Invisque

Lessons Learnt about Innovation Research
Through the INVISQUE project, we have come away with a number of lessons learnt about the process and activity of innovation, how we encourage it, and what can hinder it. In the section below, we briefly list the insights we have learnt through the process of innovation research in INVISQUE.

INNOVATION RESEARCH
Innovation research is not development – it is about breaking new ground. In ‘normal’ development, the system or application is specified. The risks are lower as funder, developer and stakeholders, ‘know’ what they will be getting. In innovation research, although the proposals have to be couched in terms of R&D, the final outcome should be ‘surprising’. It should seek to break paradigms, offering new capabilities that afford new forms of work, rather than just making (minor or major) improvements to the way we work.

Innovation research needs a framework for establishing common expectations. It is good to have a common appreciation and expectation of what the innovation prototypes are supposed to convey. For example, the NASA TRL (Technology Readiness Level) Framework is such a tool that can be used for articulating expectations. The TRL is a 9-point scale that defines the readiness of a technology for deployment. TRL 1 refers to ideas, concepts, very early prototypes used perhaps to study feasibility. TRL 9 refers to very mature technology that is ‘mission ready’, ie it can be deployed in a space ship and be expected to work under the operating conditions.

When developing or maturing the ideas
New ideas need longer time to transfer to members not usually involved in this area – it took longer time than expected when trying to get the design concepts across to all parties, including internal colleagues as well as the external development agency. Next time should allocate longer time especially when the design concepts is very new and unused in most search systems yet.

Staff are not used to thinking or designing or developing for ideas that their original training did not cater for. For example, in most of our work, we are seldom asked or required to “create” or “invent” new concepts. We often work within established paradigms, and we have developed methods and expertise around those paradigms. In many instances, it required us to make very strenous efforts to force ourselves to think differently, beyond what we would normally consider as acceptable or sensible design.

What can very easily stop a very different idea (one that does not conform with our usual paradigms) from growing and maturing is our own advanced expertise and training in critical thinking and analysis. We are very skilled at looking for risks and potential reasons that the idea will not work. In explaining such concepts for the first time or in its early stages, being overly concerned about the risks and potential failures can kill the momentum and freedom of expression that is essential at this stage for creativity and for maturing the ideas. In the early stages of innovation research, we need to be prepared to let our guard down, be flexible wit h our thinking about what works and what doesn’t (based on our experience), and to imagine how it might possibly work. Once an idea is set in motion, it may start other ideas in motion as well: eg imagine the system doing this … hey, that means we can do this as well …! This is what we would call as “imagineer”.

Once the ideas mature, that’s when we start to use those ideas to define how they should be engineered into some form of reality. This is where we draw on our research (if the concept does not have the science and technology to support it yet), engineering (if the underlying S&T exists, we can then start to design, build and test) expertise to make it happen. So, innovation research, in many ways is about imagining – research – engineering => imagineering.

Simplification and focus
The INVISQUE as a fully-deployed system would require many different underlying components to be integrated and to work together, e.g. middleware for federating databases and fusing data from different sources, technologies based on semantic latent analysis for determining semantic distances between papers (ie how close are the ideas in a set articles), and collaborative filtering algorithms for showing related and relevant searches. In the innovation stages where the focus was on the user interface, we had to agree that we would simplify and assume that the underlying technology is in place and works. Such a simplification then allows us to focus on driving the key interactive and visualisation concepts. Another simplification was that while for expediency reasons the interface is operated via a mouse and pointer and keyboard (which although effective, are somewhat more limited in scope and bandwidth), we are thinking that in future versions, the mapping of the functions to input and output device interaction would change, e.g. making use of multi-touch, multi-modal, multi-layered display technologies, and even other non-conventional I/O devices such as augmented reality and high resolution data gloves.

Using HCI as an innovation driver
We have traditionally studied HCI (Human-Computer Interaction) as a subject to understand users’ interaction with technology, and much of the obvious work in the area seems to be concerned with usability evaluations and enhancing the user experience. User-centered design is another approach, but has its limitations in the context of innovation research. UCD assumes a task exist. Part of innovation research assumes that new forms of work can be invented as a result of the inter-play between technological capabilities and user tasks. As technology advances, it creates new opportunities, which in turn changes the way people work. This in turn, sets out new demands for further advances in technology, and the cycle repeats. We need to see HCI more from this perspective than from the more popular aspects of it (e.g. Neilsen’s Usability Alert Boxes).

PROJECT MANAGEMENT IN INNOVATION RESEARCH PROJECTS Flexibility and adaptation to change
A project plan is important to all projects, but it also needs to be flexible and able to change the plan when needed. Not everything might happen as planned, issues may arise that weren’t budgeted for staff might be ill for a long time or leave and so on. The project’s aims and objectives may not change, but how they achieve them may have to. Project staff also needs to be flexible and adapt the plan.

The amount of time to replace with a qualified staff
It might take a long time to find the right staff with the required specialised skills. More time need to be given, if the staff needs to learn and develop new skills.

Plan for the fact that staff may leave
Need to plan what happens when a staff leaves. Make sure that the project is not overly dependent on any one person, and there’s an alternative person to go to when necessary. Also, before the staff leave, make sure all important tasks are completed.

Project collaboration
Communication is vital when there are external parties developing the demo. Better and regular communication is to confirm that the external source is transforming the ideas correctly into the development. This also allows us to test ideas and develop better solutions than they might individually.

Engage with users
It is important have regular evaluation and interviews with the users, so we can understand their needs and ensure that the systems developed are meeting the requirements of the users. While it is user needs that drive what a system will do, in innovation research, it should not hamper or limit the scope of the ideas and how they are implemented.

Focus on the main achievable parts of the project
If there are small parts of the project that cannot be done on time, then, that is fine. Do well on the main and the important parts.

Technical issue
The selection of tools to develop the software is critical. This could decide if you are able to illustrate the ideas and functions you want and by choosing the right tools it can also save a lot of time.

FOR JISC and JISC RI
The JISC RI program is an excellent mechanism to generate new ideas and to bring these ideas to a state that they can become real. However, there is no vehicle to take these now articulated ideas further afield. Often, there is at least one more (broadly speaking) stage before these ideas can be exploited commercially: it needs to be researched and developed further – creating and integrating the “real” underlying technologies and to see if and where the concept actually works, investigate practical limitations and how they may be overcome. Then once that is sorted, another vehicle is needed to exploit the concept for commercialisation so that it returns value to the initial public funding investment. So, we need a mechanism to support and _bridge_ this broad process: innovation => R&D => exploitation and commercialisation. In the Defence R & D Canada (DRDC), innovation and R&D projects that are judged successful or have potential, are given partial funding, and are handed over to a commercial company for exploitation and commercialisation. This way, it ensures that good ideas that are paid for by the tax-payer, gets out into the world, and are not left on the shelf because the funding ran out.