Authors: Karel Fliegel (Czech Technical University in Prague, Czech Republic), Lukáš Krasula (Arm, United Kingdom), Werner Robitza (TU Ilmenau, Germany)
Editors: Tobias Hoßfeld (University of Würzburg, Germany), Christian Timmerer (Alpen-Adria-Universität (AAU) Klagenfurt and Bitmovin Inc., Austria)
Datasets are an enabling tool for successful technological development and innovation in numerous fields. Large-scale databases of multimedia content play a crucial role in the development and performance evaluation of multimedia technologies. Among those are most importantly audiovisual signal processing, for example coding, transmission, subjective/objective quality assessment, and QoE (Quality of Experience) . Publicly available and widely accepted datasets are necessary for a fair comparison and validation of systems under test; they are crucial for reproducible research. In the public domain, large amounts of relevant multimedia contents are available, for example, ACM SIGMM Records Dataset Column (http://sigmm.hosting.acm.org/category/datasets-column/), MediaEval Benchmark (http://www.multimediaeval.org/), MMSys Datasets (http://www.sigmm.org/archive/MMsys/mmsys14/index.php/mmsys-datasets.html), etc. However, the description of these datasets is usually scattered – for example in technical reports, research papers, online resources – and it is a cumbersome task for one to find the most appropriate dataset for the particular needs.
The Qualinet Multimedia Databases Online platform is one of many efforts to provide an overview and comparison of multimedia content datasets – especially for QoE-related research, all in one place. The platform was introduced in the frame of ICT COST Action IC1003 European Network on Quality of Experience in Multimedia Systems and Services – Qualinet (http://www.qualinet.eu). The platform, abbreviated “Qualinet Databases” (http://dbq.multimediatech.cz/), is used to share information on databases with the community , . Qualinet was supported as a COST Action between November 8, 2010, and November 7, 2014. It has continued as an independent entity with a new structure, activities, and management since 2015. Qualinet Databases platform fulfills the initial goal to provide a rich and internationally recognized database and has been running since 2010. It is widely considered as one of Qualinet’s most notable achievements.
In the following paragraphs, there is a summary on Qualinet Databases, including its history, current status, and plans.
A commonly recognized database for multimedia content is a crucial resource required not only for QoE-related research. Among the first published efforts in this field are the image and video quality resources website by Stefan Winkler (https://stefan.winklerbros.net/resources.html) and related publications providing in-depth analysis of multimedia content databases . Since 2010, one of the main interests of Qualinet and its Working Group 4 (WG4) entitled Databases and Validation (Leader: Christian Timmerer, Deputy Leaders: Karel Fliegel, Shelley Buchinger, Marcus Barkowsky) was to create an even broader database with extended functionality and take the necessary steps to make it accessible to all researchers.
Qualinet firstly decided to list and summarize available multimedia databases based on a literature search and feedback from the project members. As the number of databases in the list was rapidly increasing, the handling of the necessary updates became inefficient. Based on these findings, WG4 started the implementation of the Qualinet Databases online platform in 2011. Since then, the website has been used as Qualinet’s central resource for sharing the datasets among Qualinet members and the scientific community. To the best of our knowledge, there is no other publicly available resource for QoE research that offers similar functionality. The Qualinet Databases platform is intended to provide more features than other known similar solutions such as Consumer Video Digital Library (http://www.cdvl.org). The main difference lies in the fact that the Qualinet Databases acts as a hub to various scattered resources of multimedia content, especially with the available data, such as MOS (Mean Opinion Score), raw data from subjective experiments, eye-tracking data, and detailed descriptions of the datasets including scientific references.
In the development of Qualinet DBs within the frame of COST Action IC1003, there are several milestones, which are listed in the timeline below:
- March 2011 (1st Qualinet General Assembly (GA), Lisbon, Portugal), an initial list of multimedia databases collected and published internally for Qualinet members, creation of Web-based portal proposed,
- September 2011 (2nd Qualinet GA, Brussels, Belgium), Qualinet DBs prototype portal introduced, development of publicly available resource initiated,
- February 2012 (3rd Qualinet GA, Prague, Czech Republic), hosting of the Qualinet DBs platform under development at the Czech Technical University in Prague (http://dbq.multimediatech.cz/), Qualinet DBs Wiki page (http://dbq-wiki.multimediatech.cz/) introduced,
- October 2012 (4th Qualinet GA, Zagreb, Croatia), White paper on Qualinet DBs published , Qualinet DBs v1.0 online platform released to the public,
- March 2013 (5th Qualinet GA, Novi Sad, Serbia), Qualinet DBs v1.5 online platform published with extended functionality,
- September 2013 (6th Qualinet GA, Novi Sad, Serbia), Qualinet DBs Information leaflet published, Task Force (TF) on Standardization and Dissemination established, QoMEX 2013 Dataset Track organized,
- March 2014 (7th Qualinet GA, Berlin, Germany), ACM MMSys 2014 Dataset Track organized, liaison with Ecma International (https://www.ecma-international.org/) on possible standardization of Qualinet DBs subset established,
- October 2014 (8th Final Qualinet GA and Workshop, Delft, The Netherlands), final development stage v3.00 of Qualinet DBs platform reached, code freeze.
