Slides presented at the AMEE Virtual Conference 2021, introducing the MedEdPublish platform and data policies. Approaches to sharing sensitive human data, and particulary qualitative data, are discussed.
Managing Ireland's Research Data - 3 Research MethodsRebecca Grant
Slides providing an overview of the research methods used in the author's thesis, "Managing Ireland's Research Data: Recognising Roles for Recordkeepers". The methods discussed are online surveys, comparative case studies, and autoethnography.
Licensed as CC-BY.
Research in the time of Covid: Surveying impacts on Early Career ResearchersRebecca Grant
Based on a survey of over 4,500 researchers published in the white paper The State of Open Data 2020, this session will explore the impacts of the pandemic on early career reearchers (ECRs), their research practice, and how they interact with open data. We will discuss the specific challenges reported by ECRs, as well as the gaps in training and support that they have identified that would encourage their sharing and reuse of research data.
Presentation at the E-ARMA conference 2021.
Do Open data badges influence author behaviour? A case study at Springer NatureRebecca Grant
Digital badges have previously been shown to incentivise journal authors to share their data openly. In this paper we introduce an Open data badging project at the Springer Nature journal BMC Microbiology. The development of the Open data badge is described, as well as the challenges of developing standard badging criteria and ensuring authors’ awareness of the badges. Next steps for the badging project are outlined, which are based on the experiences of the team assessing the badges, the number of badges awarded at the journal to date, and the results of an author survey.
Workshop - finding and accessing data - Cambridge August 22 2016Fiona Nielsen
Finding and accessing human genomic data for research
University of Cambridge, United Kingdom | Seminar Room G
Monday, 22 August 2016 from 10:00 to 12:00 (BST)
Charlotte, Nadia and Fiona presented an overview of data sources around the world where you can find genomics data for your research and gave examples of the data access application for dbGaP and EGA with specific details relevant for University of Cambridge researchers.
CINECA webinar slides: Making cohort data FAIRCINECAProject
Cohort studies, which recruit groups of individuals who share common characteristics and follow them over a period of time, are a robust and essential method in biomedical research for understanding the links between risk factors and diseases. Through questionnaires, medical assessments, and other interactions, voluminous and complex data are collected about the study participants. While cohort studies present a treasure trove of data, the data is often not FAIR (findable, accessible, interoperable and reusable). First, due to the sensitive and private nature of medical information, cohort data are often access controlled. Due to the lack of information about the studies (metadata), often one needs to dig deep to know what data is available in a cohort study. Therefore, many cohort datasets suffer from the findable and accessible issues. Second, often data collection is performed with instruments and data specifications tailored to the study. As a result, combining data across cohorts, even ones with similar characteristics, is difficult, making interoperability and reusability a challenge. In this presentation, we will explore several informatics techniques, such as the use of ontology, to make cohort data more FAIR. We will also consider the implications of making cohort data more open and the ethical and governance issues associated with open science benefit sharing.
This webinar is part of the “How FAIR are you” webinar series and hackathon, which aim at increasing and facilitating the uptake of FAIR approaches into software, training materials and cohort data, to facilitate responsible and ethical data and resource sharing and implementation of federated applications for data analysis.
The CINECA webinar series aims to discuss ways to address common challenges and share best practices in the field of cohort data analysis, as well as distribute CINECA project results. All CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing. CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions.
This webinar took place on 17th February 2021 and is part of the CINECA webinar series.
For previous and upcoming CINECA webinars see:
https://www.cineca-project.eu/webinars
CINECA webinar slides: Open science through fair health data networks dream o...CINECAProject
Since the FAIR data principles were published in 2016, many organizations including science funders and governments have adopted these principles to promote and foster true open science collaborations. However, to define a vision and create a video of a Personal Health Train that leverages worldwide FAIR health data in a federated manner is one step. To actually make this happen at scale and be able to show new scientific and medical insights for it is quite another!
In this webinar, we will dive into the basics of FAIR health data, but also take stock of the current situation in health data networks: after a year of frantic research and collaborations and many open datasets and hackathons on COVID-19, has the situation actually improved? Are we sharing health data on a global scale to improve medical practice, or is quality medical data still only accessible to researchers with the right credentials and deep pockets?
This webinar is part of the “How FAIR are you” webinar series and hackathon, which aim at increasing and facilitating the uptake of FAIR approaches into software, training materials and cohort data, to facilitate responsible and ethical data and resource sharing and implementation of federated applications for data analysis.
