This document summarizes the work of developing a Data Discovery Index prototype that helps users find and access shared biomedical data from various repositories. It ingests metadata from different standards and sources using ElasticSearch. It was presented at the Alan Turing Institute Symposium in April 2016. The project aims to organize data through an aggregator framework and portal. It involves mapping various metadata standards to have maximum coverage of use cases with minimal data elements. More information can be found at the listed websites.
This document summarizes Helen Henderson's presentation on institutional identifiers. It discusses existing standards like ONIX, COUNTER, and ISSN, as well as new standards being developed like KBART, Project TRANSFER, and CORE. It outlines several scenarios where institutional identifiers could be used, such as in the electronic resources supply chain, eLearning, research funding, and author registries. It describes the stakeholders involved in each scenario and key issues to address. Finally, it provides the timeline and work plan for the NISO working group developing a new institutional identifier standard.
Introduction to the Research Integrity Advisor Data Management Workshop, Bris...ARDC
Dr Jacobs' introduction to the RIA Data Management Workshop in Brisbane on 31 March 2017. The RIA Data Management Workshop series is a joint collaboration of the Australian Research Council, the National Health and Medical Research Council, the Australasian Research Management Society and the Australian National Data Service.
The document discusses how the biopharma industry has changed and how implementing FAIR principles can help improve research and development productivity. It provides three key points:
1) The biopharma industry has shifted from proprietary internally-driven research to more open collaborations across different organizations as part of a wider ecosystem. Data is now distributed across multiple sources rather than just internal.
2) Implementing FAIR (Findable, Accessible, Interoperable, Reusable) principles enables powerful new AI analytics by allowing data to be more accessible for machine learning and prediction.
3) The Pistoia Alliance supports sharing best practices for organizations to implement FAIR through public-private partnerships from 2019 to 2022.
Standardising research data policies, research data networkJisc RDM
The document discusses standardizing research data policies across journals. It describes an expert group working to develop templates and guidance for data policies. It also discusses a collaboration to implement the Joint Declaration of Data Citation Principles. The group is working with Springer Nature to help standardize their data policies across journals into four main types. The goal is to improve data sharing, citation and reuse.
Gold, silver, bronze - research data networkJisc RDM
This document discusses the development of a scalable data model to meet researcher metadata requirements. It describes conceptual and practical processes used, including aligning with standards and popular data models. An example shows over 1500 lines of metadata XML for one data package. A research data shared service is proposed to provide bronze, silver, or gold ratings for metadata completeness. Focus groups with researchers are evaluating metadata fields and use cases to test the infrastructure. Exercises are used to gather information about researchers' metadata production and needs at different research lifecycle stages.
This document summarizes the work of developing a Data Discovery Index prototype that helps users find and access shared biomedical data from various repositories. It ingests metadata from different standards and sources using ElasticSearch. It was presented at the Alan Turing Institute Symposium in April 2016. The project aims to organize data through an aggregator framework and portal. It involves mapping various metadata standards to have maximum coverage of use cases with minimal data elements. More information can be found at the listed websites.
This document summarizes Helen Henderson's presentation on institutional identifiers. It discusses existing standards like ONIX, COUNTER, and ISSN, as well as new standards being developed like KBART, Project TRANSFER, and CORE. It outlines several scenarios where institutional identifiers could be used, such as in the electronic resources supply chain, eLearning, research funding, and author registries. It describes the stakeholders involved in each scenario and key issues to address. Finally, it provides the timeline and work plan for the NISO working group developing a new institutional identifier standard.
Introduction to the Research Integrity Advisor Data Management Workshop, Bris...ARDC
Dr Jacobs' introduction to the RIA Data Management Workshop in Brisbane on 31 March 2017. The RIA Data Management Workshop series is a joint collaboration of the Australian Research Council, the National Health and Medical Research Council, the Australasian Research Management Society and the Australian National Data Service.