Qualinet Databases became Qualinet’s primary resource for sharing datasets publicly to Qualinet members and after registration also to the broad scientific community. At the final Qualinet General Assembly under the COST Action IC1003 umbrella (October 2014, Delft, The Netherlands) it was concluded – also based on numerous testimonials – that Qualinet DBs is one of the major assets created throughout the project. Thus it was decided that the sustainability of this resource must be ensured for the years to come. Since 2015 the Qualinet DBs platform is being kept running with the effort of a newly established Task Force, TF4 Qualinet Databases (Leader: Karel Fliegel, Deputy Leaders: Lukáš Krasula, Werner Robitza). The status and achievements are being discussed regularly at Qualinet’s Annual Meetings collocated with QoMEX (International Conference on Quality of Multimedia Experience), i.e., 7th QoMEX 2015 (Costa Navarino, Greece), 8th QoMEX 2016 (Lisbon, Portugal), 9th QoMEX 2017 (Erfurt, Germany), 10th QoMEX 2018 (Sardinia, Italy), and 11th QoMEX 2019 (Berlin, Germany).
The basic functionality of the Qualinet Databases online platform, see Figure 1, is based on the idea that registered users (Qualinet members and other interested users from the scientific community) have access through an easy-to-use Web portal providing a list of multimedia databases. Based on their user rights, they are allowed to browse information about the particular database and eventually download the actual multimedia content from the link provided by the database owner.
Selected users – Database Owners in particular – have rights to upload or edit their records in the list of databases. Most of the multimedia databases have a flag of “Publicly Available” and are accessible to the registered users outside Qualinet. Only Administrators (Task Force leader and deputy leaders) have the right to delete records in the database. Qualinet DBs does not contain the actual multimedia content but only the access information with provided links to the dataset files saved at the server of the Database Owner.
The Qualinet DBs is accessible to all registered users after entering valid login data. Depending on the level of the rights assigned to the particular account, the user can browse the list of the databases with description (all registered users) and has access to the actual multimedia content via a link entered by the Database Owner. It provides the user with a powerful tool to find the multimedia database that best suits his/her needs.
In the list of databases user can select visible fields for the list in the User Settings, namely:
- Database name, Institution, Qualinet Partner (Yes/No),
- Link, Description (abstract), Access limitations, Publicly available (Yes/No), Copyright Agreement signed (Yes/No),
- Citation, References, Copyright notice, Database usage tracking,
- Content type, MOS (Yes/No), Other (Eye tracking, Sensory, …),
- Total number of contents, SRC, HRC,
- Subjective evaluation method (DSCQS, …), Number of ratings.
Fulltext search within the selected visible fields is available. In the current version of the Qualinet DBs, users can sort databases alphabetically based on the visible fields or use the search field as described above.
The list of databases allows:
- Opening a card with details on particular database record (accessible to all users),
- Editing database record (accessible to the database owners and administrators),
- Deleting database record (accessible only to administrators),
- Requesting deletion of a database record (accessible to the database owners),
- Requesting assignment as the database owner (accessible to all users).
As for the records available in Qualinet DBs, the listed multimedia databases are a crucial resource for various tasks in multimedia signal processing. The Qualinet DBs is focused primarily on QoE research  related content, where, while designing objective quality assessment algorithms, it is necessary to perform (1) Verification of model during development, (2) Validation of model after development, and (2) Benchmarking of various models.
Annotated multimedia databases contain essential ground truth, that is, test material from the subjective experiment annotated with subjective ratings. Qualinet DBs also lists other material without subjective ratings for other kinds of experiments. Qualinet DBs covers mostly image and video datasets, including special contents (e.g., 3D, HDR) and data from subjective experiments, such as subjective quality ratings or visual attention data.
A timeline with statistics on the number of records and users registered in Qualinet DBs throughout the years can be seen in Figure 2. Throughout Qualinet COST Action IC1003 the number of registered datasets grew from 64 in March 2011 to 201 in October 2014. The number of datasets created by the Qualinet partner institutions grew from 30 in September 2011 to 83 in October 2014. The number of registered users increased from 37 in March 2013 to 222 in October 2014. After the end of COST Action IC1003 in November 2014 the number of datasets increased to 246 and the number of registered users to 491. The average yearly increase of registered users is approximately 56 users, which illustrates continuous interest and value of Qualinet DBs for the community.
