QROWD has released new deliverables, which can be consulted on Downloads page http://qrowd-project.eu/downloads/
The mobile application and its deployment basis
The i-Log is a mobile application that has been developed by the university of Trento to obtain information about citizens’ modal split by collecting their mobile data and asking questions about these data, thus allowing integrated real-time information on traffic and multimodal transport
- 3 – Methods for task and time management http://qrowd-project.eu/wp-content/uploads/2018/12/D3.3-Methods-for-task-and-time-management-1.pdf
Optimisations on the crowdsourcing task prototypes
This deliverable presents an analysis of experiments performed with the Virtual City Explorer (VCE).
- 4 – Crowdsourcing Vocabulary and Licensing http://qrowd-project.eu/wp-content/uploads/2018/12/D3.4-Crowdsourcing-vocabulary-and-licensing-1.pdf
Vocabulary for describing crowdsourcing tasks, and an accompanying repository
It is important for organisations that run crowdsourcing tasks periodically or that share tasks to make crowdsourcing tasks repeatable and reproducible.
- 2 – Data acquisition Framework http://qrowd-project.eu/wp-content/uploads/2018/12/D4.2-%E2%80%93-Data-acquisition-framework-1.pdf
The main building blocks of the QROWD Data Acquisition Framework for static and dynamic datasets
The framework is based on the definition of several data flows created by combination of Apache NiFi templates generated in the scope of QROWD.
- 2 – Integrated processing of data-in-motion and data-at-rest http://qrowd-project.eu/wp-content/uploads/2018/12/D6.2-Integrated-processing-of-data-in-motion-and-data-at-rest-1.pdf
To process both streaming and static data sources together
This document addresses the integrated processing solution for data-in-motion and data-at-rest, which is designed for data science users to process both streaming and static data sources together in a coordinated manner.
- 3 – Dynamic data integration, storage and access http://qrowd-project.eu/wp-content/uploads/2018/12/D7.3%E2%80%93Dynamic-data-integration2c-storage-and-access-1.pdf
to understand the full process of storing and managing the data collected
This deliverable introduces the Qrowd-DB, which is a fundamental component of the general QROWD architecture and whose main purpose is to store and manage all the QROWD data, which also includes the general task of data integration.
- 2 – Benchmarking registry, reporting, and crowdsourcing monitoring tools http://qrowd-project.eu/wp-content/uploads/2018/12/D8.2-Benchmarking-registry2c-reporting2c-and-crowdsourcing-monitoring-tools-1.pdf
providing the benchmark components and initial setup together with the monitoring tools
In this deliverable, benchmarking tools and datasets for data science users and monitoring tools for the integrated platform users are provided.