BACKGROUND: In many genomics projects, numerous lists containing biological identifiers are produced. Often it is useful to see the overlap between different lists, enabling researchers to quickly observe similarities and differences between the data sets they are analyzing. One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram: a diagram consisting of two or more circles in which each circle corresponds to a data set, and the overlap between the circles corresponds to the overlap between the data sets. Venn diagrams are especially useful when they are 'area-proportional' i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. Currently there are no programs available that can create area-proportional Venn diagrams connected to a wide range of biological databases.RESULTS: We designed a web application named BioVenn to summarize the overlap between two or three lists of identifiers, using area-proportional Venn diagrams. The user only needs to input these lists of identifiers in the textboxes and push the submit button. Parameters like colors and text size can be adjusted easily through the web interface. The position of the text can be adjusted by 'drag-and-drop' principle. The output Venn diagram can be shown as an SVG or PNG image embedded in the web application, or as a standalone SVG or PNG image. The latter option is useful for batch queries. Besides the Venn diagram, BioVenn outputs lists of identifiers for each of the resulting subsets. If an identifier is recognized as belonging to one of the supported biological databases, the output is linked to that database. Finally, BioVenn can map Affymetrix and EntrezGene identifiers to Ensembl genes.CONCLUSION: BioVenn is an easy-to-use web application to generate area-proportional Venn diagrams from lists of biological identifiers. It supports a wide range of identifiers from the most used biological databases currently available. Its implementation on the World Wide Web makes it available for use on any computer with internet connection, independent of operating system and without the need to install programs locally. BioVenn is freely accessible at http://www.cmbi.ru.nl/cdd/biovenn/.
As interactive systems become increasingly complex and entwined with the environment, technology is becoming more and more invisible. This means that much of the technology that people come across every day goes unnoticed and that the (potential) workings of ambient systems are not always clearly communicated to the user. The projects discussed in this paper are aimed at increasing public understanding of the existence, workings and potential of screens and ambient technology by visualizing its potential. To address issues and implications of visibility and system transparency, this paper presents work in progress as example cases for engaging people in ambient monitoring and public screening. This includes exploring desired scenarios for ambient monitoring with users as diverse as elderly people or tourists and an interactive tool for mapping public screens.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
The objective of DIGIREAL-XL is to build a Research, Development & Innovation (RD&I) Center (SPRONG GROUP, level 4) on Digital Realities (DR) for Societal-Economic Impact. DR are intelligent, interactive, and immersive digital environments that seamlessly integrate Data, Artificial Intelligence/Machine Learning, Modelling-Simulation, and Visualization by using Game and Media Technologies (Game platforms/VR/AR/MR). Examples of these DR disruptive innovations can be seen in many domains, such as in the entertainment and service industries (Digital Humans); in the entertainment, leisure, learning, and culture domain (Virtual Museums and Music festivals) and within the decision making and spatial planning domain (Digital Twins). There are many well-recognized innovations in each of the enabling technologies (Data, AI,V/AR). However, DIGIREAL-XL goes beyond these disconnected state-of-the-art developments and technologies in its focus on DR as an integrated socio-technical concept. This requires pre-commercial, interdisciplinary RD&I, in cross-sectoral and inter-organizational networks. There is a need for integrating theories, methodologies, smart tools, and cross-disciplinary field labs for the effective and efficient design and production of DR. In doing so, DIGIREAL-XL addresses the challenges formulated under the KIA-Enabling Technologies / Key Methodologies for sectoral and societal transformation. BUas (lead partner) and FONTYS built a SPRONG group level 4 based on four pillars: RD&I-Program, Field Labs, Lab-Infrastructure, and Organizational Excellence Program. This provides a solid foundation to initiate and execute challenging, externally funded RD&I projects with partners in SPRONG stage one ('21-'25) and beyond (until' 29). DIGIREAL-XL is organized in a coherent set of Work Packages with clear objectives, tasks, deliverables, and milestones. The SPRONG group is well-positioned within the emerging MINDLABS Interactive Technologies eco-system and strengthens the regional (North-Brabant) digitalization agenda. Field labs on DR work with support and co-funding by many network organizations such as Digishape and Chronosphere and public, private, and societal organizations.
The objective of DIGIREAL-XL is to build a Research, Development & Innovation (RD&I) Center (SPRONG GROUP, level 4) onDigital Realities (DR) for Societal-Economic Impact. DR are intelligent, interactive, and immersive digital environments thatseamlessly integrate Data, Artificial Intelligence/Machine Learning, Modelling-Simulation, and Visualization by using Gameand Media Technologies (Game platforms/VR/AR/MR). Examples of these DR disruptive innovations can be seen in manydomains, such as in the entertainment and service industries (Digital Humans); in the entertainment, leisure, learning, andculture domain (Virtual Museums and Music festivals) and within the decision making and spatial planning domain (DigitalTwins). There are many well-recognized innovations in each of the enabling technologies (Data, AI,V/AR). However, DIGIREAL-XL goes beyond these disconnected state-of-the-art developments and technologies in its focus on DR as an integrated socio-technical concept. This requires pre-commercial, interdisciplinary RD&I, in cross-sectoral andinter-organizational networks. There is a need for integrating theories, methodologies, smart tools, and cross-disciplinaryfield labs for the effective and efficient design and production of DR. In doing so, DIGIREAL-XL addresses the challengesformulated under the KIA-Enabling Technologies / Key Methodologies for sectoral and societal transformation. BUas (lead partner) and FONTYS built a SPRONG group level 4 based on four pillars: RD&I-Program, Field Labs, Lab-Infrastructure, and Organizational Excellence Program. This provides a solid foundation to initiate and execute challenging, externally funded RD&I projects with partners in SPRONG stage one ('21-'25) and beyond (until' 29). DIGIREAL-XL is organized in a coherent set of Work Packages with clear objectives, tasks, deliverables, and milestones. The SPRONG group is well-positioned within the emerging MINDLABS Interactive Technologies eco-system and strengthens the regional (North-Brabant) digitalization agenda. Field labs on DR work with support and co-funding by many network organizations such as Digishape and Chronosphere and public, private, and societal organizations
