Data Handling

Commit2Data focuses on the application possibilities of big data and the new business models and opportunities that big data brings.

To make the most of these, Commit2Data strengthens knowledge, valorisation and dissemination of data science, stewardship and technology for the top sectors.

There are a number of fundamental challenges that apply across all top sectors. Within Commit2Data, these are the so-called horizontal cross-cutting themes focused on:

Data handling: platforms; access; distributed solutions; privacy; security

Data analytics: machine learning; statistics; mining; efficient algorithms

A focused effort is needed to shift the boundaries of current data science and big data solutions and to grow the algorithmic understanding of data semantics, computational complexity, data protection and human information overload.

To achieve this, this theme focuses on data science and dealing with evolving content, processes, behaviour and societies.

Related projects

Bekijk hieronder de Projecten gerelateerd aan het thema Data Handling

TACTICS

A.I. and Machine Learning

Virtualization and Simulation:

Data science voor veranderende data

Bekijk project

Sqirel-Graphs

Data Handling and Analysis

Security and privacy

Data science voor veranderende data

Bekijk project

GASPADA : Analysis and Vizualization of Hetrogeneous Spatio-temporal Data

Movements of vehicles, people and animals are nowadays increasingly measured and stored, thanks to technologies such as GPS. An important example is digital traces (tracks) of the routes taken by cars. Not only the route points, but also the times of measurement are stored, so that speed along the tracks can be determined anywhere.

Virtualization and Simulation:

Data Handling and Analysis

Data science voor veranderende data

Bekijk project

EciDA: Evolutionary Changes in Distributed Analysis

The objective of this TKI proposal is: to develop and set up an IoT and (big) data-driven analysis platform that enables on-the-fly changes of data sources and changing data analysis steps and parameters over time to adapt to the changing environmental situation.

A.I. and Machine Learning

Internet Of Things (IoT)

Data science voor veranderende data

Bekijk project

Andamoose/ Daccompli

In the 'Dynamic Data Analytics through automatically Constructed Machine Learning Pipelines' project, the data dynamics of two focus projects are investigated.

Healthcare and Biomedical

A.I. and Machine Learning

Data-driven banking and insurance

A.I. and Machine Learning

Vorige 1 Volgende

Related calls

Bekijk hieronder de Calls gerelateerd aan het thema Data Handling

Data science voor veranderende data

Data Handling

Gesloten

Bekijk call

Vorige 1 Volgende

What do gnus on the African savanna have in common with cars making their way through Eindhoven? It may sound odd, but to professor Bettina Speckmann and her co-workers in the GASPADA-project gnus and cars are not that different. It’s all about movem...

30 March 2023

Project updates

GASPADA : Analysis and Vizualization of Hetrogeneous Spatio-temporal Data

Data Handling

Data science voor veranderende data

Lees meer

SQIREL Graph Database Systems

In this project, we are studying the design of graph database systems. The term 'graph' refers to its mathematical meaning: it involves data that takes the form of a network. While this is evident in social networks and telecommunication networks, gr...

27 March 2023

Data science

Project updates

Sqirel-Graphs

Data Handling

Data science voor veranderende data

Lees meer

Present your research at ICT.OPEN2022

Op 6 en 7 april 2022 vindt ICT.OPEN2022 plaats. De organisatie bestaande uit NWO, IPN en PRIO streven naar een fysieke conferentie die wetenschappers uit alle ICT onderzoeksdisciplines en industrieën samenbrengt om elkaar te ontmoeten, te leren en id...

03 December 2021

ICT OPEN

Demo