The CINECA webinar series aims to discuss ways to address common challenges and share best practices in the field of cohort data analysis, as well as distribute CINECA project results. All CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing. CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions.
This webinar took place on 21st January 2021 and is part of the CINECA webinar series.
For previous and upcoming CINECA webinars see:
https://www.cineca-project.eu/webinars
Paper was presented at European Survey Research Association 2013, in the session Research Data Management for Re-use: Bringing Researchers and Archivists closer.
Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...Tom Plasterer
As scientists in the life sciences we are trained to pursue singular goals around a publication or a validated target or a drug submission. Our failure rates are exceedingly high especially as we move closer to patients in the attempt to collect sufficient clinical evidence to demonstrate the value of novel therapeutics. This wastes resources as well as time for patients depending upon us for the next breakthrough.
Edge Informatics is an approach to ameliorate these failures. Using both technical and social solutions together knowledge can be shared and leveraged across the drug development process. This is accomplished by making data assets discoverable, accessible, self-described, reusable and annotatable. The Open PHACTS project pioneered this approach and has provided a number of the technical and social solutions to enable Edge Informatics. A number of pre-competitive consortia and some content providers have also embraced this approach, facilitating networks of collaborators within and outside a given organization. When taken together more accurate, timely and inclusive decision-making is fostered.
Managing Ireland's Research Data - 3 Research MethodsRebecca Grant
Slides providing an overview of the research methods used in the author's thesis, "Managing Ireland's Research Data: Recognising Roles for Recordkeepers". The methods discussed are online surveys, comparative case studies, and autoethnography.
Licensed as CC-BY.
Research in the time of Covid: Surveying impacts on Early Career ResearchersRebecca Grant
Based on a survey of over 4,500 researchers published in the white paper The State of Open Data 2020, this session will explore the impacts of the pandemic on early career reearchers (ECRs), their research practice, and how they interact with open data. We will discuss the specific challenges reported by ECRs, as well as the gaps in training and support that they have identified that would encourage their sharing and reuse of research data.
Presentation at the E-ARMA conference 2021.
Do Open data badges influence author behaviour? A case study at Springer NatureRebecca Grant
Digital badges have previously been shown to incentivise journal authors to share their data openly. In this paper we introduce an Open data badging project at the Springer Nature journal BMC Microbiology. The development of the Open data badge is described, as well as the challenges of developing standard badging criteria and ensuring authors’ awareness of the badges. Next steps for the badging project are outlined, which are based on the experiences of the team assessing the badges, the number of badges awarded at the journal to date, and the results of an author survey.
Workshop - finding and accessing data - Cambridge August 22 2016Fiona Nielsen
Finding and accessing human genomic data for research
University of Cambridge, United Kingdom | Seminar Room G
Monday, 22 August 2016 from 10:00 to 12:00 (BST)
Charlotte, Nadia and Fiona presented an overview of data sources around the world where you can find genomics data for your research and gave examples of the data access application for dbGaP and EGA with specific details relevant for University of Cambridge researchers.
CINECA webinar slides: Making cohort data FAIRCINECAProject
Cohort studies, which recruit groups of individuals who share common characteristics and follow them over a period of time, are a robust and essential method in biomedical research for understanding the links between risk factors and diseases. Through questionnaires, medical assessments, and other interactions, voluminous and complex data are collected about the study participants. While cohort studies present a treasure trove of data, the data is often not FAIR (findable, accessible, interoperable and reusable). First, due to the sensitive and private nature of medical information, cohort data are often access controlled. Due to the lack of information about the studies (metadata), often one needs to dig deep to know what data is available in a cohort study. Therefore, many cohort datasets suffer from the findable and accessible issues. Second, often data collection is performed with instruments and data specifications tailored to the study. As a result, combining data across cohorts, even ones with similar characteristics, is difficult, making interoperability and reusability a challenge. In this presentation, we will explore several informatics techniques, such as the use of ontology, to make cohort data more FAIR. We will also consider the implications of making cohort data more open and the ethical and governance issues associated with open science benefit sharing.
This webinar is part of the “How FAIR are you” webinar series and hackathon, which aim at increasing and facilitating the uptake of FAIR approaches into software, training materials and cohort data, to facilitate responsible and ethical data and resource sharing and implementation of federated applications for data analysis.
The CINECA webinar series aims to discuss ways to address common challenges and share best practices in the field of cohort data analysis, as well as distribute CINECA project results. All CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing. CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions.
This webinar took place on 17th February 2021 and is part of the CINECA webinar series.
