Lab Notebooks as Data Management (SLA Winter Virtual Conference 2012)Kristin Briney
This talk, aimed at librarians, describes the data management issues surrounding paper and electronic lab notebooks. It offers several ways for librarians to support good practices and the transition from paper to electronic.
This slideshow was used in a research data management planning course taught at IT Services, University of Oxford, on 2017-02-01. It provides an overview of the elements of a data management plan, plus an introduction to some tools that can be used to build one. (The presentation has been very slightly edited: references to resources provided to course participants have been replaced with web links.)
This slideshow was used in an Introduction to Research Data Management course taught for the Mathematical, Physical and Life Sciences Division, University of Oxford, on 2017-02-15. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.
An introductory talk for librarians on why laboratory notebooks are a critical tool for data management in scientific research. I also suggest ways that academic librarians can help scientists better manage their data in this area.
Lab Notebooks as Data Management (SLA Winter Virtual Conference 2012)Kristin Briney
This talk, aimed at librarians, describes the data management issues surrounding paper and electronic lab notebooks. It offers several ways for librarians to support good practices and the transition from paper to electronic.
This slideshow was used in a research data management planning course taught at IT Services, University of Oxford, on 2017-02-01. It provides an overview of the elements of a data management plan, plus an introduction to some tools that can be used to build one. (The presentation has been very slightly edited: references to resources provided to course participants have been replaced with web links.)
This slideshow was used in an Introduction to Research Data Management course taught for the Mathematical, Physical and Life Sciences Division, University of Oxford, on 2017-02-15. It provides an overview of some key issues, looking at both day-to-day data management, and longer term issues, including sharing, and curation.
An introductory talk for librarians on why laboratory notebooks are a critical tool for data management in scientific research. I also suggest ways that academic librarians can help scientists better manage their data in this area.
Benchmarking Domain-specific Expert Search using Workshop Program CommitteesToine Bogers
Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets.
Presented at CSTA workshop, CIKM 2013,
October 28, 2013
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Learning to Curate Research Data
Jennifer Doty, Research Data Librarian, Emory Center for Digital Scholarship, Emory University, Robert W. Woodruff Library
Reproducibility in human cognitive neuroimaging: a community-driven data sha...Nolan Nichols
Access to primary data and the provenance of derived data are increasingly recognized as an essential aspect of reproducibility in biomedical research. While productive data sharing has become the norm in some biomedical communities, human brain imaging has lagged in open data and descriptions of provenance. The overarching goal of my dissertation was to identify barriers to neuroimaging data sharing and to develop a fundamentally new, granular data exchange standard that incorporates provenance as a primitive to document cognitive neuroimaging workflow.
For my dissertation research, I led the development of the Neuroimaging Data Model (NIDM), an extension to the W3C PROV standard for the domain of human brain imaging. NIDM provides a language to communicate provenance by representing primary data, computational workflow, and derived data as bundles of linked Agents, Activities, and Entities. Similar to the way a sentence conveys a standalone thought, a bundle contains provenance statements that parsimoniously express the way a given piece of data was produced. To demonstrate a system that implements NIDM, I developed a modern, semantic Web application platform that provides neuroimaging workflow as a service and captures provenance statements as NIDM bundles. The course of this work necessitated interaction with an international community, which adopted and extended central elements of this work into prevailing brain imaging software. My dissertation contributes neuroinformatics standards to advance the current state of computational infrastructure available to the cognitive neuroimaging community.
OU Library Research Support webinar: Working with research dataIzzyChad
Slides from a webinar delivered on 31st January 2018 for OU research staff and students. Covers practical strategies for managing research data, including policies, file naming, information security, metadata and working with sensitive data.
Many of us data science and business analytics practitioners perform research and analysis for decision makers on a regular basis. The deliverable of such analysis often results in a Power Point presentation, and/or a model that needs to be productionalized. The code used to produce the analysis also needs to be considered a deliverable.
