Steps towards the development of a ‘culture of innovation’ amongst undergraduate industrial designers

Developing innovative solutions to problems is no easy task. Firstly there has to be a desire within the individual to seek out the innovative solution; secondly there is the problem of how to identify what constitutes an innovative solution; and finally one has to combat the natural tendency toward risk aversion. Successful industrial design is by its very nature innovative. Therefore generating a culture of innovation is a vital requirement in the development of a successful designer. Do we know how to stimulate, incubate and nurture innovation? What are the factors that give rise to an innovative mindset? This paper describes the experiences of an industrial design programme that for five years operated with a degree of success. However on review the programme was deemed to be lacking in innovation. Changes were made and after three years the impact was assessed and quantified and the results are now reported. Through the review strategies were developed which led to the creation of an environment for the promotion and nurturing of innovation appropriate to an undergraduate industrial design programme. Following the three year review further refinements to the model have been implemented, this will be the subject of further study

A collaboration leading to the introduction of an innovative medical device to the international market

Development of a medical device is a multi-disciplinary activity. This is particularly the case for laser based instruments which encompass mechanical, optical, hardware and software sub-systems, together with the essential industrial design process. In this field, as in many others, small companies are highly innovative. However, the broad range of expertise needed to realise any innovation can be beyond the company's finite resource base. This can lead to extended time scales resulting in lost market opportunity. Financial constraints also make it difficult to use commercial consultancy services. Collaboration with an academic institution can assist in overcoming this dilemma. This process is not without its difficulties and challenges, since it bridges two cultures. However, if approached in an innovative and imaginative way, results can be achieved that are of mutual benefit. The paper reviews the challenges that were faced, the difficulties that were encountered and how these were addressed and managed, to the mutual benefit to both the academic and the industrial partners

Additional file 1: Figure S1. of Does video feedback analysis improve CPR performance in phase 5 medical students?

Checklist assessment tool for scoring student performance. (PDF 188 kb

PANADA results of a sequence with no functional annotation.

<p>Starting from the viral protein AC4 (UniProt accession number P0DJX3), the constructed network is shown in Cytoscape with organic layout. (A) is colored by biological process with red for “virus-host interaction” (IEA) and green for “DNA recombination; DNA repair; regulation of transcription, DNA-dependent” (IEA). (B) is colored by cellular component with red for “host cell plasma membrane” (IEA) and green for “nucleus” (IEA). In both cases, the yellow color is used for the query protein AC4.</p

Protein similarity network of Thioredoxin-like structures.

<p>The PDB codes of structures from a previous publication <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0078383#pone.0078383-Atkinson2" target="_blank">[23]</a> are used in PANADA to derive a network representation coloured by functional class. The organic layout was generated in Cytoscape with PANADA default parameters. The correspondence between colour codes and functional groups is shown in the upper left part. Notice how structures with the same functional class form tightly packed cluster separated from each other by a few connecting structures.</p

Variation of a protein similarity network as a function of DJPx threshold.

<p>An automatic search for E. coli protein YebC (PDB code 1KON) represented with Cytoscape organic layout and different maximum number of top edges per node (DJPx). Related proteins are found in UniProt database using the Pfam-A family PF01709. Edges are shown for pairwise sequence identity greater than 40% and alignment coverage at least 50%. From left to right and top to bottom, the networks shown the top 100 edges per node, 75, 50 and 25. In all cases, nodes sharing the Biological Process GO terms electronically assigned (IEA) to the query protein are colored in red.</p

DataSheet_1_A model for community-driven development of best practices: the Ocean Observatories Initiative Biogeochemical Sensor Data Best Practices and User Guide.pdf

The field of oceanography is transitioning from data-poor to data-rich, thanks in part to increased deployment of in-situ platforms and sensors, such as those that instrument the US-funded Ocean Observatories Initiative (OOI). However, generating science-ready data products from these sensors, particularly those making biogeochemical measurements, often requires extensive end-user calibration and validation procedures, which can present a significant barrier. Openly available community-developed and -vetted Best Practices contribute to overcoming such barriers, but collaboratively developing user-friendly Best Practices can be challenging. Here we describe the process undertaken by the NSF-funded OOI Biogeochemical Sensor Data Working Group to develop Best Practices for creating science-ready biogeochemical data products from OOI data, culminating in the publication of the GOOS-endorsed OOI Biogeochemical Sensor Data Best Practices and User Guide. For Best Practices related to ocean observatories, engaging observatory staff is crucial, but having a “user-defined” process ensures the final product addresses user needs. Our process prioritized bringing together a diverse team and creating an inclusive environment where all participants could effectively contribute. Incorporating the perspectives of a wide range of experts and prospective end users through an iterative review process that included “Beta Testers’’ enabled us to produce a final product that combines technical information with a user-friendly structure that illustrates data analysis pipelines via flowcharts and worked examples accompanied by pseudo-code. Our process and its impact on improving the accessibility and utility of the end product provides a roadmap for other groups undertaking similar community-driven activities to develop and disseminate new Ocean Best Practices.</p