FAIR, BIG and Reliable analytical and digital data in Heritage research, conservation and public outreach 

Session chairs: Dr Sorin Hermon, Dr Vincent Detalle and Prof Franco Niccolucci

The FAIR data principles were defined as a pre-requisite for the Open Science initiative led by the European Commission in collaboration with major similar initiatives across the globe. These refer to data being Findable, Accessible, Integrable and Re-usable. They are also particularly relevant when setting large-scale scientific data repositories, considering Big Data and their related analytics. However, a closure looks at these principles one notes they lack any reference to data quality, either assuming that results of a scientific process are reliable and of high quality by default, or that dealing with big data will eventually normalize any possible sporadic flaws in such data. The roundtable will focus on how to formally express quality of Heritage Science data for the research, conservation and public outreach of Cultural Heritage, through some examples from recent works of our team and related to major European initiatives such as ESPADON, IPERION-HS, 4CH, E-RIHS - the European Research Infrastructure in Heritage Science and AriadnePlus, the European infrastructure for sharing archaeological data.