Many of us perform analysis without reproducibility in mind. With the increasing democratization of data, it is becoming more and more important for people that may not have scientific training to be able to create analysis that can be picked up by somebody else who can then reproduce your results. That, and creating reproducible research is just solid science.
We are going to spend an evening walking though the various tools available to create reproducible research on Big Data. You will get introduced to the Tidyverse of R packages and how to use them. We will discuss the ins and outs of various notebook technologies like Jupyter, and Zeppelin. You will have an opportunity to learn how to get up and running with R and Spark and the various options you have to learn on real clusters instead of just your local environment. There also be a quick introduction to source control and the various options you have around using Git.
The theme of the evening will be “getting started”. We will go over various training resources and show you the optimal path to go from zero to master. Some commentary will be provided around the current state of the job market and intel from the front lines of the data science language wars. This is a large topic and the evening will be fairly dynamic and responsive to the needs of the audience.
Bob Wakefield has spent the better part of 16 years building data systems for many organizations across various industries. He has been running Hadoop in a lab environment for 3 years. He is the principal of Mass Street Analytics, LLC a boutique data consultancy. Mass Street is a Hortonworks Consultant Partner and Confluent Partner.
In his spare time, he likes to work on an equity investment application that combines various sources of information to automatically arrive at investing decisions. When he is not doing that, you’ll find him flying his A-10 simulator. Full CV can be found here: https://www.linkedin.com/in/bobwakefieldmba/
Making qualitative analysis more transparent by using NVivoQSR International
Getting started on your qualitative study, but unsure of what a “solid and reliable” analytic process might look like? Tired of fluffy “methods” sections in journal articles that fail to describe what the authors actually did in their analysis? Then focus on procedures and techniques to make your qualitative data analysis more transparent and replicable using NVivo.
I did not create this. It was created by Laura Bergells and is an excellent presentation. All I have done to to upload it here, Laura gets all of the credit for it.
How to write an effective research paperVidhyambikaSR
Covers everything from understanding what a research paper is, to exploring the various types of research papers. Learn how to choose a compelling topic and write an engaging manuscript that not only presents innovative ideas but also reaches a broad audience. Additionally, get insights on publishing your paper in the right journal or conference, all in a concise and clear manner.
What -IoT
Why - IoT
Why - IoT
IoT is enabling Technology to ML, DL, AI and Data Science
Applications
IoT Product Development – Entrepreneurs
Research Gap
Online Tools
Benchmarking Domain-specific Expert Search using Workshop Program CommitteesToine Bogers
Traditionally, relevance assessments for expert search have been gathered through self-assessment or based on the opinions of co-workers. We introduce three benchmark datasets for expert search that use conference workshops for relevance assessment. Our data sets cover entire research domains as opposed to single institutions. In addition, they provide a larger number of topic-person associations and allow a more objective and fine-grained evaluation of expertise than existing data sets do. We present and discuss baseline results for a language modelling and a topic-centric approach to expert search. We find that the topic-centric approach achieves the best results on domain-specific datasets.
Presented at CSTA workshop, CIKM 2013,
October 28, 2013
February 18 2015 NISO Virtual Conference Scientific Data Management: Caring for Your Institution and its Intellectual Wealth
Learning to Curate Research Data
Jennifer Doty, Research Data Librarian, Emory Center for Digital Scholarship, Emory University, Robert W. Woodruff Library
Reproducibility in human cognitive neuroimaging: a community-driven data sha...Nolan Nichols
Access to primary data and the provenance of derived data are increasingly recognized as an essential aspect of reproducibility in biomedical research. While productive data sharing has become the norm in some biomedical communities, human brain imaging has lagged in open data and descriptions of provenance. The overarching goal of my dissertation was to identify barriers to neuroimaging data sharing and to develop a fundamentally new, granular data exchange standard that incorporates provenance as a primitive to document cognitive neuroimaging workflow.
