The document outlines the research methods group's data management services throughout the entire research lifecycle from proposal stage to grant closeout. It details the steps taken to establish data outputs monitoring including a database to track projects, regions, years of published datasets and their status. It also lists what is still needed such as establishing clear data policies, ethical committees, and changing institutional culture to fully support open access to research data.
FAIR - Working Data - It's not just about FAIR publishing. Presented by John Morrissey from CSIRO at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management 31 may 2018 in Melbourne
How to get there from here- Research data Managment training. presented by Sue Cook, CSIRO, at the C3DIS post conference workshop; Managed data – trusted research: an introduction to Research Data Management in Melbourne 31st May 2018
Introduction to research data management. Presented by Natasha Simons at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management, Melbourne 31st may 2018
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.
This document summarizes a training session on data management. The objectives are to describe different data capture tools, document data using available tools, evaluate tools for research, and learn GPS and GIS data capture tools. It discusses the importance of effective data management and having a data management plan. It also covers factors to consider when selecting data collection tools, and introduces several mobile data collection tools including ODK, KoBo Toolbox, and Survey CTO.
Presentation given at the Indiana University School of Medicine's Ruth Lilly Medical Library. Contains information and resources specific to Indiana University Purdue University Indianapolis (IUPUI). For full class materials, see LYD17_IUPUIWorkshop folder here: https://osf.io/r8tht/.
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
The document outlines the research methods group's data management services throughout the entire research lifecycle from proposal stage to grant closeout. It details the steps taken to establish data outputs monitoring including a database to track projects, regions, years of published datasets and their status. It also lists what is still needed such as establishing clear data policies, ethical committees, and changing institutional culture to fully support open access to research data.
FAIR - Working Data - It's not just about FAIR publishing. Presented by John Morrissey from CSIRO at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management 31 may 2018 in Melbourne
How to get there from here- Research data Managment training. presented by Sue Cook, CSIRO, at the C3DIS post conference workshop; Managed data – trusted research: an introduction to Research Data Management in Melbourne 31st May 2018
Introduction to research data management. Presented by Natasha Simons at the C3DIS post conference workshop: Managed data – trusted research: an introduction to Research Data Management, Melbourne 31st may 2018
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.
This document summarizes a training session on data management. The objectives are to describe different data capture tools, document data using available tools, evaluate tools for research, and learn GPS and GIS data capture tools. It discusses the importance of effective data management and having a data management plan. It also covers factors to consider when selecting data collection tools, and introduces several mobile data collection tools including ODK, KoBo Toolbox, and Survey CTO.
Presentation given at the Indiana University School of Medicine's Ruth Lilly Medical Library. Contains information and resources specific to Indiana University Purdue University Indianapolis (IUPUI). For full class materials, see LYD17_IUPUIWorkshop folder here: https://osf.io/r8tht/.
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
Presentation given by Anne Spalding, KAPTUR Project Officer for University for the Creative Arts as part of the UCA RDM training workshop given on 16th January 2013.
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.
This document outlines best practices for creating research data. [1] It recommends using consistent data organization with standardized formats and descriptive file names. [2] Researchers should perform quality assurance checks and use scripted programs to analyze data while keeping notes. [3] All aspects of data collection and analysis should be thoroughly documented. Following these practices will improve data usability, sharing, and reproducibility.
This document discusses best practices for data management for research. It covers topics such as file organization, documentation, storage, sharing and publishing data, and archiving. Good practices include using file naming conventions and open formats, documenting projects, processes, and data, making backups in multiple locations, and publishing and archiving data in repositories to enable access and preservation. Data management is important for research reproducibility, sharing, and complying with funder requirements.
Webinar: Data management and the Open Research Data Pilot in Horizon 2020OpenAccessBelgium
This webinar provides information about strategies for successful Research Data Management, 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.
