majors, however it’s also an elective credit score for the Minor in Digital Studies. My primary aim on this course is to introduce college students to media research by serving to them uncover how totally different media texts interact in an enormous narrative ecosystem. We take a look at important readings by McLuhan, Marie-Laure Ryan, and others, but all the main texts we learn are based mostly on the vector map and comply with themes as they develop there.
We start with a central “triad” of
- Alice’s Adventures in Wonderland (1865)
- Disney’s Alice in Wonderland (1951)
- American McGee’s Alice (2000)
The central triad of main texts.
We learn the e-book, watch the film, play the game, and along the best way we speak about what how issues like cultural context, technical constraints, and medial affordances influence the versions of Alice and the recurring story parts that we discover in all by way of. These three texts are related on the Kumu map, and then college students begin contributing. Using the method I describe above, students find a textual content that has some plausible relationship to one of the texts already on the map, then they create a component for their new text and connect it to the unique factor(s) that it has some connection to.
It behaves type of like a recreation of “Six Degrees of Kevin Bacon.” A connection merely needs to be believable, but I might say a lot of the examples within the map are variations, parodies, translations, or different 1:1-style connections. After some encouragement, we discovered it useful to broaden that to incorporate looser connections like “shares the same director”.
Later, I initiated a second triad round Sherlock Holmes texts, and eventually — after a pair rounds of voting and debate — settled on a third triad around “Sleepy Hollow”.
As a visible doc, our “vector map” demonstrates something that is, on the one hand, fairly intuitive: cultural texts are related and associated to one another in a number of, complicated methods. What I’ve referred to as the “messiness” of our map bears that out. However then again, as I take a look at the the contours of our particular map, I see the ebbs and flows of themes in our class discussions, together with the personalities of certain students and teams of scholars.
For instance, there’s a pronounced anime cluster — scorching pink in our legend — populating the lower-left quadrant of the map, and an orange splash of film operating up the middle. An extended tendril of Harry Potter books, films and video video games arcs up in the the top-left area.
The anime archipelago.
What’s cool about these patterns is that they’re evidence of students finding methods to connect something they care about to different books and media that they wouldn’t have in any other case encountered, and by fascinated by the relationships amongst these texts they know and these texts which might be new, students hopefully get to know their private textual ecosystem a bit of higher.
Lessons Discovered and Future Iterations
I enjoyed the task, and I feel students did too, as soon as they obtained used to Kumu. We got here to Kumu after first making an attempt Scalar, so a few of the sentiment my college students have been expressing was alongside the strains of “better than Scalar.” I should say, I favored Scalar’s flexibility and wealthy metadata, however it was already struggling to scale with the undertaking after 2 rounds of our task, so with a objective of 8 of these rounds, I needed to discover a higher choice.
Originally — approach back in 2012 once I first taught the class — we used a collaborative google drawing, but that too had issues scaling, despite the fact that it did achieve producing something monstrously convoluted.
So of the three platforms, Kumu has undoubtedly labored one of the best for this task, and I’ll in all probability use it once more for this class once I train it once more, almost certainly in Spring 2017. Once I do, I’ll in all probability change a couple of issues like
- Stricter Typing — stronger predefined categories and genres of media varieties like “book,” “film”, “video game,” and broader, better-labeled connection varieties like paratext, adaptation, “shares an actor”, and so forth.
- Managed Attributes — initiating outlined attributes like “Added By” and serving to college students use these persistently.
- Other Assignments that Work with the Map — it’s one factor to understand the complexity of a map, it’s another to elucidate how “At the Mountains of Madness” to the Cam Jansen mystery collection.
Such “traversals” get to the guts of what I’ve find most beneficial about this task, so it might make sense as a midterm or last challenge. Students might use Kumu’s “presentation mode” (something I only discovered lately) to speak about essential factors or loops along the best way from one factor to the subsequent. It may additionally be helpful to create an task or modality where college students must find and add secondary sources that help an analysis of a number of parts within the map. Many things are attainable.
Finally, though Kumu did current some challenges that wanted to be resolved, and students took some time studying methods to use it. And regardless that our remaining product is slightly messy and considerably incomplete and inconsistent, I favored working with Kumu properly enough that I’ve discovered different makes use of for it and I plan to return again to it again once I subsequent revisit this class.
What do you assume? Are you already using Kumu in your courses? In that case, what are it’s strengths and disadvantages? If not, anything you’d wish to find out about my experiences with it?
EDIT TO ADD:
A free Kumu account will get you limitless public tasks, however if you’d like personal tasks, it’s a must to improve to one among their plans, kind of like GitHub. Since public Kumu tasks can have limitless contributors, there was never any drawback utilizing it with my class.