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𝐅𝐀𝐈𝐑 𝐏𝐫𝐢𝐧𝐜𝐢𝐩𝐥𝐞𝐬 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐌𝐋/𝐀𝐈 - Findings from Skills4EOSC Delphi Study (Elda Osmenaj and Curtis J M Sharma,)

'Whilst everyone is obsessed with AI/ML they often seem to forget that the data is the key part and that 'garbage in garbage out' applies to this principle and we have to invest in the data, to reach the true potential of AI/ML!'

𝐄𝐮𝐫𝐨𝐩𝐞𝐚𝐧 𝐏𝐞𝐫𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞𝐬 𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐃𝐚𝐭𝐚 𝐒𝐭𝐞𝐰𝐚𝐫𝐝𝐬 (Nida van Leersum and Saba Sharma)

'This is important because producing FAIR data is a complex and lengthy process that researchers cannot be expected to do without more staffing resources. Data stewards are key to the success of FAIR, which means we need to invest in training them!'

𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐂𝐮𝐫𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐀𝐫𝐜𝐡𝐢𝐯𝐢𝐧𝐠: 𝐀 𝐃𝐚𝐭𝐚 𝐂𝐮𝐫𝐚𝐭𝐨𝐫’𝐬 𝐏𝐞𝐫𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐋𝐚𝐬𝐭 10 𝐘𝐞𝐚𝐫𝐬 (Fernando Rios)

'Software is ever evolving and there are an immense amount of complexities associated with creating re-useable software, so I am very interested to see what this presentation discusses and what we can learn from the last 10 years.'

𝐌𝐞𝐞𝐭𝐢𝐧𝐠 𝐃𝐨𝐦𝐚𝐢𝐧-𝐒𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬 𝐖𝐢𝐭𝐡 𝐓𝐡𝐞 4𝐓𝐔.𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡𝐃𝐚𝐭𝐚 𝐑𝐞𝐩𝐨𝐬𝐢𝐭𝐨𝐫𝐲 (Madeleine De Smaele)

'Repositories are another key interest of mine, and I'm intrigued to see what domain-specific requirements this repository meets.'