For my dissertation research, I led the development of the Neuroimaging Data Model (NIDM), an extension to the W3C PROV standard for the domain of human brain imaging. NIDM provides a language to communicate provenance by representing primary data, computational workflow, and derived data as bundles of linked Agents, Activities, and Entities. Similar to the way a sentence conveys a standalone thought, a bundle contains provenance statements that parsimoniously express the way a given piece of data was produced. To demonstrate a system that implements NIDM, I developed a modern, semantic Web application platform that provides neuroimaging workflow as a service and captures provenance statements as NIDM bundles. The course of this work necessitated interaction with an international community, which adopted and extended central elements of this work into prevailing brain imaging software. My dissertation contributes neuroinformatics standards to advance the current state of computational infrastructure available to the cognitive neuroimaging community.
OU Library Research Support webinar: Working with research dataIzzyChad
Slides from a webinar delivered on 31st January 2018 for OU research staff and students. Covers practical strategies for managing research data, including policies, file naming, information security, metadata and working with sensitive data.
Many of us data science and business analytics practitioners perform research and analysis for decision makers on a regular basis. The deliverable of such analysis often results in a Power Point presentation, and/or a model that needs to be productionalized. The code used to produce the analysis also needs to be considered a deliverable.
Many of us perform analysis without reproducibility in mind. With the increasing democratization of data, it is becoming more and more important for people that may not have scientific training to be able to create analysis that can be picked up by somebody else who can then reproduce your results. That, and creating reproducible research is just solid science.
We are going to spend an evening walking though the various tools available to create reproducible research on Big Data. You will get introduced to the Tidyverse of R packages and how to use them. We will discuss the ins and outs of various notebook technologies like Jupyter, and Zeppelin. You will have an opportunity to learn how to get up and running with R and Spark and the various options you have to learn on real clusters instead of just your local environment. There also be a quick introduction to source control and the various options you have around using Git.
The theme of the evening will be “getting started”. We will go over various training resources and show you the optimal path to go from zero to master. Some commentary will be provided around the current state of the job market and intel from the front lines of the data science language wars. This is a large topic and the evening will be fairly dynamic and responsive to the needs of the audience.
Bob Wakefield has spent the better part of 16 years building data systems for many organizations across various industries. He has been running Hadoop in a lab environment for 3 years. He is the principal of Mass Street Analytics, LLC a boutique data consultancy. Mass Street is a Hortonworks Consultant Partner and Confluent Partner.
In his spare time, he likes to work on an equity investment application that combines various sources of information to automatically arrive at investing decisions. When he is not doing that, you’ll find him flying his A-10 simulator. Full CV can be found here: https://www.linkedin.com/in/bobwakefieldmba/
Making qualitative analysis more transparent by using NVivoQSR International
Getting started on your qualitative study, but unsure of what a “solid and reliable” analytic process might look like? Tired of fluffy “methods” sections in journal articles that fail to describe what the authors actually did in their analysis? Then focus on procedures and techniques to make your qualitative data analysis more transparent and replicable using NVivo.
I did not create this. It was created by Laura Bergells and is an excellent presentation. All I have done to to upload it here, Laura gets all of the credit for it.
How to write an effective research paperVidhyambikaSR
Covers everything from understanding what a research paper is, to exploring the various types of research papers. Learn how to choose a compelling topic and write an engaging manuscript that not only presents innovative ideas but also reaches a broad audience. Additionally, get insights on publishing your paper in the right journal or conference, all in a concise and clear manner.
What -IoT
Why - IoT
Why - IoT
IoT is enabling Technology to ML, DL, AI and Data Science
Applications
IoT Product Development – Entrepreneurs
Research Gap
Online Tools
Linux commands working with file contents:
head, tail, cat, tac, more, less and strings, more file
attributes: hard links, symbolic links, fins, umask
and inodes The Linux file tree: the root directory, binary
directories, configuration directories, data
directories, Commands and arguments: $PATH,
echo, ls, env
Discussed on
Introduction to Linux: Linux history,
distributions, licensing, Linux commands: man
pages, commands working with directories,
absolute and relative paths
commands working with files: file, touch, rm, cp,
mv and rename, general purpose utilities: cal,
date, script, who, tty, pwd, ps, uname
Discussed about
An overview – Object basics – Object state and properties – Behavior – Methods – Messages –
Information hiding – Class hierarchy – Relationships – Associations – Aggregations- Identity –
Dynamic binding – Persistence – Metaclasses – Object oriented system development life cycle.