For previous and upcoming CINECA webinars see:
https://www.cineca-project.eu/webinars
CINECA webinar slides: Open science through fair health data networks dream o...CINECAProject
Since the FAIR data principles were published in 2016, many organizations including science funders and governments have adopted these principles to promote and foster true open science collaborations. However, to define a vision and create a video of a Personal Health Train that leverages worldwide FAIR health data in a federated manner is one step. To actually make this happen at scale and be able to show new scientific and medical insights for it is quite another!
In this webinar, we will dive into the basics of FAIR health data, but also take stock of the current situation in health data networks: after a year of frantic research and collaborations and many open datasets and hackathons on COVID-19, has the situation actually improved? Are we sharing health data on a global scale to improve medical practice, or is quality medical data still only accessible to researchers with the right credentials and deep pockets?
This webinar is part of the “How FAIR are you” webinar series and hackathon, which aim at increasing and facilitating the uptake of FAIR approaches into software, training materials and cohort data, to facilitate responsible and ethical data and resource sharing and implementation of federated applications for data analysis.
The CINECA webinar series aims to discuss ways to address common challenges and share best practices in the field of cohort data analysis, as well as distribute CINECA project results. All CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions. Please note that all webinars are recorded and available for posterior viewing. CINECA webinars include an audience Q&A session during which attendees can ask questions and make suggestions.
This webinar took place on 21st January 2021 and is part of the CINECA webinar series.
For previous and upcoming CINECA webinars see:
https://www.cineca-project.eu/webinars
Paper was presented at European Survey Research Association 2013, in the session Research Data Management for Re-use: Bringing Researchers and Archivists closer.
Harnessing Edge Informatics to Accelerate Collaboration in BioPharma (Bio-IT ...Tom Plasterer
As scientists in the life sciences we are trained to pursue singular goals around a publication or a validated target or a drug submission. Our failure rates are exceedingly high especially as we move closer to patients in the attempt to collect sufficient clinical evidence to demonstrate the value of novel therapeutics. This wastes resources as well as time for patients depending upon us for the next breakthrough.
Edge Informatics is an approach to ameliorate these failures. Using both technical and social solutions together knowledge can be shared and leveraged across the drug development process. This is accomplished by making data assets discoverable, accessible, self-described, reusable and annotatable. The Open PHACTS project pioneered this approach and has provided a number of the technical and social solutions to enable Edge Informatics. A number of pre-competitive consortia and some content providers have also embraced this approach, facilitating networks of collaborators within and outside a given organization. When taken together more accurate, timely and inclusive decision-making is fostered.
This seminar discuss the important of the scientific data and how to plan data management and data sharing for your research. Also, discuss the research ethics and privacy in data sharing and intellectual property rights.
Data strategies for collaborative research, how to publish and cite research , and data opportunities and limitations in using other people's research data, illustrated with real-life data reuse cases will be discussed. The ways to share your research data and discuss the advantages and disadvantages for each of these ways of sharing data. The Egyptian 2017 data protection act and its principles. Finally, discuss practicality real cases.
Why study Data Sharing? (+ why share your data)Heather Piwowar
A presentation to the DBMI department at the University of Pittsburgh about data sharing and reuse: what this means, why it is important, some of what we’ve learned, and what we still don’t know.
IDCC Workshop: Analysing DMPs to inform research data services: lessons from ...Amanda Whitmire
A workshop as part of the International Digital Curation Conference 2016 on DMP development and support. This presentation demonstrates how we can use data management plans as a source of information to better understand researcher data stewardship practices and how to support them. Be sure to see the slide notes to better understand the presentation (most slides are just photos/icons).
This slideshow was used in a Preparing Your Research Data for the Future course taught in the Medical Sciences Division, University of Oxford, on 2015-06-08. It provides an overview of some key issues, focusing on long-term data management, sharing, and curation.
FAIR Data Knowledge Graphs–from Theory to PracticeTom Plasterer
FAIR data has flown up the hype curve without a clear sense of return from the required data stewardship investment. The killer use case for FAIR data is a science knowledge graph. It enables you to richly address novel questions of your and the world’s data. We started with data catalogues (findability) which exploited linked/referenced data using a few focused vocabularies (interoperability), for credentialed users (accessibility), with provenance and attribution (reusability) to make this happen. Our processes enable simple creation of dataset records and linking to source data, providing a seamless federated knowledge graph for novice and advanced users alike.
Presented May 7th, 2019 at the Knowledge Graph Conference, Columbia University.
