Mondrian: An Agile Visualization Framework

Data visualization is the process of representing data as pictures to support reasoning about the underlying data. For the interpretation to be as easy as possible, we need to be as close as possible to the original data. As most visualization tools have an internal meta-model, which is different from the one for the presented data, they usually need to duplicate the original data to conform to their meta-model. This leads to an increase in the resources needed, increase which is not always justified. In this work we argue for the need of having an engine that is as close as possible to the data and we present our solution of moving the visualization tool to the data, instead of moving the data to the visualization tool. Our solution also emphasizes the necessity of reusing basic blocks to express complex visualizations and allowing the programmer to script the visualization using his preferred tools, rather than a third party format. As a validation of the expressiveness of our framework, we show how we express several already published visualizations and describe the pros and cons of the approach.

Thoracolumbar dorsolateral laminectomy with osteotomy of the spinous process in fourteen dogs

OBJECTIVE: To describe outcome after an alternative unilateral approach to the thoracolumbar spine for dorsal laminectomy. STUDY DESIGN: Retrospective clinical study. ANIMALS: Dogs (n=14) with thoracolumbar spinal cord compression. METHODS: Thoracolumbar spinal cord compression was lateral (6 dogs), dorsal (4), and dorsolateral (4) caused by subarachnoid (7) and synovial cysts (2) and intradural-extramedullary neoplasia (5). All dogs were treated by dorsal laminectomy with osteotomy of the spinous process using a unilateral paramedian approach. The contralateral paraspinal muscles were not stripped from the spinous process and the osteoligamentous complexes were preserved. Retraction of the spinous process and muscles to the contralateral side resulted in complete visualization of the dorsal vertebral arch thereby allowing dorsal laminectomy to be performed. RESULTS: No technique complications occurred. Approximately 75% exposure of the spinal cord (dorsal and lateral compartments) was achieved providing adequate visualization and treatment of the lesions. Transient deterioration of neurologic state occurred in 5 dogs because of extensive spinal cord manipulation. At long-term follow-up, 6 dogs were normal, 6 had clinical improvement, and 2 were unchanged. CONCLUSION: Dorsal laminectomy after osteotomy and retraction of the spinous process may be considered in canine patients with dorsal, dorsolateral, or lateral compression to facilitate adequate decompression of the spinal cord. CLINICAL SIGNIFICANCE: This surgical technique offers an alternative approach to the thoracolumbar spine and spinal cord by a modified dorsal laminectomy that preserves the paraspinal muscle integrity on the contralateral side.

Applying the Fuzzy Analytical Hierarchy Process in Cognitive Cities

This paper introduces a mobile application (app) as the first part of an interactive framework. The framework enhances the inter-action between cities and their citizens, introducing the Fuzzy Analytical Hierarchy Process (FAHP) as a potential information acquisition method to improve existing citizen management en-deavors for cognitive cities. Citizen management is enhanced by advanced visualization using Fuzzy Cognitive Maps (FCM). The presented app takes fuzziness into account in the constant inter-action and continuous development of communication between cities or between certain of their entities (e.g., the tax authority) and their citizens. A transportation use case is implemented for didactical reasons.

Applying the fuzzy analytical hierarchy process in digital marketing

The fuzzy analytical network process (FANP) is introduced as a potential multi-criteria-decision-making (MCDM) method to improve digital marketing management endeavors. Today’s information overload makes digital marketing optimization, which is needed to continuously improve one’s business, increasingly difficult. The proposed FANP framework is a method for enhancing the interaction between customers and marketers (i.e., involved stakeholders) and thus for reducing the challenges of big data. The presented implementation takes realities’ fuzziness into account to manage the constant interaction and continuous development of communication between marketers and customers on the Web. Using this FANP framework, the marketers are able to increasingly meet the varying requirements of their customers. To improve the understanding of the implementation, advanced visualization methods (e.g., wireframes) are used.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.