At the end of the session participants will be able to:
- Understand the basic principles and importance of RDM
- Set clear goals regarding data curation, preservation and sharing
- Comply with the requirements of the Research Data Pilot
- Draft a Data Management Plan
- Identify RDM resources and tools
Incentivising the uptake of reusable metadata in the survey production processLouise Corti
This document discusses incentivizing the uptake of reusable metadata in survey production. It notes that there is no universal language used to document survey questions and variables, leading to wasted resources. The Data Documentation Initiative (DDI) is proposed as a standard. Barriers to adopting metadata best practices include legacy systems, manual processes, and reluctance to change. The document outlines ideas to incentivize metadata use such as specifying documentation requirements in funding calls and improving documentation tools and workflows. Showing tangible benefits through applications like question banks and data exploration systems is also suggested.
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 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.
Data Management Lab: Session 4 Review OutlineIUPUI
Data Management Lab: Session 4 Review Outline (more details at http://ulib.iupui.edu/digitalscholarship/dataservices/datamgmtlab)
What you will learn:
1. Build awareness of research data management issues associated with digital data.
2. Introduce methods to address common data management issues and facilitate data integrity.
3. Introduce institutional resources supporting effective data management methods.
4. Build proficiency in applying these methods.
5. Build strategic skills that enable attendees to solve new data management problems.
This document discusses research data in the context of visual arts research. It defines research data, discusses its importance and challenges in the visual arts domain. Key points covered include the heterogeneous nature of visual arts data, principles of data curation and preservation, and the need for data management planning and assistance with archiving. Examples of types of visual arts research data are provided.
The document summarizes the Jisc Managing Research Data Programme which aims to support universities in improving research data management. It discusses why managing research data is important, highlighting funder policies and the benefits of open data. It provides an overview of Jisc's activities including training projects, guidance resources, and funding for institutional infrastructure services and repositories. The presentation emphasizes the importance of institutional policies, support services, skills development and cultural change to effectively manage research data in line with funder expectations.
The presentation was given at the Delos Summer School (Tirrenia, June 2008). This presentation provides an overview of digital repositories, looking at different repository types and dividing them by content type, coverage, functionality and target user group. It concludes with two group exercises, one writing a use case for a web archiving project and the other a business case for sustained funding for an Institutional Repository beyond its start-up phase, to help apply knowledge to real-world situations.
The document discusses the FAIR principles for findable, accessible, interoperable, and reusable scientific data. It provides a timeline for the development of the FAIR principles from 2014 to the present. It describes each of the FAIR components and proposes indicators for evaluating compliance. For each principle, it discusses challenges in implementing them at Wageningen University in the Netherlands. Overall, the document aims to help researchers and institutions understand and apply the FAIR principles to improve data management and sharing.
This document discusses creating a data management plan. It explains that a data management plan is a comprehensive plan for managing research data throughout a project's lifecycle and briefly describing how data will be shared per a funder's policy. It provides an overview of key elements to include in a plan such as file formats, organization, sharing, and preservation. The document also reviews funder requirements and available tools to create plans, noting they can be tailored to different funders' guidelines.
presentation at Electronic Resources & Libraries, April 5, 2016
http://erl2016.sched.org/event/5ZQN/s45-sharing-and-reuse-of-scientific-and-research-data-risky-for-privacy
A template for a basic data management plan. Handout to accompany the presentations Introduction to Research Data Management and Preparing Your Research Data for the Future.
This document discusses the importance of managing research data and provides best practices and resources for doing so. It notes that data is a valuable product of research that should be stored securely and potentially shared. Guidelines recommend developing a data management plan, organizing and documenting data, storing data securely in multiple locations, considering ethics and copyright, and potentially sharing data. The document provides links to Bond University's research data management toolkit and other resources to help researchers manage their data responsibly.
Supporting the Research data management process- a guide for Librarians. .ALISS
This document discusses research data management (RDM) and the need to support researchers in managing the large amount of digital data produced during research projects. It defines RDM as the organization and storage of all digital materials created during research, not just publications. The roots of RDM lie in the expansion of digital research and collaboration. Practical examples of research data are provided. The document outlines key aspects of RDM that libraries and research support staff can assist with, such as data storage, metadata, research ethics, and data management planning.