Genome sharing projects around the world nijmegen oct 29 - 2015Fiona Nielsen
Genome sharing projects across the world
Did you ever wonder what happened to the exponential increase in genome sequencing data? It is out there around the world and a lot of it is consented for research use. This means that if you just know where to find the data, you can potentially analyse gigabytes of data to power your research.
In this talk Fiona will present community genome initiatives, the genome sharing projects across the world, how you can benefit from this wealth of data in your work, and how you can boost your academic career by sharing and collaboration.
by Fiona Nielsen, Founder and CEO of DNAdigest and Repositive
With a background in software development Fiona pursued her career in bioinformatics research at Radboud University Nijmegen. Now a scientist-turned-entrepreneur Fiona founded DNAdigest and its social enterprise spin-out Repositive Ltd. Both the charity and company focus on efficient and ethical sharing of genetics data for research to accelerate diagnostics and cures for genetic diseases.
As BioPharma adapts to incorporate nimble networks of suppliers, collaborators, and regulators the ability to link data is critical for dynamic interoperability. Adoption of linked data paradigm allows BioPharma to focus on core business: delivering valuable therapeutics in a timely manner.
Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...Tom Plasterer
Edge Informatics is an approach to accelerate collaboration in the BioPharma pipeline. By combining technical and social solutions knowledge can be shared and leveraged across the multiple internal and external silos participating in the drug development process. This is accomplished by making data assets findable, accessible, interoperable and reusable (FAIR). Public consortia and internal efforts embracing FAIR data and Edge Informatics are highlighted, in both preclinical and clinical domains.
This talk was presented at the Molecular Medicine Tri-Conference in San Francisco, CA on February 20, 2017
Presentation to IASSIST 2013, in the session Expanding Scholarship: Research Journals and Data Linkages. Describes PREPARDE workshop on repository accreditation for data publication and invites comments on guidelines.
Our regular Introduction to Data Management (DM) workshop (90-minutes). Covers very basic DM topics and concepts. Audience is graduate students from all disciplines. Most of the content is in the NOTES FIELD.
This is an update on the status of federal requirements for data sharing in 2015. These slides were presented at ACRL in Portland in March 2015, by Linda Detterman and Jared Lyle of ICPSR, based at the University of Michigan. The session includes overviews of federal requirements, data curation, data management plans, data sharing services, and lots of fun!
Lesson 8 in a set of 10 created by DataONE on Best Practices for Data Management. The full module can be downloaded from the DataONE.org website at: http://www.dataone.org/educaiton-modules. Released under a CC0 license, attribution and citation requested.
Introduction to research data managementdri_ireland
An Introduction to Research Data Management: slides from a presentation given online on May 12 2022, by Beth Knazook, Project Manager, Research Data. Covers topics such as: what are research data; why share research data; why DMPs are important; and where should you share your data?
Presentation given by Kate LeMay at the 'Sharing Health-y Data: Challenges and Solutions' workshop, held at The Menzies Research Institute (Hobart, Tasmania) on 28th June 2016. The event was co-hosted by ANDS and the University of Tasmania library
This seminar discuss the important of the scientific data and how to plan data management and data sharing for your research. Also, discuss the research ethics and privacy in data sharing and intellectual property rights.
Data strategies for collaborative research, how to publish and cite research , and data opportunities and limitations in using other people's research data, illustrated with real-life data reuse cases will be discussed. The ways to share your research data and discuss the advantages and disadvantages for each of these ways of sharing data. The Egyptian 2017 data protection act and its principles. Finally, discuss practicality real cases.
Why study Data Sharing? (+ why share your data)Heather Piwowar
A presentation to the DBMI department at the University of Pittsburgh about data sharing and reuse: what this means, why it is important, some of what we’ve learned, and what we still don’t know.
IDCC Workshop: Analysing DMPs to inform research data services: lessons from ...Amanda Whitmire
A workshop as part of the International Digital Curation Conference 2016 on DMP development and support. This presentation demonstrates how we can use data management plans as a source of information to better understand researcher data stewardship practices and how to support them. Be sure to see the slide notes to better understand the presentation (most slides are just photos/icons).
This slideshow was used in a Preparing Your Research Data for the Future course taught in the Medical Sciences Division, University of Oxford, on 2015-06-08. It provides an overview of some key issues, focusing on long-term data management, sharing, and curation.
FAIR Data Knowledge Graphs–from Theory to PracticeTom Plasterer
FAIR data has flown up the hype curve without a clear sense of return from the required data stewardship investment. The killer use case for FAIR data is a science knowledge graph. It enables you to richly address novel questions of your and the world’s data. We started with data catalogues (findability) which exploited linked/referenced data using a few focused vocabularies (interoperability), for credentialed users (accessibility), with provenance and attribution (reusability) to make this happen. Our processes enable simple creation of dataset records and linking to source data, providing a seamless federated knowledge graph for novice and advanced users alike.