The document discusses how the biopharma industry has changed and how implementing FAIR principles can help improve research and development productivity. It provides three key points:
1) The biopharma industry has shifted from proprietary internally-driven research to more open collaborations across different organizations as part of a wider ecosystem. Data is now distributed across multiple sources rather than just internal.
2) Implementing FAIR (Findable, Accessible, Interoperable, Reusable) principles enables powerful new AI analytics by allowing data to be more accessible for machine learning and prediction.
3) The Pistoia Alliance supports sharing best practices for organizations to implement FAIR through public-private partnerships from 2019 to 2022.
Standardising research data policies, research data networkJisc RDM
The document discusses standardizing research data policies across journals. It describes an expert group working to develop templates and guidance for data policies. It also discusses a collaboration to implement the Joint Declaration of Data Citation Principles. The group is working with Springer Nature to help standardize their data policies across journals into four main types. The goal is to improve data sharing, citation and reuse.
Gold, silver, bronze - research data networkJisc RDM
This document discusses the development of a scalable data model to meet researcher metadata requirements. It describes conceptual and practical processes used, including aligning with standards and popular data models. An example shows over 1500 lines of metadata XML for one data package. A research data shared service is proposed to provide bronze, silver, or gold ratings for metadata completeness. Focus groups with researchers are evaluating metadata fields and use cases to test the infrastructure. Exercises are used to gather information about researchers' metadata production and needs at different research lifecycle stages.
Implementing figshare, research data networkJisc RDM
Implementing figshare and engaging researchers,
Research data network, September 2016, Georgina Parsons, Cranfield University and Megan Hardeman, figshare.
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
FAIR for the future: embracing all things dataARDC
FAIR for the future: embracing all things data - Natasha Simons, Keith Russell and Liz Stokes, presented at Taylor & Francis Scholarly Summits in Sydney 11 Feb 2019 and Melbourne 14 Feb 2019.
Grampian safe haven, research data networkJisc RDM
Safe havens" should be developed as an environment for population-based research where the risk of identifying individuals is minimized. Researchers in safe havens are bound by strict confidentiality codes preventing disclosure of personally identifying information and providing sanctions for breaches of confidentiality.
The document discusses enabling FAIR (Findable, Accessible, Interoperable, Reusable) practices through both bottom-up and top-down approaches. It describes several EU and US biomedical data infrastructure programs and projects since 2014 that have taken bottom-up approaches through multi-institutional collaborations. It also discusses the FAIRsharing registry, a top-down approach that has been recommending standards, databases, and policies since 2011 to help researchers and improve data sharing policies of journals and funders. Lessons learned include the need to work both with technical and social aspects to define and measure success.
Midwest Medical Library Association 2015 Big Data PanelIUPUI
The document discusses best practices for managing research data to enable reuse. It emphasizes the importance of planning, incentives, licensing, metadata, identifiers, standards, access, and infrastructure to share and preserve data. Enabling reuse requires considering these factors from the inception of a research project. The document also lists resources for data management plans, tutorials, policies, and tools to archive, discover, access, and track the impact of shared research data.
Managing sensitive data at the University of BristolJisc RDM
Presentation on managing sensitive data at the University of Bristol by Kellie Snow, Research Data Librarian for the Research Data Network event, May 2016, Cardiff University.
This presentation was provided by Maria Praetzellis of California Digital Library, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Les Hawkins discusses the development of the CONSER Standard Record (CSR) for cataloging serials. He addresses the challenges of introducing change, building trust, and clear communication. The CSR provides essential elements for users while streamlining training. It was developed cooperatively, tested at several institutions, and informed by user perspectives. While initial agreement took time, outreach, documentation, and online learning have increased adoption of the CSR over the past year.
Libraries, RDM and e-infrastructure requirementsSusan Reilly
Presentation by S.K. Reilly on the e-infrastructure requirements of libraries and the LERU Roadmap for Research Data. Presented at the EIRG meeting, Athen, 10 June, 2014
The document summarizes findings from a survey on research data management practices. Some key findings include:
- 17% of researchers had lost data due to issues like hardware failure and human error.
