Data intensive projects are inefficient since in science and industry it is known from surveys that 80 % of the time is wasted for data wrangling. We suffer from fragmentation at all levels from data organisation up to semantics which lets many data projects fail and prohibiits the participation of many researchers and companies. The concept of Digital Objects is now broadly accepted as a new level of commodity to overcome the fragmentation at data organisation level and to facilitate interoperability at other levels and to open the way to automatic processing which will be the only way to scale up data intensive work. The C2CAMP initiative as a GO FAIR implementation network is now working on specifying and implementing key components of a...
Currently, research requires processing data at alarge scale. Data is not anymore a collection of st...
The basic idea behind data infrastructures is that it provides for tools giving easy access to distr...
In addition to the previous intensive discussion on the "Data Deluge" with respect to enormous incre...
Data intensive projects are inefficient since in science and industry it is known from surveys that ...
Data-intensive science is reality in large scientific organizations such as the Max Planck Society, ...
Data science is facing the following major challenges: (1) developing scalable cross-disciplinary ca...
Digital research objects are packets of information that scientists can use to organize and store th...
This talk discusses the use of Fair Digital Objects (FDOs for short) for a democratised approach to ...
Data Management Plans (DMP) are now a routine part of research proposals but are generally not refer...
In June 2017, the International Council for Science (ICSU) and its Committee on Data for Science and...
This presentation is about how DiSSCo (Distributed System of Scientific Collections) is using the FA...
Data is the lifeblood of science. Scientists produce data and analyse data, and service providers in...
RO-Crate is a lightweight method to package research outputs along with their metadata, based on Lin...
The Distributed System of Scientific Collections (DiSSCo) is a new Research Infrastructure that is w...
Introductory address for Dealing with Data 2017. A video of this presentation can be viewed at https...
Currently, research requires processing data at alarge scale. Data is not anymore a collection of st...
The basic idea behind data infrastructures is that it provides for tools giving easy access to distr...
In addition to the previous intensive discussion on the "Data Deluge" with respect to enormous incre...
Data intensive projects are inefficient since in science and industry it is known from surveys that ...
Data-intensive science is reality in large scientific organizations such as the Max Planck Society, ...
Data science is facing the following major challenges: (1) developing scalable cross-disciplinary ca...
Digital research objects are packets of information that scientists can use to organize and store th...
This talk discusses the use of Fair Digital Objects (FDOs for short) for a democratised approach to ...
Data Management Plans (DMP) are now a routine part of research proposals but are generally not refer...
In June 2017, the International Council for Science (ICSU) and its Committee on Data for Science and...
This presentation is about how DiSSCo (Distributed System of Scientific Collections) is using the FA...
Data is the lifeblood of science. Scientists produce data and analyse data, and service providers in...
RO-Crate is a lightweight method to package research outputs along with their metadata, based on Lin...
The Distributed System of Scientific Collections (DiSSCo) is a new Research Infrastructure that is w...
Introductory address for Dealing with Data 2017. A video of this presentation can be viewed at https...
Currently, research requires processing data at alarge scale. Data is not anymore a collection of st...
The basic idea behind data infrastructures is that it provides for tools giving easy access to distr...
In addition to the previous intensive discussion on the "Data Deluge" with respect to enormous incre...