Presented May 7th, 2019 at the Knowledge Graph Conference, Columbia University.
Genome sharing projects around the world nijmegen oct 29 - 2015Fiona Nielsen
Genome sharing projects across the world
Did you ever wonder what happened to the exponential increase in genome sequencing data? It is out there around the world and a lot of it is consented for research use. This means that if you just know where to find the data, you can potentially analyse gigabytes of data to power your research.
In this talk Fiona will present community genome initiatives, the genome sharing projects across the world, how you can benefit from this wealth of data in your work, and how you can boost your academic career by sharing and collaboration.
by Fiona Nielsen, Founder and CEO of DNAdigest and Repositive
With a background in software development Fiona pursued her career in bioinformatics research at Radboud University Nijmegen. Now a scientist-turned-entrepreneur Fiona founded DNAdigest and its social enterprise spin-out Repositive Ltd. Both the charity and company focus on efficient and ethical sharing of genetics data for research to accelerate diagnostics and cures for genetic diseases.
As BioPharma adapts to incorporate nimble networks of suppliers, collaborators, and regulators the ability to link data is critical for dynamic interoperability. Adoption of linked data paradigm allows BioPharma to focus on core business: delivering valuable therapeutics in a timely manner.
Edge Informatics and FAIR (Findable, Accessible, Interoperable and Reusable) ...Tom Plasterer
Edge Informatics is an approach to accelerate collaboration in the BioPharma pipeline. By combining technical and social solutions knowledge can be shared and leveraged across the multiple internal and external silos participating in the drug development process. This is accomplished by making data assets findable, accessible, interoperable and reusable (FAIR). Public consortia and internal efforts embracing FAIR data and Edge Informatics are highlighted, in both preclinical and clinical domains.
This talk was presented at the Molecular Medicine Tri-Conference in San Francisco, CA on February 20, 2017
Presentation to IASSIST 2013, in the session Expanding Scholarship: Research Journals and Data Linkages. Describes PREPARDE workshop on repository accreditation for data publication and invites comments on guidelines.
Our regular Introduction to Data Management (DM) workshop (90-minutes). Covers very basic DM topics and concepts. Audience is graduate students from all disciplines. Most of the content is in the NOTES FIELD.
This is an update on the status of federal requirements for data sharing in 2015. These slides were presented at ACRL in Portland in March 2015, by Linda Detterman and Jared Lyle of ICPSR, based at the University of Michigan. The session includes overviews of federal requirements, data curation, data management plans, data sharing services, and lots of fun!
Lesson 8 in a set of 10 created by DataONE on Best Practices for Data Management. The full module can be downloaded from the DataONE.org website at: http://www.dataone.org/educaiton-modules. Released under a CC0 license, attribution and citation requested.
Introduction to research data managementdri_ireland
An Introduction to Research Data Management: slides from a presentation given online on May 12 2022, by Beth Knazook, Project Manager, Research Data. Covers topics such as: what are research data; why share research data; why DMPs are important; and where should you share your data?
Presentation given by Kate LeMay at the 'Sharing Health-y Data: Challenges and Solutions' workshop, held at The Menzies Research Institute (Hobart, Tasmania) on 28th June 2016. The event was co-hosted by ANDS and the University of Tasmania library
Lesson 2 in a set of 10 created by DataONE on Best Practices fo Data Management. The full module can be downloaded from the DataONE.org website at: http://www.dataone.org/educaiton-modules. Released under a CC0 license, attribution and citation requested.
workshop session delivered alongside 'Making your thesis legal' workshop in July and September 2013 to PhD, MPhil, DrPh students who are completing their thesis. Discusses standards for sharing data, issues that need addressing, formats, data protection, usability, licenses
Presentación de Joy Davidson, Digital Curation Centre (UK) en FOSTER event: Data Management Plan and Social Impact of Research. Universitat Jaume I, 27 mayo 2016
Presentation given by Sarah Jones at a seminar run by LSHTM on 6th November 2012. http://www.lshtm.ac.uk/newsevents/events/2012/11/developing-data-management-expertise-in-research---half-day-event
Preparing your data for sharing and publishingVarsha Khodiyar
Talk given as part of the MRC Cognition and Brain Sciences Unit Open Science Day on 20th November 2018 , University of Cambridge (https://www.eventbrite.co.uk/e/open-science-day-at-the-mrc-cbu-tickets-50363553745)
NIH Grants and Data: New Rules Coming in 2023Erin Owens
Beginning in January 2023, any new applications for funding with the National Institutes of Health (NIH) must now include a Data Management and Sharing Plan (DMSP). Even researchers who don't plan to share their data with others will still be required to submit a plan describing limitations which preclude sharing. Join Professor and Scholarly Communications Librarian Erin Owens for a one-hour overview of what the DMSP is and how to begin developing yours.
