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Original author: 
Holly Wilkins


There are many things about this video that will blow you away, firstly this incredible feat of audio-visual amazing-ness is Daniel Sierra’s thesis animation. All of it was created with computer software which he only learnt to use a few months previously. Daniel wanted to “visualise waveform patterns that evolve from the fundamental sine wave to more complex patterns, creating a mesmerising audio-visual experience in which sign and sound work in unison to capture the viewer’s attention.”

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Because the President’s limousine passed almost exactly in front of Dallas clothing manufacturer Abraham Zapruder on Nov. 22, 1963, just as he was playing with his new film camera, and precisely at the moment that Lee Harvey Oswald fired his rifle from a nearby books depository, his silent, 26.6-second home movie has become the focal point of America’s collective memory on that weird day. For many of us, especially those who weren’t alive when it happened, we’re all watching that event through Zapruder’s lens.

Other footage from the scene turns up here and there, becomes fodder for documentaries (like this new one disproving the “second shooter” theory). But Zapruder’s film is still the canonical ur text of John F. Kennedy’s assassination, the most complete and most chilling visual record. In many ways, it prefigured all sorts of American pastimes, from widespread paranoia about government to a loss of faith in photographic truth and the news media, from the acceptance of graphic violence to newer concerns about copyright. Don DeLillo once said that the little film “could probably fuel college courses in a dozen subjects from history to physics.” Without the 486 frames of Kodachrome II 8mm safety film, our understanding of JFK’s assassination would likely be an even greater carnival of conspiracy theories than it already is. Well, maybe.

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This article is about usability evaluation. For application of heuristics to antivirus software, see Heuristic analysis.

A heuristic evaluation is a discount usability inspection method for computer software that helps to identify usability problems in the user interface (UI) design. It specifically involves evaluators examining the interface and judging its compliance with recognized usability principles (the "heuristics"). These evaluation methods are now widely taught and practiced in the New Media sector, where UIs are often designed in a short space of time on a budget that may restrict the amount of money available to provide for other types of interface testing.


The main goal of heuristic evaluations is to identify any problems associated with the design of user interfaces. Usability consultant Jakob Nielsen developed this method on the basis of several years of experience in teaching and consulting about usability engineering.

Heuristic evaluations are one of the most informal methods[1] of usability inspection in the field of human-computer interaction. There are many sets of usability design heuristics; they are not mutually exclusive and cover many of the same aspects of user interface design.

Quite often, usability problems that are discovered are categorized—often on a numeric scale—according to their estimated impact on user performance or acceptance. Often the heuristic evaluation is conducted in the context of use cases (typical user tasks), to provide feedback to the developers on the extent to which the interface is likely to be compatible with the intended users’ needs and preferences.

The simplicity of heuristic evaluation is beneficial at the early stages of design. This usability inspection method does not require user testing which can be burdensome due to the need for users, a place to test them and a payment for their time. Heuristic evaluation requires only one expert, reducing the complexity and expended time for evaluation. Most heuristic evaluations can be accomplished in a matter of days. The time required varies with the size of the artifact, its complexity, the purpose of the review, the nature of the usability issues that arise in the review, and the competence of the reviewers. Using heuristic evaluation prior to user testing will reduce the number and severity of design errors discovered by users. Although heuristic evaluation can uncover many major usability issues in a short period of time, a criticism that is often leveled is that results are highly influenced by the knowledge of the expert reviewer(s). This “one-sided” review repeatedly has different results than performance testing, each type of testing uncovering a different set of problems.

Nielsen's heuristics

Jakob Nielsen's heuristics are probably the most-used usability heuristics for user interface design. Nielsen developed the heuristics based on work together with Rolf Molich in 1990.[1][2] The final set of heuristics that are still used today were released by Nielsen in 1994.[3] The heuristics as published in Nielsen's book Usability Engineering are as follows[4]

Visibility of system status:
The system should always keep users informed about what is going on, through appropriate feedback within reasonable time.

Match between system and the real world:
The system should speak the user's language, with words, phrases and concepts familiar to the user, rather than system-oriented terms. Follow real-world conventions, making information appear in a natural and logical order.

User control and freedom:
Users often choose system functions by mistake and will need a clearly marked "emergency exit" to leave the unwanted state without having to go through an extended dialogue. Support undo and redo.

Consistency and standards:
Users should not have to wonder whether different words, situations, or actions mean the same thing. Follow platform conventions.

Error prevention:
Even better than good error messages is a careful design which prevents a problem from occurring in the first place. Either eliminate error-prone conditions or check for them and present users with a confirmation option before they commit to the action.