- 68% of researchers currently share or plan to share their data. Main motivations for sharing include funder requirements and increasing citation/impact.
- Only 16% of researchers currently use university research data management support services, indicating a need to improve outreach and support.
- 41% of researchers hold some type of sensitive data like patient or personal information, underscoring the need for secure data storage and sharing policies.
The document discusses interest from researchers at other universities in Edinburgh's integration of electronic lab notebooks (ELNs) with research data management systems (RDMS). It summarizes the key benefits of RSpace, Edinburgh's ELN and RDMS, including its ability to capture, organize, and share data and files. It connects to Edinburgh's data storage systems and is integrated with their data repository and archive. This provides researchers an integrated research data management workflow.
What I wish I’d known at the start! What I wish I’d known at the start! Lessons learned the hard way when setting up RDM services;
Stephen Grace, London South Bank University, Sarah Jones, DCC; Research Data Network
This document discusses the role of librarians in supporting research data management (RDM). It outlines the University of East London's (UEL) approach to RDM, including developing an RDM policy and providing training to librarians and researchers. Librarians are well-positioned to help with RDM due to their expertise in managing information and commitment to long-term research. However, many librarians lack skills specific to RDM. To address this, UEL created an online training course called "supportDM" to teach librarians how to support researchers with data management plans, preservation, and sharing data. The document encourages other institutions to make use of existing RDM resources and train their own lib
My presentation at the http://neuroinformatics2017.org (Kuala Lumpur, Malaysia) on FAIR and FAIRsharing (previously BioSharing); metadata standards and their implementation by databases/repositories and adoption by journals' and funders' data policies.
This presentation was provided by Dr. Paul Burton of the University of Bristol during the NISO Symposium, Privacy Implications of Research Data, held on September 11, 2016, in conjunction with the International Data Week in Denver, Colorado.
This presentation was provided by Clara Llebot of Oregon State University, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
This document discusses supporting data sharing through publisher policies and services. It summarizes that over 40 research funders globally require data archiving as a condition for grants. While funder policies motivate researchers to share data, complying with these policies is challenging for over half of researchers. The document then discusses Springer Nature's efforts to standardize and harmonize research data policies across journals, provide related support services to help with compliance, and lessons learned from their implementation progress.
Libraries and Research Data Management – What Works? LERU´s Recommendations o...LIBER Europe
This presentation by Dr Wolfram Horstmann was given at the Scholarly Communication and Research Infrastructures Steering Committee Workshop. The workshop title was Libraries and Research Data Management – What Works?
Implementing figshare, research data networkJisc RDM
Implementing figshare and engaging researchers,
Research data network, September 2016, Georgina Parsons, Cranfield University and Megan Hardeman, figshare.
From "A National Approach to Open Research Data in Ireland", a workshop held on 8 September 2017 in National Library of Ireland, organised by The National Library of Ireland, the Digital Repository of Ireland, the Research Data Alliance and Open Research Ireland.
FAIR for the future: embracing all things dataARDC
FAIR for the future: embracing all things data - Natasha Simons, Keith Russell and Liz Stokes, presented at Taylor & Francis Scholarly Summits in Sydney 11 Feb 2019 and Melbourne 14 Feb 2019.
Grampian safe haven, research data networkJisc RDM
Safe havens" should be developed as an environment for population-based research where the risk of identifying individuals is minimized. Researchers in safe havens are bound by strict confidentiality codes preventing disclosure of personally identifying information and providing sanctions for breaches of confidentiality.
The document discusses enabling FAIR (Findable, Accessible, Interoperable, Reusable) practices through both bottom-up and top-down approaches. It describes several EU and US biomedical data infrastructure programs and projects since 2014 that have taken bottom-up approaches through multi-institutional collaborations. It also discusses the FAIRsharing registry, a top-down approach that has been recommending standards, databases, and policies since 2011 to help researchers and improve data sharing policies of journals and funders. Lessons learned include the need to work both with technical and social aspects to define and measure success.
