TOOLS
TOOLS
SPARQL-Integrate is a swiss army knife for realizing small to medium sized data integration workflows as a mere sequence of SPARQL queries stored in a .sparql fileIntegrate heterogeneous data with standard SPARQL syntax plus function extensions.
The tool uses the plugin system of Apache Jena’s SPARQL engine (ARQ) for adding the functionality to access local and remote data and to process JSON, CSV and XML formats. Introduces SPARQL functions which compute a single RDF term from its arguments, e.g. json json:parse(string) and SPARQL property functions (can be seen as magic RDF properties) which transform literals into multiple SPARQL result set rows, e.g. { ?jsonLiteral json:unnest ?itemVar }
Trips are the fundamental entity for analyzing mobility patterns in a Smart City. How many trips are done by car every week? How many in bike? Can we encourage the usage of greener transportation modes?
The trip Update Interface allows citizens to contribute with trips they have made, and to verify/amend trips detected automatically, for example with the transport mode detector component
The Transport Mode Detector is a component that takes a timestamped GPS and accelerometer trace of a citizen and returns (i) the trips made by the citizen, and (ii) a classification of the transport modes of each leg of the trip. The ML techniques were used in combination with Data Mining strategies to pre-process the streaming data and evaluate the models to provide confident labels for specific trips like bike, bus, car, train and walk. The result is a model able to predict new data with high accuracy and high confidence level.
This analytics module developed by TomTom takes data on parking spots (on-street and off-street, for bikes, motorbikes and cars) and historical trip data for these type of vehicles, and produces a map of parking probabilities
i-Log is a (Android) mobile application system to collect data from the sensors of mobile phones and engage with the owners of the phones for contextual information in form of text, audio, photograph, or video. i-Log is modular and adapts to different smartphone models, especially in terms of sensing strategies for both smartphones and their internal sensors; robust to Android version changes; is energy-efficient and has built-in mechanisms for users’ privacy.
The Virtual City Explorer (VCE), is an online crowdsourcing platform for urban auditing. The VCE helps public administrations and mapping agencies recruit volunteers online and ask them to locate Points of Interest (PoIs) in a city, such as shops, bus stops, or disabled parking spaces. Participants explore the relevant area remotely using digital street imagery, spot the PoIs and
submit their location using a built-in custom screen capture capability. The VCE can be used with different types of Crowd: Experts, volunteers or crowdworkers.
More information on the VCE is available at this link
To help municipalities deal with data source heterogeneity. QROWD offers pre-configured, easily customizable acquisition data flows to ingest disparate data sources into a CKAN instance (for static data sources), or into the FIWARE Orion Context broker (for dynamic data sources), from where they can be picked up by other data flows.
QROWD-DB is the main storage component facilitates the discovery and exploitation of data in specific processes and services.
It is comprised by three main elements:
1) The Linked Data Storage: its main goal is to store and manage linked data, entities;
2) The Big Data Storage: dedicated to the storage of the personal big data generated by mobile phone of citizens;
3) The Business Logic: a set of software components previously developed by the University of Trento that allows the partners to access the underlying two
systems and databases
QROWD includes a set of utils for discovering links and fusion data in RDF. The utils take as input several data sources on the same entities (e.g., location of mobility infrastructure accroding to different sources, including crowdsourcing) and allow the creation of clusters of sameAs entities, that can then be fusioned according to trust scores on the the original data sources.
QROWDSmith is a gamification platform to add hedonic incentives to a task, making it more enjoyable for contributors, therefore, increasing engagement and user experience. A motivated contributor is a better contributor! QROWDSmith integrates customizable personal profiles, badges, leaderboards and constant feedback about performance and achievements.
QROWDSmith enables the gamification of
The participatory framework helps organisations to design a Human Interaction Task (HIT) to be undertaken by a crowd. It guides through the principal dimensions of crowdsourcing in order to produce a first step towards the specification and implementation of an effective HIT.
The framework was a QROWD deliverable, that can be downloaded through this link , and is embedded below.
D3.1 - Participatory frameworkThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 732194
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