Recognition rather than recall:
Minimize the user's memory load by making objects, actions, and options visible. The user should not have to remember information from one part of the dialogue to another. Instructions for use of the system should be visible or easily retrievable whenever appropriate.

Flexibility and efficiency of use:
Accelerators—unseen by the novice user—may often speed up the interaction for the expert user such that the system can cater to both inexperienced and experienced users. Allow users to tailor frequent actions.

Aesthetic and minimalist design:
Dialogues should not contain information which is irrelevant or rarely needed. Every extra unit of information in a dialogue competes with the relevant units of information and diminishes their relative visibility.

Help users recognize, diagnose, and recover from errors:
Error messages should be expressed in plain language (no codes), precisely indicate the problem, and constructively suggest a solution.

Help and documentation:
Even though it is better if the system can be used without documentation, it may be necessary to provide help and documentation. Any such information should be easy to search, focused on the user's task, list concrete steps to be carried out, and not be too large.

Gerhardt-Powals’ cognitive engineering principles

Although Nielsen is considered the expert and field leader in heuristics, Jill Gerhardt-Powals also developed a set of cognitive principles for enhancing computer performance.[5] These heuristics, or principles, are similar to Nielsen’s heuristics but take a more holistic approach to evaluation. Gerhardt Powals’ principles[6] are listed below.

  • Automate unwanted workload:
    • free cognitive resources for high-level tasks.
    • eliminate mental calculations, estimations, comparisons, and unnecessary thinking.
  • Reduce uncertainty:
    • display data in a manner that is clear and obvious.
  • Fuse data:
    • reduce cognitive load by bringing together lower level data into a higher-level summation.
  • Present new information with meaningful aids to interpretation:
    • use a familiar framework, making it easier to absorb.
    • use everyday terms, metaphors, etc.
  • Use names that are conceptually related to function:
    • Context-dependent.
    • Attempt to improve recall and recognition.
    • Group data in consistently meaningful ways to decrease search time.
  • Limit data-driven tasks:
    • Reduce the time spent assimilating raw data.
    • Make appropriate use of color and graphics.
  • Include in the displays only that information needed by the user at a given time.
  • Provide multiple coding of data when appropriate.
  • Practice judicious redundancy.

Weinschenk and Barker classification

Susan Weinschenk and Dean Barker created a categorization of heuristics and guidelines by several major providers into the following twenty types:[7]

1. User Control: heuristics that check whether the user has enough control of the interface.

2. Human Limitations: the design takes into account human limitations, cognitive and sensorial, to avoid overloading them.

3. Modal Integrity: the interface uses the most suitable modality for each task: auditory, visual, or motor/kinesthetic.

4. Accommodation: the design is adequate to fulfill the needs and behaviour of each targeted user group.

5. Linguistic Clarity: the language used to communicate is efficient and adequate to the audience.

6. Aesthetic Integrity: the design is visually attractive and tailored to appeal to the target population.

7. Simplicity: the design will not use unnecessary complexity.

8. Predictability: users will be able to form a mental model of how the system will behave in response to actions.

9. Interpretation: there are codified rules that try to guess the user intentions and anticipate the actions needed.

10. Accuracy: There are no errors, i.e. the result of user actions correspond to their goals.

11. Technical Clarity: the concepts represented in the interface have the highest possible correspondence to the domain they are modeling.

12. Flexibility: the design can be adjusted to the needs and behaviour of each particular user.

13. Fulfillment: the user experience is adequate.

14. Cultural Propriety: user's cultural and social expectations are met.

15. Suitable Tempo: the pace at which users works with the system is adequate.

16. Consistency: different parts of the system have the same style, so that there are no different ways to represent the same information or behavior.

17. User Support: the design will support learning and provide the required assistance to usage.

18. Precision: the steps and results of a task will be what the user wants.

19. Forgiveness: the user will be able to recover to an adequate state after an error.

20.Responsiveness: the interface provides enough feedback information about the system status and the task completion.

See also

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Electronic music making has had several major epochs. There was the rise of the hardware synth, first with modular patch cords and later streamlined into encapsulated controls, in the form of knobs and switches. There was the digital synth, in code and graphical patches. And there was the two-dimensional user interface.

We may be on the cusp of a new age: the three-dimensional paradigm for music making.

AudioGL, a spectacularly-ambitious project by Toronto-based engineer and musician Jonathan Heppner, is one step closer to reality. Three years in the making, the tool is already surprisingly mature. And a crowd-sourced funding campaign promises to bring beta releases as soon as this summer. In the demo video above, you can see an overview of some of its broad capabilities:

  • Synthesis, via modular connections
  • Sample loading
  • The ability to zoom into more conventional 2D sequences, piano roll views, and envelopes/automation
  • Grouping of related nodes
  • Patch sharing
  • Graphical feedback for envelopes and automation, tracked across z-axis wireframes, like circuitry

All of this is presented in a mind-boggling visual display, resembling nothing more than constellations of stars.