Midwest Medical Library Association 2015 Big Data PanelIUPUI
The document discusses best practices for managing research data to enable reuse. It emphasizes the importance of planning, incentives, licensing, metadata, identifiers, standards, access, and infrastructure to share and preserve data. Enabling reuse requires considering these factors from the inception of a research project. The document also lists resources for data management plans, tutorials, policies, and tools to archive, discover, access, and track the impact of shared research data.
Managing sensitive data at the University of BristolJisc RDM
Presentation on managing sensitive data at the University of Bristol by Kellie Snow, Research Data Librarian for the Research Data Network event, May 2016, Cardiff University.
This presentation was provided by Maria Praetzellis of California Digital Library, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Les Hawkins discusses the development of the CONSER Standard Record (CSR) for cataloging serials. He addresses the challenges of introducing change, building trust, and clear communication. The CSR provides essential elements for users while streamlining training. It was developed cooperatively, tested at several institutions, and informed by user perspectives. While initial agreement took time, outreach, documentation, and online learning have increased adoption of the CSR over the past year.
Libraries, RDM and e-infrastructure requirementsSusan Reilly
Presentation by S.K. Reilly on the e-infrastructure requirements of libraries and the LERU Roadmap for Research Data. Presented at the EIRG meeting, Athen, 10 June, 2014
The document summarizes findings from a survey on research data management practices. Some key findings include:
- 17% of researchers had lost data due to issues like hardware failure and human error.
- 68% of researchers currently share or plan to share their data. Main motivations for sharing include funder requirements and increasing citation/impact.
- Only 16% of researchers currently use university research data management support services, indicating a need to improve outreach and support.
- 41% of researchers hold some type of sensitive data like patient or personal information, underscoring the need for secure data storage and sharing policies.
The document discusses interest from researchers at other universities in Edinburgh's integration of electronic lab notebooks (ELNs) with research data management systems (RDMS). It summarizes the key benefits of RSpace, Edinburgh's ELN and RDMS, including its ability to capture, organize, and share data and files. It connects to Edinburgh's data storage systems and is integrated with their data repository and archive. This provides researchers an integrated research data management workflow.
What I wish I’d known at the start! What I wish I’d known at the start! Lessons learned the hard way when setting up RDM services;
Stephen Grace, London South Bank University, Sarah Jones, DCC; Research Data Network
This document discusses the role of librarians in supporting research data management (RDM). It outlines the University of East London's (UEL) approach to RDM, including developing an RDM policy and providing training to librarians and researchers. Librarians are well-positioned to help with RDM due to their expertise in managing information and commitment to long-term research. However, many librarians lack skills specific to RDM. To address this, UEL created an online training course called "supportDM" to teach librarians how to support researchers with data management plans, preservation, and sharing data. The document encourages other institutions to make use of existing RDM resources and train their own lib
My presentation at the http://neuroinformatics2017.org (Kuala Lumpur, Malaysia) on FAIR and FAIRsharing (previously BioSharing); metadata standards and their implementation by databases/repositories and adoption by journals' and funders' data policies.
This presentation was provided by Dr. Paul Burton of the University of Bristol during the NISO Symposium, Privacy Implications of Research Data, held on September 11, 2016, in conjunction with the International Data Week in Denver, Colorado.
This presentation was provided by Clara Llebot of Oregon State University, during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
This document discusses supporting data sharing through publisher policies and services. It summarizes that over 40 research funders globally require data archiving as a condition for grants. While funder policies motivate researchers to share data, complying with these policies is challenging for over half of researchers. The document then discusses Springer Nature's efforts to standardize and harmonize research data policies across journals, provide related support services to help with compliance, and lessons learned from their implementation progress.
Libraries and Research Data Management – What Works? LERU´s Recommendations o...LIBER Europe
This presentation by Dr Wolfram Horstmann was given at the Scholarly Communication and Research Infrastructures Steering Committee Workshop. The workshop title was Libraries and Research Data Management – What Works?
