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We discuss the results of a Community EDI Survey run in July-September 2021 by the Network of Networks, a union of research networks that are largely funded by the UK Engineering and Physical Sciences Research Council and fall under their remit. Responses were received from members of 19 networks, with, relevant to this meeting, 70% of the 267 responses coming from members of the UK Acoustics Network. We discuss implications of the results for how we organise and support attendance at events across our networks, reflecting on feedback to questions on barriers and possible enablers to attending in-person events, and on feedback as to what does and doesn't work for events blending in-person and online attendance. To put this work in context we survey relevant literature on the value or otherwise of blended and online events for supporting the diverse membership of a network. The survey results also provide interesting feedback on the diversity of our networks and how inclusive our networks are perceived to be as a function of the identity of the respondents. We reflect also on lessons from this experience regarding how and how not to attract a strong response to surveys of this type.

The Network has run for four very successful years between 2018-2022. Over these four years we created a community of over 1500 people and gained a strong social media presence, especially on twitter. We have funded 7 pilot projects, 15 interns and over 120 students to attend our machine learning summer schools, in addition to providing training to hundreds of other Network members through our Failed it to Nailed it and Skills4Scientists series. We were undeterred by COVID and took our Network activities online, doubling our membership over the summer of 2020 and bringing us a new array of international members where before we had been predominantly UK based, and since the return of physical events, we converted to a hybrid Network bringing together the best of both worlds for a mix of hybrid and virtual activities.The Network has produced an immense number of resources, including 174 videos for our YouTube Channel and 52 reports across funded projects and events, in addition to supporting the publication of 19 peer reviewed journal and conference papers. The Network has also been heavily involved in other projects including supporting an Ethics for AI working group, and some collaborative projects with the Network of Networks group to run an Equality, Diversity, and Inclusion survey, and to write and compile a very comprehensive resource on how to run a Network which has been distributed to new Networks who were looking for guidance. Overall we feel that this Network has been very successful both in terms of impact and outputs. This report provides a comprehensive overview of the Network. Section 2 details our membership statistics and growth, different social media and website accounts, and statistics on our events. Section 3 lists our outputs, Section 4 contains impact statements and collated feedback on our funded initiatives, and Section 5 describes our other outputs including our work with the Network of Networks.

Openness and transparency constitute a foundational principle for research integrity, as set out in the UK Concordat to Support Research Integrity. Openness can promote rigour, constructive scrutiny, accountability and can enable others to build on research. However, it can also bring challenges. Critically, what openness and transparency can and should mean varies across disciplines and fields of study. This is one of a series of case studies in a wide range of disciplines that illustrate these differences. The series is intended to enable researchers to see similarities and differences between fields, and to inform those supporting open research through, for example, training, policies or incentives. This case study is primarily based on the field of chemistry, although delves into examples pertaining to the whole of the physical sciences domain and its interfaces with other domains. It is based on a single interview with a researcher, and is therefore illustrative rather than representative.

Report from Case Study 7of the Physical Sciences Data Infrastructure (PSDI) pilot phase.The preliminary aim of Case Study 7 was “Explore data trust and sharing framework for applicability to PSDI and develop recommendations for preservation and curation approaches’. Thisbroadened additionally to explore other options for data exchange and sharing frameworks, thereby to enable the recommendations more realistically to reflect the probable requirements of the Physical Sciences community.

Report from Case Study 6of the Physical Sciences Data Infrastructure (PSDI) pilot phase.The main aims of this case study were to:Assess process recording requirements and the associated digital landscape, Investigate Digital Research Notebooks and evaluate the suitability of generic recording systemsto support diverse workflows. &nbsp

Background: The use of artificial intelligence (AI) is growing in food supply chains. The ethical language associated with food supply and technology is contextualised and framed by the meaning given to it by stakeholders. Failure to differentiate between these nuanced meanings can create a barrier to technology adoption and reduce the benefit derived.Scope and approach: The aim of this review paper is to consider the embedded ethical language used by stakeholders who collaborate in the adoption of AI in food supply chains. Ethical perspectives frame this literature review and provide structure to consider how to shape a common discourse to build trust in, and frame more considered utilisation of, AI in food supply chains to the benefit of users, and wider society.Key findings and conclusions: Whilst the nature of data within the food system is much broader than the personal data covered by the European Union General Data Protection Regulation (GDPR), the ethical issues for computational and AI systems are similar and can be considered in terms of particular aspects: transparency, traceability, explainability, interpretability, accessibility, accountability and responsibility. The outputs of this research assist in giving a more rounded understanding of the language used, exploring the ethical interaction of aspects of AI used in food supply chains and also the management activities and actions that can be adopted to improve the applicability of AI technology, increase engagement and derive greater performance benefits. This work has implications for those developing AI governance protocols for the food supply chain as well as supply chain practitioners.

