Registration and management system software available as open source



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www.visceral.eu Registration and management system software available as open source Deliverable number D1.4 Dissemination level Public Delivery date 5 May 2015 Status Author(s) Final Oscar Alfonso Jiménez del Toro, Georgios Kontokotsios, Aldo Lipani, Sokratis Metallidis, Henning Müller, Allan Hanbury This project is supported by the European Commission under the Information and Communication Technologies (ICT) Theme of the 7th Framework Programme for Research and Technological Development. Grant Agreement Number: 318068

Abstract This document presents the open source release of the VISCERAL Registration System software (http://visceral.eu:8080/register/login.xhtml). This system was developed and adapted over the first two years of the VISCERAL project. It was used during all VISCERAL Benchmarks and released as open source on GitHub (https://github.com/visceral-project/registration-system). The document provides an overview of the management of participants, registration and submission steps. The system can be accesed both by participants and administrators, and handles the documentation available for each of the benchmarks organized by VISCERAL. The submission of the data usage and participation agreements is also included in the system. Finally, this document includes a report on the experience gained in using the cloud infrastructure for evaluation. Page 2 of 9

Table of Contents 1 VISCERAL registration system... 4 1.1 Registration... 4 1.2 Management of participants... 4 1.3 Submission... 5 2 Open source software release... 7 3 VISCERAL infrastructure experience report... 7 3.1 Lessons learned... 7 3.2 Current challenges... 8 4 Conclusion... 9 FTP OS VM file transfer protocol operating system virtual machine Page 3 of 9

1 VISCERAL registration system This section describes the various features available in the VISCERAL registration system. 1.1 Registration The Registration screen for the VISCERAL System is shown in Figure 1. New users will be asked to fill in their contact information including affiliation and the benchmark in which they would like to participate. The participants then receive an email to confirm their registration and obtain access to the system. The VISCERAL usage agreement can be downloaded from the participant dashboard. It should be signed by the participants and a scanned copy uploaded in the dashboard. Once the administrators have approved and activated the participant account, the participant is granted access to the VISCERAL data set and the login info of a virtual machine. Figure 1. The VISCERAL System Registration screen 1.2 Management of participants The dashboard is different for administrators as shown in Figure 2. It displays all the participants registered according to the benchmark and their contact info. Different colours highlight the status of the participants indicating whether they have uploaded the user agreement, have pending verification or a Virtual Machine (VM) has been assigned already to them. The full description of these features can be found in the deliberable D1.3. It is also possible to access and edit the information for the VM of each participant. The files and documents available for the benchmarks can be uploaded or removed in the File Manager screen (Figure 3). Using the Benchmark Manager, administrators can create new benchmarks or administer the starting and ending dates of the existing ones. There is also the VM Manager in which the status of all VMs can be visualized. The administrators are able to visualize and edit the Leaderboard in the Manage Leaderboard screen accessible only to adminsitrators. Page 4 of 9

Figure 2. VISCERAL Registration System Administrator Dashboard 1.3 Submission Figure 3. Files related to the Anatomy2 Benchmark After installing their algorithms in the provided VM, the participants can submit it by clicking the Submit VM button in the Dashboard. Starting from the Anatomy3 Benchmark the system allows multiple submissions before a given deadline. In each submission the organisers take over the VM using the partly automated system for continuous evaluation described in VISCERAL deliverable D1.3. The participant can view their results in the Dashboard by modality, body region, organ and configuration (Figure 4). The participants can select the results they wish to make public with the Publish button in the Evaluation Results screen. The published result metrics will then be displayed in the publicly visible LeaderBoard (Figure 5). Page 5 of 9

Figure 4. Results of the segmentation evaluation for a single participant Figure 5. The public LeaderBoard for the segmentation results Page 6 of 9