Is it just me, or does this make anyone else want to somehow combine modular synthesis with a space strategy sim like Galactic Civilizations? Then again, that might cause some sort of nerd singularity that would tear apart the fabric of the space-time continuum – or at least ensure we never have any normal human relationships again.

Anyway, the vitals:

  • It runs on a lowly Lenovo tablet right now, with integrated graphics.
  • The goal is to make it run on your PC by the end of the year. (Mac users hardly need a better reason to dual boot. Why are you booting into Windows? Because I run a single application that makes it the future.)
  • MIDI and ReWire are onboard, with OSC and VST coming.
  • With crowd funding, you’ll get a Win32/64 release planned by the end of the year, and betas by summer (Windows) or fall/winter (Mac).

I like this quote:

Some things which have influenced the design of AudioGL:
Catia – Dassault Systèmes
AutoCAD – Autodesk
Cubase – Steinberg
Nord Modular – Clavia
The Demoscene

Indeed. And with computer software now reaching a high degree of maturity, such mash-ups could open new worlds.

Learn about the project, and contribute by the 23rd of March via the (excellent) IndieGogo:


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Dr. Luke McMillan, a senior lecturer in game design at Qantm College Brisbane, goes in-depth on undergrad education and explains why seemingly unimportant curricula can be extremely important in hindsight.

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What makes music software popular? Simple recording, DJ, and remix apps unsurprisingly do well. But perhaps as a testament to the importance of individual music expression, some stranger entries do, too. And those less-typical software creations can give you new ways of exploring music creation and performance. Just take Nodal.

GarageBand sits comfortably at the top of the sellers list on Apple’s App Store. But, at least briefly, a generative composition tool has rocketed to second place. Nodal 1.7, available for both Mac and Windows, is unlike most music production tools. In place of linear track arrangement, clusters of graphical nodes represent musical structure, awaiting real-time experimentation. In a network you create, “virtual players” produce patterns by traversing a geometric map defining pitch, rhythm, and sequence.

Nodal and tools like it have always been able to create musical machines from simple elements, letting the user define an arrangement and then set it in motion. But Nodal 1.7 is a major release in that it allows MIDI control, so that you can actually “play” the structure and not just sit back and let it roll.

This isn’t just for ambient music lovers, either – sync features mean you can use Nodal just as easily in rhythmic pieces or even dance music.

Developer Peter Mcilwain tells CDM:

We think new features make [Nodal 1.7] a serious composing tool. Firstly, it can be synced to other applications. Next, individual networks can be triggered (like clips in Ableton) from MIDI notes. The velocity levels in these networks can be scaled according to the velocity of the triggering note. Also, the edges or connections between nodes can now contain MIDI controller curves. This is all demonstrated in [the YouTube clip at top].

The triggering aspect means that you can perform with a generative system in a very intuitive way. Also, I have been working on a piece for a flute ensemble in which I create a triggering score in Logic. This information is then sent to Nodal. Nodal then sends back MIDI which is rendered and recorded in Logic. I’m finding this a fascinating and natural way to work.

Nodal has slipped a bit since Peter first contacted me, but seeing this among the top Mac App Store apps to me is tremendously satisfying. Peter tells us they’re not giving up their day jobs, but it’s nice just to get to support great software.

Nodal: Generative Music Software

I’d love to hear more about Nodal here, especially if you’re making interesting stuff with it. Of course, to discuss with other Nodal users, your best bet is the Nodal discussion group:

Support | Nodal Google Group

The development team – Jon McCormack, Alan Dorin, Aidan Lane, Jon McCormack and Peter McIlwain of Monash University’s Centre for Electronic Media Art in Australia – have published technical papers, too:

Nodal R&D / Technical Papers

Nodal fans / users … or other folks doing development … we’d love to hear from you.

For more generative goodness, see also:

Intermorphic and Noatikl / Mixtilk, a cross-platform system that also includes mobile tools for iOS, from the same team that collaborated with Brian Eno and worked on the landmark SSEYO Koan system.

Hans Kuder’s Tiction uses graphical nodes as does Nodal, and, built in Processing, works on any OS (including Linux). Unfortunately, I’m not sure what happens to Hans or the tool; if anyone knows, let us know.

There are probably others I’m forgetting as the coffee settles in, so chime in in comments.


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