As the volume of data associated with scientific research has exploded over recent years, the use of digital infrastructures to support this research and the data underpinning it has increased significantly. Physical chemists have been making use of eScience infrastructures since their conception, but in the last five years their usage has increased even more. While these infrastructures have not greatly affected the chemistry itself, they have in some cases had a significant impact on how the research is undertaken. The combination of the human effort of collaboration to create open source software tools and semantic resources, the increased availability of hardware for the laboratories, and the range of data management tools available has made the life of a physical chemist significantly easier. This review considers the different aspects of eScience infrastructures and explores how they have improved the way in which we can conduct physical chemistry research.

Our Ethics for AI Working group was born out of a meeting held by the Internet of Food Things Network just before the pandemic to consider research challenges for developing a data trust system for the food sector. Our group came together through a shared interest in Ethics, and formed a working group to consider the ethical dimensions of digital collaboration in the food sector, such as the unintended consequence of AI. We have run several workshops and produced several papers as part of this work (1 published, 2 submitted awaiting review, 3 in progress). We used two key methodologies to explore these ethical issues: Design Fiction and the Moral IT Cards. Whilst our focus was on the food industry, we found these methods extremely useful in terms of considering different ethical aspects of technology and as such we believe they would be of great use to the wider scientific community. Our talk will introduce the working group and our activities, and explain how our methodologies can be put into practice for any Ethical Project.

This talk will cover tips and tricks for how to organise your networks and projects, including how to set up your communication methods, how to structure and organise all of the different types of data that you collect and best practices for project management.

This talk will look at how to capture a wealth of different outputs. Gone are the days when journal papers were the only items to be considered outputs, there are so many different types of outputs that can be produced when working as part of a Network or large scale project. These can include videos, reports, presentations, posters, interviews and much more. This talk will look at creating templates for some of these items, how to capture these, different methods for storing and sharing them, and how to collate together all of your outputs in your institutional repository.

This event was run by the Paperless Lab Academy which is organized by NL42 Consulting and is the 7th iteration of this congress, this year hosted again at Lake Maggiore in Italy. The cent- ral theme for this edition of the conference was #eDataLifeCycle @Work ������ turn your laboratory into a data-driven knowledge center.The congress was a two-day event comprised of a number of presentations, interactive work- shops, and an expert panel discussion session. It was also possible to attend pre-congress train- ing sessions on the day before the event. In the main congress the talks all ran consecutively so it was possible to attend each one, although the workshops ran 2-3 to a workshop session. There was plenty of time for networking alongside the talks with generous coffee breaks, lunch and a networking cocktail session on the first night. Alongside the main hall there was also an exhibition hall where industry vendors had stands and were able to present their offerings with respect to paperless lab solutions. This hall was open during all the networking breaks and so it was possible to talk to and receive software demos from the wide range of vendors present at this event.

This talk forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD students. This video was the second talk in the Skills4Scientists #7 - Ethical Research Session, which focussed on several areas of ethical research including discussions on why ethics is important and how to write an ethics application.

This talk forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD students. This video was the second talk in the Skills4Scientists #6 - Careers 1 Session, which focussed on on several areas of careers advice that will be useful to you as you complete your studies and begin your careers.

his talk forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD students. This video was the fourth talk in the Skills4Scientists #5 - Posters, Presentations & Reports Session, which focussed on several areas of communication for your research; presentations, posters and reports.

This talk forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD students. This video was the third talk in the Skills4Scientists #3 - Version Control and LaTeX Session, which focussed on focus on teaching the basics of LaTeX and version control.

This talk forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD students. This video was the first talk in the Skills4Scientists #3 - Version Control and LaTeX Session, which focussed on focus on teaching the basics of LaTeX and version control.

This talk forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD students. This video was the second talk in the Skills4Scientists #1 - Research Data Management Session, which focussed on several areas of good data management practices.

The use of semantic web technologies within scientific research has slowly gained momentum over the last twenty years. Researchers have realised that these technologies are key to dealing with large volumes of data, and that they enable better organisation of scientific documents and practices. However, we still have a long way to go before these technologies realise their true potential, and this is as much a human endeavour as a technological one. This talk will discuss the affordances of the semantic web, demonstrating where it can be used across the entire scientific research process; but it will also note some lessons learned throughout the last twenty years, and provide some recommendations for going forward in the future.

This is a record of all of the videos from Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD students.

