The Quality Dashboard is an industry-shared platform which visualizes translation quality and productivity data in a flexible reporting environment. Both internal and external benchmarking is supported, offering the possibility to monitor your own development and compare your results to industry averages.



Dynamic Quality Framework

Translation quality is a pressing theme in the translation industry. The diversification in content types and rapid adoption of translation technologies (including machine translation) drives the need for more dynamic and reliable methods of quality evaluation.In order to meet this demand, TAUS developed the Dynamic Quality Framework (DQF), a comprehensive set of tools, best practices, metrics, reports, and data to help the industry set benchmarking standards. The vision behind DQF is to standardize the methods and tools for quality evaluation, aggregate the scores and measurements and make these available as industry-shared metrics.

DQF-MQM Error Typology

The Multidimensional Quality Metrics (MQM) is an error typology metric that was developed as part of the (EU-funded) QTLaunchPad project based on careful examination and extension of existing quality models. In a series of meetings, the developers of MQM and DQF agreed to make substantive changes to both DQF and MQMto bring them into harmony. The DQF-MQM metric can be used ‘stand-alone’ but is also available through the DQF open API.

Quality Dashboard

The Quality Dashboard delivers on the vision of DQF as an industry collaborative platform for the global translation services sector, helping all stakeholders – translation buyers and providers, technology developers, and translators – to get deeper insights into the processes and the technologies. Through an open API that connects their translation tools and workflow systems with DQF, translators and project, vendor and quality managers can track and benchmark the quality, productivity, and efficiency of translation.

DQF Data Connector

If you’re using your own dashboard tool, you can make use of the DQF Data Connector. The DQF Data Connector lets you generate a JSON string which allows you to visualize your data on your own, custom dashboard.

Integrations

A DQF integration allows seamless communication between your translation tool and the DQF platform so that you can keep working in your into the environment while the reports are generated in real time. Reports can be visualized on the TAUS Quality Dashboard or you can use your own.

DQF Tools

DQF tools provided a vendor independent environment for evaluating translated content. Users could post-edit machine-translated segments to track productivity, evaluate adequacy and fluency of target sentences, compare translations and count errors based on the DQF-MQM error typology.

Dynamic Quality Framework Report 2015

In 2014 a survey was carried out, aimed at collecting user feedback on the TAUS Dynamic Quality Framework (DQF) tools and resources, and on translation Quality Evaluation (QE) in general. This report contains some use cases, results of the survey and recommendations on how to apply DQF to real life scenarios in the translation and localization business.

DQF-MQM Error Typology

The TAUS Dynamic Quality Framework (DQF) was developed in consultation with TAUS members. DQF includes various tools for the evaluation of translation quality, the error typology being one them. The Multidimensional Quality Metrics (MQM) is an error typology metric that was developed as part of the (EU-funded) QTLaunchPad project based on careful examination and extension of existing quality models. Despite the variety of approaches taken in industry and research, the two models turned out to be broadly similar, but they were also different in important ways due to their history.

In a series of meetings, the developers of MQM and DQF agreed to make substantive changes to both frameworks to bring them into harmony. The newly harmonized metric offers translation professionals a standard and dynamic model that can be used in every context. It can be used ‘stand-alone’ but is also available through the DQF open API .

Check out the DQF-MQM Error Categories

QT21 Project

Quality Translation 21 is a machine translation project which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement no. 645452.

DQF-MQM Harmonization Press Release

In 2015 TAUS and DFKI completed the harmonization of their respective translation quality metrics, the Dynamic Quality Framework (DQF) error typology and the Multidimensional Quality Metrics (MQM).

The DQF-MQM Error Typology Template allows you to manually track your translation quality using the DQF-MQM Error Types. If you're interested in integrating DQF-MQM into your workflow, please check out the available DQF integrations contact our team via dqf@taus.net.

Quality Dashboard

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TAUS Quality Management White Paper

In this white paper, we show that preparation, the use of industry standards and metrics, using a dynamic approach toward content and workflow integration can smoothen the quality evaluation process.
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TAUS Quality Dashboard White Paper

This white paper describes how the TAUS Dynamic Quality Framework (DQF) generates a Quality Dashboard serving the interests of all stakeholders in the global translation industry. Through easy-to-use plug-ins translators and managers share data and reports that give them valuable statistics, benchmarking.

Upcoming features 2017

  1. Trend reports
  2. Improving and extending project-based reports
    1. Reviewing bugs and calculations in the current translation, correction and error annotation reports
    2. Review on the data format for the charts
    3. Extending functionality of the charts on the current translation, correction and error annotation reports with dropdowns for customer and vendor filters
  3. Internal benchmarking by project

DQF Data Connector

If you’re using your own dashboard tool, you can make use of the DQF Data Connector. The DQF Data Connector lets you generate a JSON string which allows you to visualize your data on your own, custom dashboard.

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Integrations

In order to generate quality and productivity reports on the Quality Dashboard, as well as help you track and benchmark your performance for your projects, you need to enable DQF in your CAT tool. A DQF integration allows seamless communication between your translation tool and the DQF platform so that you can keep working in your usual environment while the reports are generated in real time.

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DQF Tools

DQF provides a vendor independent environment for evaluating translated content. Users can post-edit machine-translated segments to track productivity, evaluate adequacy and fluency of target sentences, compare translations and count errors based on an error-typology. The tools help establish return-on-investment and benchmark performance enabling users to take informed decisions.To ensure evaluation results are reliable it is vital that best practices are applied. The DQF Tools help users apply best practices whether they are selecting their preferred engine, measuring productivity or evaluating the quality of translations.

Please note that as of January 1st, 2017 DQF Tools is no longer supported by TAUS. DQF Tools will remain online for educational purposes. If you're interested in tracking and benchmarking translation quality and productivity in a professional setting, we advise you to use the Quality Dashboard or contact dqf@taus.net.

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Content Profiling

The DQF Content Profiling feature is used to help select the most appropriate quality evaluation model for specific requirements. This leads to the knowledge base where you find best practices, metrics, step-by-step guides, reference templates, and use cases.Your underlying process, technology and resources will guide the choice of the quality evaluation model.

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