When nothing is easy: Dealing with heterogeneous data and interoperability issues

When nothing is easy: Dealing with heterogeneous data and interoperability issues

11.03.2021 12:15 – 14:00

All over the world, data is being collected faster and in ever-increasing quantities every day, opening up unprecedented potential for a broad new access to knowledge. However, extracting knowledge from this data brings with it many technical and methodological challenges. These issues are obviously related to the volumes of these data sets, but they are also and above all induced by their complexity and heterogeneity. As such, it is often the question of data interoperability that stands out for many as an insurmountable or at least time-consuming obstacle. Occurring on a multitude of scales - international, internal to certain institutions or research groups, or even sometimes to individuals over time - there is no ‘one size fits all’ solution to heterogeneity, and the least that can be said is that in the face of these challenges, nothing is easy.

Through concrete examples drawn from their research, the speakers at this seminar will share the challenges they have faced in managing and analyzing heterogeneous data, and the solutions they have developed to make interoperability possible. These presentations will underline that the very notion of heterogeneity does not embody the same situation everywhere and can be induced by very different epistemological conditions; notably marked by issues that sometimes go beyond purely scientific considerations, as it can be the case at the Geneva University Hospitals. The need for interoperability is also negotiated differently at the local and the global level, leading to the development of innovative solutions to allow the transition from one to the other, as it is the case for Earth Observation Data Cubes. Finally, once interoperability has been achieved, the question of the reproducibility of data integration processes arises. We will also see during this seminar that in the face of these ultimate challenges - sometimes taken into account (too) late in the research cycle - specific tools and methods can be of significant help.

Lieu

Online - registration mandatory

Organisé par

Rectorat et administration centrale

entrée libre

Classement

Catégorie: Séminaire

Mots clés: Data Science, data, Data collection, data analysis

Inscription

Date limite d'inscription: 11.03.2021

Registration will be opened until 10am.

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