'Data Management Planning: the role of institutions and researchers' eResearc...Marta Ribeiro
Recent changes to the Australian Code for the Responsible Conduct of Research bring home the importance of Data Management Planning. DMPs have been required by UK research funders for several years now, and the Digital Curation Centre (DCC) has developed a number of resources in response. Notably these include example plans, a DMP Checklist and DMPonline , a web-based tool to help researchers write plans according to requirements from their funder and institution.
This half-day workshop showcases the many benefits of data management and sharing plans. We will share resources and lessons from the UK context to assist Australian researchers and universities to address requirements for DMPs. Colleagues from ANDS will speak about the Australian context and the Digital Scholarship team will explain how the University of Melbourne is responding. The DCC will provide an overview of DMPonline and how this can be customised by institutions to add templates and tailored guidance. An exercise will also give an opportunity to write a DMP based on guidance and examples from the UK. The workshop will end with a Q&A session giving attendees the opportunity to ask questions and suggest ideas which may influence future development of the tool.
- An understanding of the purpose of data management planning and how the process benefits different stakeholders;
- An awareness of DMPonline and how it can be used;
- Ideas of how DMPs can be integrated into existing institutional system;
Systems and Services: Adding Value For ResearchARDC
Research data infrastructure and services at universities and research institutions are constantly evolving to make better use of technology and to better meet the needs of researchers and other stakeholders. The first part of this Webinar will look at five strategies Australian research institutions have used to maximise the value of their research data assets:
1. Revise institutional data management strategic plan
2. Rethink data management plans and tools
3. Connect and integrate research systems
4. Track project activities, contributors and outputs
5. Leverage skills and knowledge gained through the ANDS 23 (research data) Things program
Webinar recording in YouTube: https://www.youtube.com/watch?v=L8-DuxZQl5c
Research Data Management in practice, RIA Data Management Workshop Brisbane 2017ARDC
The Australian National Data Service (ANDS) aims to make Australian research data more valuable by partnering with research organizations and funding data projects. In 2015, ANDS conducted over 100 workshops and events with over 4,000 participants and developed online resources. ANDS provides guides on topics like data management and the FAIR data principles. ANDS also advocates for practices like data citation and publishing to ensure research data is preserved and reusable over time. The presentation outlines ANDS' role in supporting good research data management practices and sharing to ensure the integrity and impact of research evidence.
Presentation to the Woolcock Institute of Medical Research ARDC
The document discusses principles and best practices for managing and sharing health and medical research data. It outlines the benefits of open data sharing, such as increased collaborations and citations. However, health data also requires special protections for privacy and ethical use. The document provides guidance on obtaining informed consent, de-identifying data, choosing appropriate licenses, and using reputable repositories. It recommends that researchers publish detailed metadata and make data accessible while respecting legal and ethical standards for sensitive information.
The document discusses the Research Data Alliance (RDA), an international organization focused on building the infrastructure to support open sharing of research data. It provides an overview of RDA's governance structure, which includes councils, working groups, and interest groups that work to develop technical standards and social agreements to advance open data sharing. The document also notes RDA's growing global membership across academic, government, and commercial organizations and its efforts to address barriers to data sharing through the development and adoption of infrastructure components.
Brief summary for the INCF Neuroscience Assembly (https://neuroinformatics.incf.org/2021/program-week-2) of the two sessions run at the RDA Plenary 17th, which FAIRsharing WG has contributed t.
What infrastructure is necessary for successful research data management (RDM...heila1
RDM life cycle; research data elements in the research life cycle; what is RDM infrastructure; IT infrastructure; Library infrastructure; Research Office infrastructure; Examples of 4 universities RDM service offerings
The document discusses data governance and quality challenges for publishers. It defines data governance and highlights common data quality issues like multiple data sources, inconsistent data entry, and challenges identifying individuals and institutions uniquely. The presentation recommends developing a data governance program that includes planning, auditing existing data, improving data capture processes, using identifiers, and ongoing monitoring to improve data quality over time. A publisher example is provided that leverages tools like Ringgold identifiers and data governance dashboards to clean data and monitor quality.