Research Transparency in the Social Sciences: DA-RTARDC
Transparency Protects the Legitimacy of Research
Transparency and Openness Promotion (TOP) Guidelines for Journals
What are we afraid of?
What can be gained?
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 7, 2016|...EUDAT
| www.eudat.eu | 1st Session: July 7, 2016.
In this webinar, Sarah Jones (DCC) and Marjan Grootveld (DANS) talked through the aspects that Horizon 2020 requires from a DMP. They discussed examples from real DMPs and also touched upon the Software Management Plan, which for some projects can be a sensible addition
Research Data Management: An Introductory Webinar from OpenAIRE and EUDATTony Ross-Hellauer
OpenAIRE and EUDAT co-present this webinar which aims to introduce researchers and others to the concept of research data management (RDM). As well as presenting the benefits of taking an active approach to research data management – including increased speed and ease of access, efficiency (fund once, reuse many times), and improved quality and transparency of research – the webinar will advise on strategies for successful RDM, resources to help manage data effectively, choosing where to store and deposit data, the EC H2020 Open Data Pilot and the basics of data management, stewardship and archiving.
Webinar recording available: http://www.instantpresenter.com/eifl/EB57D6888147
Research Data Management: An Introductory Webinar from OpenAIRE and EUDATOpenAIRE
OpenAIRE and EUDAT co-present this webinar which aims to introduce researchers and others to the concept of research data management (RDM). As well as presenting the benefits of taking an active approach to research data management – including increased speed and ease of access, efficiency (fund once, reuse many times), and improved quality and transparency of research – the webinar will advise on strategies for successful RDM, resources to help manage data effectively, choosing where to store and deposit data, the EC H2020 Open Data Pilot and the basics of data management, stewardship and archiving.
Webinar recording available: http://www.instantpresenter.com/eifl/EB57D6888147
Aim:- To show how research data management can contribute to the success of your PhD.
*What is research data and why it is important?
*The Research Data lifecycle
* Research Data – more than just your results
* FAIR data and Open Research
* DMP online tool
Similar to Increasing transparency in Medical Education through Open Data (20)
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
Salas, V. (2024) "John of St. Thomas (Poinsot) on the Science of Sacred Theol...Studia Poinsotiana
I Introduction
II Subalternation and Theology
III Theology and Dogmatic Declarations
IV The Mixed Principles of Theology
V Virtual Revelation: The Unity of Theology
VI Theology as a Natural Science
VII Theology’s Certitude
VIII Conclusion
Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
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.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Increasing transparency in Medical Education through Open Data
1. Information Classification: General
Increasing transparency in Medical
Education through Open Data
Dr. Rebecca Grant, Head of Data & Software Publishing, F1000
Prof. Barbara Jennings, MedEdPublish Advisory Board, UEA
Niall Rundle, Portfolio Manager, Taylor & Francis
2. Information Classification: General
• An introduction to MedEdPublish - Why AMEE is moving to a new Platform, and
what opportunities does that allow?
• What is data in Medical Education research?
• Sharing Medical Education data transparently and safely
• Breakout discussion
• Closing statements and next steps
• Q&A session
Today’s session
3. Information Classification: General
Speaker introductions
• Dr. Rebecca Grant, Head of Data & Software
Publishing, F1000
• Prof. Barbara Jennings, MedEdPublish Advisory
Board, UEA
• Niall Rundle, Portfolio Manager, Taylor & Francis
4. Information Classification: General
An Introduction to MedEdPublish
• Articles are peer reviewed AFTER publication #PPPR
• Open approach to peer review that avoids editorial bias and
increases speed of publication
• Promotes scholarship & sharing expertise with colleagues at
all levels
• Online format facilitates comprehensive data presentation
5. Information Classification: General
1. Speed of Publication, world leading
technology and an improved user experience
2. A Platform fully compliant with major funder
mandates including Plan S and DORA
3. The opportunity to expand MedEdPublish
with new content, features and opportunities
4. A continued commitment to openness,
including a new focus on open data…
Why is MedEdPublish moving to a new Platform?
