Understanding Open Access and Open Data Open Access Deposited

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Date Uploaded: 07/28/2020
Date Modified: 07/28/2020

This webinar was a part of the Data and Computation Science Series and one of five webinars focused on the Publishing Lifecycle of Data. It occurred on July 27, 2020, at 2:00 pm EDT.

Due to technical difficulties, the presentation starts at 8:47.

The presenter was Claudio Aspesi, Senior Research Analyst. He joined Sanford C. Bernstein & Co., LLC, in 2004 covering European media stocks. Previously he was Global Senior Vice President of Strategy at EMI Music and was responsible for defining the company’s business model as the music industry entered the digital age. Before joining EMI Music in 2002, Mr. Aspesi was a member of the executive team at Airclic, an Internet infrastructure company, and prior to that a Principal at McKinsey and Co., working with many leading media and entertainment companies. Mr. Aspesi graduated with the highest honors from Universita Luigi Bocconi, Milan, with a Laurea in Economia Aziendale.

Session Description - Open data and metadata - opportunities, risks, and possible actions

Research data is at the core of what universities do. Its value to researchers is, of course, paramount - and open science offers significant benefits to the scientific community. But this data, and the attached metadata, are increasingly valuable for third parties as well. We will discuss how research data and metadata increasingly overlaps with all the other data produced by academic institutions, how it is becoming increasingly valuable outside the academic community, and how it could become even more valuable in the future. The collection, analysis, synthesis and preservation of data and metadata, however, pose significant issues as well; for example, data can and is being used to evaluate individuals (with the biases implicit in developing algorithms to analyze them). More broadly, the collection and analysis of data raises privacy and academic freedom concerns, and so does the lack of transparency and accountability of third party users. Ultimately, the deployment of data analytics and Artificial Intelligence tools should fit with the broader values of the academic community, such as equity and sustainability - whether it does so is controversial.

In addition to the need to establish principles for the use of data analytics and Artificial Intelligence, there are also significant ethical questions that need to be addressed, and that pose significant challenges, and there are questions about how to ensure the long term preservation of data and metadata.

We will close the presentation with a look at possible steps that the academic community ought to take to address all these issues. We hope that a discussion will follow, in order to address questions and issues, as well as to gather points of view from participants

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