This presentation was provided by Carly Strasser of the Chan Zuckerberg Initiative during the NISO hot topic virtual conference "Effective Data Management," which was held on September 29, 2021.
Rubbish in Rubbish out: applying good data governance techniques to gain maxi...Ringgold Inc
1) The document discusses the importance of data governance and quality for organizations. It defines data governance as processes, policies, standards, organization, and technologies required to manage data availability, accessibility, quality, consistency, auditability, and security.
2) Common challenges to data quality are multiple data silos, inconsistent data entry, and lack of unique identifiers. Poor data quality can lead to incorrect decision making and lost opportunities.
3) The presentation recommends developing a data governance program including cleaning existing data, improving data capture processes, using unique identifiers, and ongoing monitoring to improve an organization's data quality over time.
Ross Wilkinson - Data Publication: Australian and Global Policy DevelopmentsWiley
Australia invests $AUD1-2B per annum in research data. Like most countries, it wants to get the best return possible on this data. Europe is spending E1.4B on their open data “pilot”. This means the data should be FAIR: findable, accessible, interoperable, and reusable. Part of this is that data should be routinely “published” and available in a “data repository”. But what does this mean?
Ross Wilkinson
CEO, Australian National Data Service
Presented at the 2015 Wiley Publishing Seminar, 5 November, Melbourne, Australia.
This document summarizes an update on the Research Data Alliance (RDA). It discusses the growth of RDA membership and activities. Key points include:
- RDA works to reduce barriers to data sharing and exchange by building social, organizational and technical infrastructure.
- RDA has grown significantly since its launch in 2013, with over 2,500 members from over 90 countries working in various working groups.
- Working groups focus on developing deliverables like standards, best practices and code to enable data sharing in various domains and for community needs, data stewardship, and base infrastructure.
- The first deliverables have been presented, with more to come, aimed at making data sharing and discovery more trustworthy
#1 FINDABLE covers: -- an overview of the FAIR principles: their origins, Australian FAIR initiatives, what FAIR is (and what it is not) -- the 4 FINDABLE principles which underpin the discoverability of data -- resources to support institutional awareness and uptake of Findable principles to make your institutional data globally discoverable
Speakers
1) Keith Russell, ANDS, will introduce FAIR
2) Nick Thieberger, Director of Paradisec, will present how Paradisec has made their data findable via rich metadata, identifiers through Research Data Australia and disciplinary discovery portals.
YouTube : https://youtu.be/vn2pr2dGzCs
Transcript: https://www.slideshare.net/AustralianNationalDataService/transcript-1-fair-intro-into-fair-and-f-for-findable
Ingrid Dillo from DANS (Dutch Academy and Research Funding Organisation) discusses data sharing and the FAIR principles. She explains that data sharing is important for research validation, reuse, and building on prior work. However, ensuring data quality and trust is key. The FAIR principles provide guidelines for findable, accessible, interoperable and reusable data. Certification mechanisms like CoreTrustSeal help create trust in digital repositories. While open data is important, responsible data management practices are also needed. Guidelines have been developed to help researchers and institutions in the arts and humanities domain apply FAIR principles to their work.
This document discusses the need for critical infrastructure to promote data synthesis and evidence-based nutrient management. It outlines 10 steps for real-time data uptake, analysis, and customized nutrient recommendations. Key challenges include data standards, minimum data sets, provenance, and repositories. The Purdue University Research Repository is presented as a solution, providing preservation, curation, and publication of agricultural data. Hands-on support from librarians and agronomists is discussed to help researchers transition data and ensure best practices.
Similar to FAIR publishing of research outputs in Australia 20180526 (20)
How well does your repository support f.a.i.r. poll resultsKeith Russell
This document summarizes the results of an online voting poll conducted at a repository community event on October 30, 2018 about how well repositories support F.A.I.R. principles. The poll asked questions about findability, accessibility, interoperability, and reusability of repository data. Contact information is provided for those seeking more guidance on next steps for improving F.A.I.R. support.