This is a record of all of the videos and reports from the Failed it to Nailed it Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD), the Physical Sciences Data-Science Service (PSDS) and the Cell Press Journal Patterns. All of our speakers were invited to be interviewed and where that interview has taken place, the records of the talks listed below also contain links to the related interviews. The following videos have been recorded for this series:1. Love notes to the future: the importance of metadata - Isobel Stark (University of Southampton) - http://dx.doi.org/10.5258/SOTON/P00322. Pitfalls and Gotcha's with bioactivity data - Professor John Overington (Medicines Discovery Catapult) - http://dx.doi.org/10.5258/SOTON/P00323. Digitising your Chemistry for Recordability, Shareabilty and Reproducibility - Dr Mark Warne - (Deep Matter) - http://dx.doi.org/10.5258/SOTON/P00694. Data Generation, Data Standards and Metadata Capture in Drug Discovery - Dr Martin-Immanuel Bittner (Arctoris) - http://dx.doi.org/10.5258/SOTON/P00645. Giving your Open Data the best chance to realise its potential - Mr Chris Gutteridge (University of Southampton) - http://dx.doi.org/10.5258/SOTON/P00656. Linked Data - Examples and Heuristics - Dr Terhi Nurmikko-Fuller (Australian National University) - http://dx.doi.org/10.5258/SOTON/P00667. Ethical data management - balancing individual privacy and public benefit - Zosia Beckles (University of Bristol) - http://dx.doi.org/10.5258/SOTON/P00598. Data legislation, personal and non-personal data, ethical issues and protecting your IP rights - Michele Voznick (Pinsent Masons LLP) - http://dx.doi.org/10.5258/SOTON/P00609. Practical Ethics for Data Science and Algorithm Design - Tessa Darbyshire (Cell Press Patterns) - http://dx.doi.org/10.5258/SOTON/P006110. Data publication - a personal tale - Dr Sarah Callaghan (CellPress Patterns) - http://dx.doi.org/10.5258/SOTON/P006211. Publishing and citing data in practice - Mr Jez Cope (British Library) - http://dx.doi.org/10.5258/SOTON/P006312. The (long) journey from supporting information to Publishing and Finding FAIR data in chemistry - Professor Henry Rzepa (Imperial College London) - https://doi.org/10.14469/hpc/762913. Organising your Networks & Projects - Dr Samantha Kanza & Dr Nicola Knight (University of Southampton) - http://dx.doi.org/10.5258/SOTON/AI3SD021814. Hints and tips for optimising your researchfish data - Gavin Reddick (ResearchFish Limited) - https://eprints.soton.ac.uk/457241/15. Capturing and Tracking your outputs - Dr Samantha Kanza & Dr Nicola Knight (University of Southampton) - http://dx.doi.org/10.5258/SOTON/AI3SD022016. Using Scopus and SciVal to track your research impact and find collaborators - Christopher James (Elsevier) - http://dx.doi.org/10.5258/SOTON/AI3SD022117. Introduction to Data Visualisation - Dr Rita Borgo (Kings College London) - https://doi.org/10.5258/SOTON/AI3SD025218. (Reproducible) Data Visualisation with R and how to make interactive things with R - Miss Charlie Hadley (Visible Data Ltd) - https://doi.org/10.5258/SOTON/AI3SD025319. Data Visualisation with Python - Mr Samuel Munday (University of Southampton) - https://doi.org/10.5258/SOTON/AI3SD025420. Data Visualisation in Publishing & Communication - Dr Sarah Callaghan (Patterns) - https://doi.org/10.5258/SOTON/AI3SD0255The following reports were also produced:Â 1. AI3SD-Event-Series: Report-19: Failed it to Nailed it! How to get data sharing right! - Dealing with Data: Tips & Tricks - Dr Samantha Kanza & Dr Nicola Knight - http://dx.doi.org/10.5258/SOTON/P00322. AI3SD-Event-Series: Report-20: Failed it to Nailed it! How to get data sharing right! - Data Standards - Dr Samantha Kanza & Dr Nicola Knight - http://dx.doi.org/10.5258/SOTON/P00333. AI3SD-Event-Series: Report-21: Failed it to Nailed it! How to get data sharing right! - Responsible Data Management - Dr Samantha Kanza & Dr Nicola Knight - http://dx.doi.org/10.5258/SOTON/P00344. AI3SD-Event-Series: Report-22: Failed it to Nailed it! How to get data sharing right! - Data Citations and Publishing - Dr Samantha Kanza & Dr Nicola Knight - http://dx.doi.org/10.5258/SOTON/P0035

This event is part of the ‘Failed it to Nailed it’ data seminar series. This event series, currently comprised of four online events is a collaboration between AI3 Science Discovery Network+, Patterns & the Physical Sciences Data-Science Service (PSDS). This event series follows on from a data sharing survey that was undertaken earlier in 2020. Each event in the series handles a different aspect of dealing with data aiming to educate and inform researchers about how to work well with their data, as well as encouraging discussion along the way. Following on from these events the organisers hope to be able to organise more face-to-face events in 2021 which will expand this event series. Understanding the different data standards that are available is absolutely essential to any data-driven research, irrespective of the type of data. In these events we want to encourage re- searchers to consider this as a fundamental aspect of managing, presenting and organising their data rather than an afterthought, or something they wish they did but never got round to. This event aimed to provide an introduction to the different types of data standards, alongside examples of their usage and suggestions for best practices.

Scientists and researchers handle vast amounts of data in the course of their work, and in recent years technology and computational power has revolutionised the ability to create, store and analyse data. Scientific research increasingly now requires scientists to be skilled in computational analysis and the ability to work with algorithms, as they deal with larger and larger data sets. The handling of data in science brings with it legal considerations in relation to data protection and intellectual property rights. This talk will give an overview of the data legislation that applies to scientists and researchers including guidance from data protection authorities and decisions taken by courts, the differences between personal and non-personal data, the ethical issues involved in the use of algorithms and how you can protect your intellectual property rights.