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Australasian Human Research Ethics Consultancy Services Pty Ltd (AHRECS)

Ask The Chefs: AI and Scholarly Communications – Scholarly Kitchen (Ann Michael | April 2019)0

Posted by Admin in on May 19, 2019
 

No one will dispute that AI (Artificial Intelligence) needs to “eat” data, preferably in massive quantities, to develop. The better the data quality, the better the result. When thinking about the potential applications of AI in scholarly communications as related to research artifacts, how will that work? How might AI be trained on high quality, vetted information? How are the benefits and costs distributed?

The ‘chefs’ at Scholarly Kitchen reflect on the role artificial intelligence could play in scholarly communications.  #SpoilerAlert, two things we need first are good and reliable data and steps to ensure deep biases in the current academic processes aren’t enshrined (and made invisible) in the inscrutable black box of code. We have included some links to a collection of related items.

This month we asked the Chefs: Where does scholarly communication and academic outputs fit in to the world of AI development?
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Judy Luther: In scholarly communications there is an expanding body of openly available content from preprint servers, such as arXiv and bioRxiv, and Open Access journals and books. In addition, there is a growing variety of formats that include datasets and code, open peer review, media, and other elements of the scholarly research cycle. This volume of content provides a rich resource to be mined for all stakeholders as well as a broader audience.
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Friday afternoon’s funny – How safe is your data?0

Posted by Admin in on May 17, 2019
 

Cartoon by Don Mayne www.researchcartoons.com

Like most of Don’s work, this chuckle should prompt an important reflection. Do you have a robust plan for your research data?  Does it include:

  1. Data backup and disaster recovery?
  2. (If it is personally identified, sensitive, commercially valuable or otherwise risky) Involve storing the data in a coded form separate from the code key.
  3. Access control/privileges
  4. Discussion about
    1. Data transport
    2. Ethics
    3. Privacy
    4. GDPR
    5. Ownership and use
  5. Metadata
  6. A plan with regard to retention and disposal

Research: Data Protection Impact Assessment (DPIA) (Guidance: SOAS UL | November 2018)0

Posted by Admin in on May 2, 2019
 

Table of Contents
Research: Data Protection Impact Assessment (DPIA) …. 1
1. Requirement …. 3
2. The Nature of the DPIA …. 3
3. Screening Evaluation …. 4
4. Content and scope …. 4
5. Process …. 5
6. Unmitigated High-Risks …. 5
Appendix 1: Screening Evaluation …. 7
Appendix 2: Data Protection Impact Assessment (DPIA) Template ….8

SOAS University of London’s Research Office has produced a guidance document: Research Data Protection Impact Assessment that is part of the institution’s overall Research Ethics process. It is formulated in line with SOAS’ corporate approach to data and privacy.  Also included below is a trove of other privacy items.

1. Requirement
1.1 The Data Protection Impact Assessment (DPIA) is a requirement that is set out in both the General Data Protection Regulation (GDPR) and the Data Protection Act (DPA) 2018.1
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1.2 The Research Office has prepared the guide set out here as it relates to Research and it forms part of the overall Research Ethics process. It is formulated in line with SOAS’ corporate approach as set out in the Data Protection Impact Assessment Guide.
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Access the full document

Guest Post: Encouraging Data Sharing: A Small Investment for Large Potential Gain – Scholarly Kitchen (Rebecca Grant, et al | January 2019)0

Posted by Admin in on April 20, 2019
 

Data sharing is like maths at school.*

Bear with us.

It might seem harder than the other subjects. You might feel your teachers are not very good at explaining it. But if you do not pay attention, you will very quickly find that many real-world skills rely on maths; and you would have benefited from learning the basics as it provides a solid foundation for the rest of your adult life (whether your ambitions are to become an astronaut, a Grandmaster of chess, or simply to balance your personal expenses).

Likewise, data sharing and data management form the foundation of global academic collaboration, discovery and scientific advancement. Sadly, surveys show that academics rarely get formal training in good data management (let alone best practice), and data management is rarely incentivized by institutions. All too often even the basics are ignored, with data ending up languishing on a USB stick or on a paper notepad.

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