Besides the Qualinet DBs online platform (http://dbq.multimediatech.cz/), there are also additional resources available for download via the Wiki page (http://dbq-wiki.multimediatech.cz) and Qualinet website (http://www.qualinet.eu/). Two documents are available: (1) “QUALINET Multimedia Databases v6.5” (May 28, 2017) with a detailed description of registered datasets, and “List of QUALINET Multimedia Databases v6.5” in a searchable spreadsheet with records as of May 28, 2017.
There are indicators – especially the number of registered users – showing that Qualinet DBs is a valuable resource for the community. However, the current platform as described above has not been updated since 2014, and there are several issues to be solved, such as the burden on one institution to host and maintain the system, possible instability and an obsolete interface, issues with the Wiki page and lack of a file repository. Moreover, in the current system, user registration is required. It is a very useful feature for usage tracking, ensuring database privacy, but at the same time, it can put some people off from using and adding new datasets, and it requires handling of personal data. There are also numerous obsolete links in Qualinet DBs, which is useful for the record, but the respective databases should be archived.
A proposal for a new platform for Qualinet DBs has been presented at the 13th Qualinet General Meeting in June 2019 (Berlin, Germany) and was subsequently supported by the assembly. The new platform is planned to be based on a Git repository so that the system will be open-source and text-based, and no database will be needed. The user-friendly interface is to be provided by a static website generator; the website itself will be hosted on GitHub. A similar approach has been successfully implemented for the VQEG Software & Tools (https://vqeg.github.io/software-tools/) web portal. Among the main advantages of the new platform are (1) easier access (i.e., fast performance with simple interface, no hosting fees and thus long term sustainability, no registration necessary and thus no entry barrier), (2) lower maintenance burden (i.e., minimal technical maintenance effort needed, easy code editing), and (3) future-proofness (i.e., databases are just text files with easy format conversion, and hosting can be done on any server).
On the other hand, the new platform will not support user registration and login, which is beneficial in order to prevent data privacy issues. Tracking of registered users will no longer be available, but database usage tracking is planned to be provided via, for example, Google Analytics. There are three levels of dataset availability in the current platform: (1) Publicly available dataset, (2) Information about dataset but data not available/available upon request, and (3) Not publicly available (e.g., Qualinet members only, not supported in the new platform). The migration of Qualinet DBs to the new platform is to be completed by mid-2020. Current data are to be checked and sanitized, and obsolete records moved to the archive.
Broad audiovisual contents with diverse characteristics, annotated with data from subjective experiments, is an enabling resource for research in multimedia signal processing, especially when QoE is considered. The availability of training and testing data becomes even more important nowadays, with ever-increasing utilization of machine learning approaches. Qualinet Databases helps to facilitate reproducible research in the field and has become a valuable resource for the community.
-  Le Callet, P., Möller, S., Perkis, A. Qualinet White Paper on Definitions of Quality of Experience, European Network on Quality of Experience in Multimedia Systems and Services (COST Action IC 1003), Lausanne, Switzerland, Version 1.2, March 2013. (http://www.qualinet.eu/images/stories/QoE_whitepaper_v1.2.pdf)
-  Winkler, S. Analysis of public image and video databases for quality assessment, IEEE Journal of Selected Topics in Signal Processing, 6(6):616-625, 2012. (https://doi.org/10.1109/JSTSP.2012.2215007)
-  Fliegel, K., Timmerer, C. (eds.) WG4 Databases White Paper v1.5: QUALINET Multimedia Database enabling QoE Evaluations and Benchmarking, Prague/Klagenfurt, Czech Republic/Austria, Version 1.5, March 2013.
-  Fliegel, K., Battisti, F., Carli, M., Gelautz, M., Krasula, L., Le Callet, P., Zlokolica, V. 3D Visual Content Datasets. In: Assunção P., Gotchev A. (eds) 3D Visual Content Creation, Coding and Delivery. Signals and Communication Technology, Springer, Cham, 2019. (https://doi.org/10.1007/978-3-319-77842-6_11)
Note: The readers interested in active contribution to extending the success of Qualinet Databases are referred to Qualinet (http://www.qualinet.eu/) and invited to join its Task Force on Qualinet Databases via email reflector. To subscribe, please send an email to (firstname.lastname@example.org). This work was partially supported by the project No. GA17-05840S “Multicriteria optimization of shift-variant imaging system models” of the Czech Science Foundation.