Discussed about:
A Short History of Business Models
The Business Model Canvas
Who is the Business Model for
Models
Funding an IoT Start-up
Lean Start-ups
Discussed about the following topics: A Web Security Forensic Lesson
Web Languages
Introduction to different web attacks
overview of n-tier web applications
Web servers
Apache
IIS
Database Servers
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
How to publish your research work
1. A Free Webinar
on
How to Publish your Research work
From Copper Strip to Gold Bar
Vikram Neerugatti
Technical Head,
Harmonizer Solutions.
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 1
2. Credits
• Prof. Rama Mohan Reddy A (My Research Supervisor)
• ARMR – Scholars (my co-scholars)
• Family
• Google
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 2
3. Content
• About Us
• Training
• List of Courses
• Research Methodology
• Participants
• Conclusion
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 3
5. Training
• Collaboration with NSIC
• Online or offline
• Expert
• Real Time work
• Hands on Training
• Certificate
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 5
6. List of Courses
• Machine Learning
• Artificial Intelligence
• Deep Learning
• Internet of Things
• Data Science
• Big data Analytics
• Research Methodology
• Power Quality and many more
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 6
7. Research
• Research
• “The systematic investigation into and study of materials and sources
in order to establish facts and reach new conclusions” – oxford
• “Research is a systematic inquiry to describe, explain, predict, and
control the observed phenomenon”-questionpro
• “Research is work that involves studying something and trying to
discover facts about it” -collins
• Evidence based research
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 7
8. Why to publish your Research work
• Why to publish
• Idea
• Sharing-food
• Society
• Carrier growth
• Passion
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 8
9. Who can Publish
• Any individual
• Students
• Scholars
• Employees/Employers
• Research and Development
• Entrepreneurs (start a new Company)
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 9
10. Where to publish
• Idea/problem/solution/facts
• Publish-share
• Conference
• Journals
• Magazines
• Book chapters
• Book
• Patent
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 10
11. How to publish your Research work
• Idea/problem/solution/facts-IoT
• SLR-Time Process
• Paper Sources-IEEE
• Collect Papers-IoT
• Read-3 pass-Security
• Clusters-Different Layers
• Select one cluster-RPL
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 11
12. How to publish your Research work
• Final Cluster-RPL
• Collect all papers on RPL
• References
• Conclusion & Future work
• Validate the research of others
• Compare
• Idea-our work (with evidence)- both problem and Solution
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 12
13. Write a Research paper
• Your idea with evidence
• Check already existing papers-structure of paper
• Everyone can understand- lay man
• Base paper
• Identify the relevant source
• Follow the source rules – change accordingly
• Communicate with source
• Answer reviews and get published
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 13
14. Course outline
• Identify Sources-subscriptions
• Collecting papers
• How to read a research paper
• Identifying clusters
• Identifying sub-cluster
• Problem formulation
• Drawing solutions with evidence
• How to write a Paper
• Publishing by attending reviews
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 14
15. Hands on Training
• On their own research area
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 15
16. Example
• IoT
• IEEE
• Cooja Simulator
• Node RED
• Aurduino/NodeMCU
• Rasberry pi
• Sensors/actuators
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 16
17. My Phd Work (IoT)
• Vikram Neerugatti
--------------------------------------------------
View my research on my SSRN Author page:
• https://www.scopus.com/authid/detail.uri?authorId=57204562941
https://ssrn.com/author=3235464
• https://scholar.google.co.in/citations?user=xhyqsDsAAAAJ&hl=en#
--------------------------------------------------
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 17
18. Summary
• About Us
• Training
• List of Courses
• Machine Learning
• Participants
• Students
• Research
• To Read and Write a paper
• Publish a paper
Vikram Neerugatti, Technical Head, Harmonizer Solutions. 18