This document discusses the rising tide of data in science and the opportunities and challenges it presents. It outlines how scientific breakthroughs are increasingly powered by advanced computing capabilities applied to massive datasets. Open sharing of research data allows for errors to be identified and theories to be supported, rejected or refined, improving reproducibility. However, a survey found that many scientists believe there is a reproducibility crisis. Maximizing the value of data requires making it FAIR (findable, accessible, interoperable, and reusable). Examples provided demonstrate how open data sharing has benefited fields like epidemiology and agriculture.
Metadata stores systems in use 20180322Keith Russell
Presentation to Macquarie University research data committee on systems in use in Australia for tracking and exposing research data (including metadata catalogs and metadata stores) 22 March 2018
Presentation on the FAIR data principles and how they relate to Science Gateways and software. Presented at a workshop prior to eResearch Australasia 16 October 2017
The FAIR data principles were drafted in 2015 to improve the findability, accessibility, interoperability, and reusability of digital assets. They consist of 15 guidelines across the four areas. Findable guidelines ensure data has a unique identifier and is searchable. Accessible guidelines specify how metadata and data can be retrieved. Interoperable guidelines promote standard formats and vocabularies. Reusable guidelines address attribution, licensing, and community standards. The principles aim to make data more easily discovered and used across technology and disciplines.
Presentation on Weblectures at the OnderwijsdagenKeith Russell
This presentation was delivered at a preconference of the onderwijsdagen on the 11th of November 2008 on adopting Weblectures. Not only does it focus on use in education but also more general lessons learnt and organisational issues.
A presentation in Dutch on the results of the Weblectures project discussing the advantages of rich media and criteria for the choice for a rich media system.
Dit is de presentatie gegeven bij het departement Biologie, Universiteit Utrecht, gegeven op woensdag 11 juni 2008 over de bevindingen uit het project Weblectures.
An early presentation on the weblectures project at Utrecht University, The Netherlands, delivered on the 22nd of March 2007 to the ICT coordinators of the different faculties.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...Travis Hills MN
By harnessing the power of High Flux Vacuum Membrane Distillation, Travis Hills from MN envisions a future where clean and safe drinking water is accessible to all, regardless of geographical location or economic status.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Authoring a personal GPT for your research and practice: How we created the Q...Leonel Morgado
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
Sexuality - Issues, Attitude and Behaviour - Applied Social Psychology - Psyc...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...Scintica Instrumentation
Targeting Hsp90 and its pathogen Orthologs with Tethered Inhibitors as a Diagnostic and Therapeutic Strategy for cancer and infectious diseases with Dr. Timothy Haystead.
Current Ms word generated power point presentation covers major details about the micronuclei test. It's significance and assays to conduct it. It is used to detect the micronuclei formation inside the cells of nearly every multicellular organism. It's formation takes place during chromosomal sepration at metaphase.
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
FAIR publishing of research outputs in Australia 20180526
1. Keith Russell
FAIR publishing of research outputs in
Australia
Pieces of the puzzle
Partnerships Programs Manager
28 May 2018
2. What is in place?
NCRIS facilities: AUSCOPE, IMOS, TERN, ALA, NCI,
Pawsey, AAF, AARNet
Policy development at the national level: FAIR access
policy statement
Institutional policies and practices
support in libraries: data librarians
Metadata stores and profiling places
Research data management 101
ORCID rollout
NCRIS
facilities
National
policy
Institutional
policy &
support
Skilled
staff
Identifiers
Connected
(trusted)
tools &
repositories
4. Institutional ‘Infrastructure’
Data Management policies and guidelines
Data Management plans
Output registries/repositories (not many TDRs)
Research Software and tool development
Skilled staff
5. Network of research data catalogs feeding into
http://researchdata.ands.org.au
6. Persistent identifiers
ORCIDs for contributors
DOIs for data
DOIs for software
DOIs for publications
IGSN for samples
Grant IDs
Research Activity IDs
7. Skills and FAIR awareness
23 Research Data Things
‘Are you FAIR aware survey?’