2 Open source software release The Registration system is built with the JAVA EE platform and Git is used for the software management. On Github the project source is publicly available under GNU General Public License for anyone to review and extend as they wish. Committing changes on the original codebase is not possible and requires the relevant privileges to be given. The software repository can be found under: https://github.com/visceral-project/registration-system The aim in writing this code was to demonstrate the concept of cloud-based evaluation through having a working registration and administration system for the benchmarks. Due to this being the first version of the registration system that interacts so closely with the Azure cloud, the code is rather poorly documented and contains many workarounds and quick solutions. The code is therefore not well suited for easy installation, nevertheless we make it available so that the work in the VISCERAL project remains available for further development beyond the project. This project is an MVC project using JSF and glassfish as the deployment server. The database that is being used is MySQL. Each.xhtml page inside the project represents a page of the registration system. To each.xhtml there is a bean(controller) linked which describes the logic of the page. An important service is VisceralEAO which contains all the calls to the database. On this website there is available for download a Virtual Machine (VM) which is equipped with everything necessary to continue further the development of the registration system, which can simplify further use of the code. 3 VISCERAL infrastructure experience report The VISCERAL project organized the first series of benchmarks with a large scale 3D radiology image data set using an innovative cloud-based evaluation approach. Having the data stored centrally yields legal, administrative and practical solutions to organizing benchmarks with large data sets: The data can be allocated in a private storage container that complies with the legal requirements from the data providers. Better control over the project s costs, since a cloud platform is flexible enough to increase or reduce the number of VMs and storage containers according to the shifting challenges needs. The scalability and storage capacity from a cloud platform is virtually unlimited. This feature opens up the possibility to run benchmarks on big data sets with a high number of participants. Different access permissions to the data are defined by the organizers with the option to make some information unaccessible to the participants (e.g. test set). The submitted algorithms can be evaluated by the administrators without the intervention from the participants. This generates an objective evaluation of the execution and results. 3.1 Lessons learned In retrospective, the following steps were highlighted due to their favourable influence in the benchmarks success: Planning must extensively consider every component of the platform and how to seamlessly connect them when running the benchmarks. Some early decisions in the project can have a decisive effect in the long term of the evaluation process. Page 7 of 9

Clear specifications are paramount and should be defined in great detail from the beginning. Both organizers and participants will rely on these specifications throughout the project. Continuous assessment of the infrastructure should be based on the participants feedback. The updates coming from these assessments need to be well documented and transparent to the participants. 3.2 Current challenges Running benchmarks in the cloud is a significant paradigm shift and requires an adaptation period, both from the benchmark s organizers, as well as from the participants perspective. It can be challenging to move away from the classic model of providing the data to the participants (i.e. downloading data sets via traditional file transfer protocols such as FTP) and towards the new way of bringing the participants to the data (i.e. giving the participants data access through a virtual machine in the cloud). Outlined in this section are some pending challenges to consider for future benchmark organizers: Narrow time frame for planning, setting up the infrastructure and running benchmarks Access and usage of a cloud platform requires a learning period for most of the participants. Strict timelines for isolated benchmarks can limit the number of participants that go through the process of registering, training their algorithms and submitting their VMs. Having a continuous cycle of benchmarks (e.g. annual events) might attract more participants to adapt their algorithms in the cloud and eventually submit results for the benchmarks. This is not always possible because of the strict timelines to run the benchmarks and analyse the participants results for a finite number of competitions. Freedom to adapt the cloud platform Apart from data security and confidentiality considerations, using a public cloud environment can impact the level of customization available to administrators. The provided management tools need to be used as is, and little to no possibilities exist to adapt them to more specific needs. Scheduled maintenance operations can also make the platform unavailable or cause disruptions in the benchmarks workflow. A private cloud may provide a more flexible environment to develop an evaluation framework. On the other hand, a public cloud simplifies setting up and maintaining the backbone of the platform and theoretically allows for limitless scalability. Choosing the right cloud computing option depends on the initial objectives of the benchmark. Some of the components of the VISCERAL infrastructure were implemented outside the Azure cloud platform. This was mainly due to the limited time frame to set up the needed infrastructure for running and preparing the benchmarks in the cloud. Technical limitations, such as reduced internet connection speed, as well as unfamiliarity of the users with the cloud environment were also hurdles in setting up the benchmarks. Having all the system components in the cloud would have allowed for a more streamlined benchmark organization process. No uniform participants working environments Managing different operating systems and heterogeneous participant prototyping languages and tools increased the workload of setting up the infrastructure : compilation of evaluation tool for different platforms, handling OS differences in the automation process (Windows, Linux), VM maintenance Page 8 of 9

Using a single family of OS could harmonize the infrastructure management tasks. However, this might result in less groups participating overall. 4 Conclusion A registration and administration system for running benchmarks using a cloud-based evaluation approach has been developed in VISCERAL. This system functions well, and will continue to be used for running automated segmentation benchmarks beyond the end of the VISCERAL project. Nevertheless, due to the often experimental approach that had to be adopted to get the system working with the cloud, the code often contains workarounds and quick solutions, and is not well documented. Nevertheless, we have made the code available as open source on GitHub so that what has been done in VISCERAL is not lost. To simplify further use of the code, a Virtual Machine containing the environment in which it runs is also available on GitHub. The developers can be contacted to request some basic assistance in getting the code set up. Page 9 of 9