The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

LTHEchat – The Story of a Community of Practice through Twitter

The original idea for an ongoing tweetchat for professional development came from Dr. Chrissi Nerantzi. The idea emerged through the success of the #BYOD4Lchat, a daily feature of the 5-day openly-licensed course Bring Your Own Devices for Learning (BYOD4L), first offered in January 2014 and based on flexible, distance and online learning (FDOL) Offered Monday to Friday from 8-9pm UK time #BYOD4Lchat always created a real buzz. Chrissi saw the potential for a tweetchat on its own, outside a course that would have the potential to develop a community around it. Courses have such a short lifespan, she thought. What about a community approach to professional development? If we want our academics engaged in ongoing professional development could a weekly tweetchat be an attractive option? Could it work? She wanted to give it a go! When the idea matured a little bit in her head, she shared it with Sue Beckingham over a Skype meeting and then with Dr. David Walker and Peter Reed in an email signing as Chrissi and Sue. She wanted the tweetchat to become a truly collaborative project from the outset and therefore creating the conditions for co-ownership were important to her. The Learning and Teaching in Higher Education tweetchat, or #LTHEchat, came to live. The name came from a core module Chrissi led while working at the University of Salford. Chrissi, Sue, David and Peter became the steering group and decided to run a 3-month pilot and see how it went