6. Information Classification: General
• MedEdPublish will advocate an Open Data policy. This means all articles should
include citations to repositories that host the data underlying their results, together with
details of any software used to process those results.
• This is so that other researchers can see the raw data, be able to replicate published
studies and analyze the data, as well as in some circumstances, reuse it.
• Others who then reuse this data for their own studies can cite this data (which can be
cited separately from the original article if appropriate).
• Failure to openly provide data for publication without good justification is likely to result
in your article being rejected.
• Exceptions: We recognise that there may be cases where openly sharing data may
not be feasible (due to ethical, data protection or confidentiality considerations), or
because the data have been obtained from a third party and access restrictions apply.
What is the new MedEdPublish data policy?
8. Information Classification: General
Research Data
Data produced for the
purpose of the
reported study
Data produced by
others
Materials produced for
the purposes of the
reported study
Code produced either
as the primary output
or for purposes of
replication
What do we mean by research data?
10. Information Classification: General
Data in Medical Education Research
“Participants completed application forms, pre-
course, post-course and daily evaluation
questionnaires..”
“The participants were asked to experience and
evaluate … and the results were discussed in a
Focus Group Discussion.”
“Anonymous online surveys were distributed..”
“Semi-structured interviews with final year
medical students…”
• Quant, qual or both
• Text, audio, video,
transcripts
• Sensitive topics
discussed
11. Information Classification: General
The challenges of sharing sensitive human data
My participants
didn’t consent to
sharing their data
I’m concerned
about the legal
implications
The topic of my
study is too
sensitive
12. Information Classification: General
The challenges of sharing qualitative data
Where can I
store my data?
How can I
anonymise my
data?
What about my
audio and video
files?
14. Information Classification: General
1. Plan for data sharing in advance
2. Seek consent for sharing from your
participants
3. Anonymise data or shared in a controlled
access repository
4. Describe any sharing limitations in your
data availability statement
How to ensure you can safely share your data
15. Information Classification: General
1. Plan for data sharing in advance
Create a Data Management Plan (DMP) before your research begins
Consider data collection, storage, team roles, discipline specific
guidance and how you will share your data when the project ends
Keep your plan up-to-date as your research progresses
Key benefits:
Comply with funder and institutional policies
Prepare for data sharing and publication from the beginning
Ensure you will have informed consent from participants
16. Information Classification: General
2. Seek consent from your participants
Ensure that your participants can provide informed consent for
future data sharing
Outline any anonymisation or de-identification techniques you will
use, where data will be stored and who will have access
Key benefits:
Assists with compliance with any legal frameworks like GDPR
Necessary in order to share data ethically
17. Information Classification: General
3. Anonymise or store in controlled access repository
Based on your DMP and participant consent you will likely:
• Anonymise the data
• Deposit the data into a controlled access repository
• OR both
Key benefits:
Protects the privacy of your participants and safeguards them from harm
Allows maximum possible reuse of your data by other researchers
18. Information Classification: General
A process which removes information from a dataset so that research
participants can no longer be identified
What does it mean to anonymise data?
Indirect identifiers:
Information which, in combination,
uniquely identifies a research
participant.
Ethnicity +
Sex +
Place of birth +
Job title +
Direct identifiers:
Information which uniquely
identifies a research participant.
Full names
Dates of birth
Address
Phone number
Biometric information
19. Information Classification: General
Key techniques in data anonymisation
Remove the variable (e.g. lat-long, date of birth)
Generalise (e.g. swap an address for a city)
Pseudonymise (e.g. swap names for falsified versions)
Create bands (e.g. age ranges, salary ranges)
21. Information Classification: General
Anonymising qualitative data
Data formats:
Transcripts, focus group
notes and narrative survey
responses are more
difficult to anonymise
Challenging to automate as
meaningful information
may be left in the text
Necessary to indicate
where changes have been
made, e.g. diacritics
Technical challenges:
Audio and video files are
extremely time-consuming
to anonymise
May be useful to include
budget for this in initial
Data Management Plan
Value of data may be lost:
Removal of information
damages the intrinsic value
of the data collected?
22. Information Classification: General
Anonymising qualitative data
Data formats:
Transcripts, focus group
notes and narrative survey
responses are more
difficult to anonymise
Challenging to automate as
meaningful information
may be left in the text
Necessary to indicate
where changes have been
made, e.g. diacritics
Technical challenges:
Audio and video files are
extremely time-consuming
to anonymise
May be useful to include
budget for this in initial
Data Management Plan
Value of data may be lost:
Removal of information
damages the intrinsic value
of the data collected?