Data management Capability Maturity
FAIR data self assessment tool
RDM101 Train the Data Trainer workshops
RDM101 training materials
FAIR resources
9. Partnerships Programs Manager
Keith.Russell@ands.org.au
03 9905 6273
www.ands-nectar-rds.org.au/
Keith Russell
With the exception of third party images or where otherwise indicated, this work is licensed under the Creative
Commons 4.0 International Attribution Licence.
ANDS, Nectar and RDS are supported by the Australian Government through the National Collaborative Research
Infrastructure Strategy Program (NCRIS).
Editor's Notes
I will give you a brief overview of some of the pieces of the puzzle that are in place to support publishing of FAIR research outputs in Australia
A few elements that are in place or in development in Australia so a researcher can comply with publisher requirements in Earth and Environmental Sciences
NCRIS facilities
National policy drive
Institutional policy and support
Skilled Staff to support researchers
Identifiers
Connected (trusted) repositories
You have already have had a chance to meet some of the NCRIS facilities that play a role in publishing Earth Science and Environmental data, so I won’t go into them today
Regarding national policy there is amongst other things the Policy Statement on F.A.I.R. access to research outputs which came out of a committee convened by Universities Australia, the council of University Librarians and covers publications, data, software and other research outputs.
There is also a push for opening up research outputs and making them more FAIR
For example in the funder policies and government responses to the Productivity Commission around Data availability and Use
At the same time international publisher policies strongly influence
To tie all this information together there is a growing uptake of persistent identifiers
ORCIDs for contributors (we have encouraged the uptake and use of ORCIDs to unambiguously identify the contributors
Using DOIs to identify data, for software and publications
Using IGSNs for samples
Grant IDs for grants from the ARC and NHMRC
Research Activity IDs to tie together outputs, contributors and activities that are taking place under a research activity
Adrian and Amir already spoke about how these identifiers enable tying information together
Re Institutional Policy and Support
The institutions have data management policies and procedures in place for the researchers
Data management plans
Training to early career researchers
They provide data stores and metadata catalogs which means they can keep track of the research outputs being produced
Not only on each of the separate types but also the links between the outputs and exposing what their researchers are working on.
Not many of these are trusted data repositories yet
They can use this to feed information to the national discovery service Research Data Australia
To tie all this information together there is a growing uptake of persistent identifiers
ORCIDs for contributors (we have encouraged the uptake and use of ORCIDs to unambiguously identify the contributors
Using DOIs to identify data, for software and publications
Using IGSNs for samples
Grant IDs for grants from the ARC and NHMRC
Research Activity IDs to tie together outputs, contributors and activities that are taking place under a research activity
Adrian and Amir already spoke about how these identifiers enable tying information together
To tie all this information together there is a growing uptake of persistent identifiers
ORCIDs for contributors (we have encouraged the uptake and use of ORCIDs to unambiguously identify the contributors
Using DOIs to identify data, for software and publications
Using IGSNs for samples
Grant IDs for grants from the ARC and NHMRC
Research Activity IDs to tie together outputs, contributors and activities that are taking place under a research activity
Adrian and Amir already spoke about how these identifiers enable tying information together
And to support researchers in their endeavours there are skilled support staff, this includes data librarians, data stewards, software engineers
They are being supported in various ways, we are providing training and resources to them directly to better understand research data management and the FAIR data principles.
This includes the 23 Research Data things course we ran last year.
This year we have been raising awareness for the FAIR data principles. This includes the recently released FAIR data self assessment tool and collecting and presenting training resources in FAIR,
We are also facilitating national communities in the area of provenance, software citation, data services, data management plans, etc
We are also running Train the Trainer courses on RDM101 which will train the trainers that will in turn train the Early career researchers in proper data management and FAIR data sharing. We will be developing a kit of training resources that institutions can re-use.
So all in all there are a number of the pieces of the puzzle in place, the ongoing task is to make these all fit together seamlessly so publishing FAIR data and software and other research outputs will be as easy as possible and provide the greatest benefits.