Use of controlled
access repository
may be appropriate
23. Information Classification: General
Choosing a data repository
✓ A location on the web for your data to be stored and accessed
✓ Allows you to provide contextual information so that data can be reused
✓ Provides a persistent identifier (e.g. a DOI) so that your data can be cited
✓ Provides peace of mind – data is managed by the repository, not by you
Controlled access repositories:
✓ Do not share data openly on the web
✓ Require certain access conditions to be met by users
✓ Protect participant privacy
✓ May remove need for anonymisation
24. Information Classification: General
Choosing a data repository
Is it used by other researchers in your
discipline?
Does it guarantee storage for
a particular length of time?
What metadata
format does it use?
Is there a cost for
storage?
DOIs?
Is it
recommended?
25. Information Classification: General
The F1000 recommended repositories list
What type of data Which repository
Any Dryad
Any, but especially data in SAV and POR
formats
Dataverse
Any Figshare
Any, but especially deposits with mixed
data and code
Zenodo
Any, but reserved for ISCPR member
institutions
Open ICPSR
Social and economic data UK Data Service
26. Information Classification: General
4. Describe any limitations in your data availability
statement
Your data availability statement:
A required section of your manuscript
Should describe all data underpinning your research and where it can
be found.
If relevant include:
An explanation of why the data is not open;
Links to any intermediary data that can be de-identified without
compromising anonymity;
What, if anything, the relevant Institutional Review Board (IRB) or
equivalent said about data sharing;
Where applicable, all necessary information required for a reader or
reviewer to apply for access to the data and the conditions under which
access will be granted
27. Information Classification: General
Sharing medical education research data
✓ Plan for sharing
✓ Protect your participants and share ethically
✓ Share data appropriately
✓ Explain what you’ve shared (or not shared) and why
Need more help?
https://think.f1000research.com/open-data:
Repositories, licensing, data collections, spreadsheets, writing a data availability statement,
sharing code…
29. Information Classification: General
1. Findable: Include a persistent identifier in your data availability statement,
linking to a data repository.
2. Accessible: Use a recommended data repository that’s accessible on the
web.
3. Interoperable: Use any applicable reporting standards, vocabularies or
ontologies which are common in your discipline.
4. Reusable: Include a standard licence for your data.
Show your data’s “FAIR”-ness
30. Information Classification: General
The benefits of transparent, open data
✓ Boost your credibility – work is replicable and can be validated
✓ Enhance the visibility of your work – both your article and your dataset can be found
by others
✓ Develop a better understanding of your field – support a deeper, richer understanding
of your topic
✓ Progress your career – open data sharing is associated with an increase of
citations to your published paper of up to 25%
*(Colavizza et al., https://doi.org/10.1371/journal.pone.0230416)
31. Information Classification: General
In your breakout groups, please discuss the following and make some notes
to feedback. Take 10 minutes.
• What challenges have you faced in sharing data, or what concerns do you have
if you’ve not done so before?
• Have you identified solutions during today’s session?
• Are there other solutions you require?
Breakout session
32. Information Classification: General
In your breakout discussions explore ideas about sharing data in clinical & educational research.
Open the hyperlink to a padlet forum in a browser & capture your ideas and queries:
www.tinyurl.com/MedEdData
33. Information Classification: General
Breakout feedback
• What challenges have you faced in
sharing data, or what concerns do you
have if you’ve not done so before?
• Have you identified solutions during
today’s session?
• Are there other solutions you require?
35. Information Classification: General
• Submissions to the new Platform are
now open, with the first publications
due October 2021
• The new Platform has a full set of
article guidelines, instructions and
FAQs
• You can visit the URL here, or visit
the current MEP site
How to submit to the new MedEdPublish Platform,
and what’s next?
submission.mededpublish.org
36. Information Classification: General
Final Q&A session
• Do you have any questions about the workshop, publishing
your data or the new MedEdPublish Platform?
• Was this a useful workshop? Are there any areas where we
could have expanded?
• What further resources around data would be helpful for you,
and the wider medical education community?
39. Information Classification: General
The MedEdPublish post-publication
peer review publishing model
Designed to maximise discoverability, reach, use and potential impact
DOI issued
Indexed: Google Scholar
Scopus
PubMed
DOAJ
etc
40. Information Classification: General
• A fully transparent APC
policy, with a breakdown of
the costs for different article
types
• 100% and 50% APC
discounts in place for
authors from HINARI
Band-A and Band B
countries
• 5% discount for all AMEE
members
How much will it cost to publish in MedEdPublish?