RDAP 15: Virginia Tech University Libraries’ Data Service Pilot with the Coll...ASIS&T
Research Data Access and Preservation Summit, 2015
Minneapolis, MN
April 22-23, 2015
Natsuko Nicholls, Research Data Consultant, Virginia Tech
Andi Ogier, Research Data Consultant, Virginia Tech
Kyrille Goldbeck DeBose, College Librarian for Natural Resources and Environment and Animal Sciences, Virginia Tech
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
Presentation given by Anne Spalding, KAPTUR Project Officer for University for the Creative Arts as part of the UCA RDM training workshop given on 16th January 2013.
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.
This document outlines best practices for creating research data. [1] It recommends using consistent data organization with standardized formats and descriptive file names. [2] Researchers should perform quality assurance checks and use scripted programs to analyze data while keeping notes. [3] All aspects of data collection and analysis should be thoroughly documented. Following these practices will improve data usability, sharing, and reproducibility.
This document discusses best practices for data management for research. It covers topics such as file organization, documentation, storage, sharing and publishing data, and archiving. Good practices include using file naming conventions and open formats, documenting projects, processes, and data, making backups in multiple locations, and publishing and archiving data in repositories to enable access and preservation. Data management is important for research reproducibility, sharing, and complying with funder requirements.
Webinar: Data management and the Open Research Data Pilot in Horizon 2020OpenAccessBelgium
This webinar provides information about strategies for successful Research Data Management, 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.
At the end of the session participants will be able to:
- Understand the basic principles and importance of RDM
- Set clear goals regarding data curation, preservation and sharing
- Comply with the requirements of the Research Data Pilot
- Draft a Data Management Plan
- Identify RDM resources and tools
Incentivising the uptake of reusable metadata in the survey production processLouise Corti
This document discusses incentivizing the uptake of reusable metadata in survey production. It notes that there is no universal language used to document survey questions and variables, leading to wasted resources. The Data Documentation Initiative (DDI) is proposed as a standard. Barriers to adopting metadata best practices include legacy systems, manual processes, and reluctance to change. The document outlines ideas to incentivize metadata use such as specifying documentation requirements in funding calls and improving documentation tools and workflows. Showing tangible benefits through applications like question banks and data exploration systems is also suggested.
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 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.
Data Management Lab: Session 4 Review OutlineIUPUI
Data Management Lab: Session 4 Review Outline (more details at http://ulib.iupui.edu/digitalscholarship/dataservices/datamgmtlab)
What you will learn:
1. Build awareness of research data management issues associated with digital data.
2. Introduce methods to address common data management issues and facilitate data integrity.
3. Introduce institutional resources supporting effective data management methods.
4. Build proficiency in applying these methods.
5. Build strategic skills that enable attendees to solve new data management problems.
This document discusses research data in the context of visual arts research. It defines research data, discusses its importance and challenges in the visual arts domain. Key points covered include the heterogeneous nature of visual arts data, principles of data curation and preservation, and the need for data management planning and assistance with archiving. Examples of types of visual arts research data are provided.
The document summarizes the Jisc Managing Research Data Programme which aims to support universities in improving research data management. It discusses why managing research data is important, highlighting funder policies and the benefits of open data. It provides an overview of Jisc's activities including training projects, guidance resources, and funding for institutional infrastructure services and repositories. The presentation emphasizes the importance of institutional policies, support services, skills development and cultural change to effectively manage research data in line with funder expectations.
The presentation was given at the Delos Summer School (Tirrenia, June 2008). This presentation provides an overview of digital repositories, looking at different repository types and dividing them by content type, coverage, functionality and target user group. It concludes with two group exercises, one writing a use case for a web archiving project and the other a business case for sustained funding for an Institutional Repository beyond its start-up phase, to help apply knowledge to real-world situations.
The document discusses the FAIR principles for findable, accessible, interoperable, and reusable scientific data. It provides a timeline for the development of the FAIR principles from 2014 to the present. It describes each of the FAIR components and proposes indicators for evaluating compliance. For each principle, it discusses challenges in implementing them at Wageningen University in the Netherlands. Overall, the document aims to help researchers and institutions understand and apply the FAIR principles to improve data management and sharing.
This document discusses creating a data management plan. It explains that a data management plan is a comprehensive plan for managing research data throughout a project's lifecycle and briefly describing how data will be shared per a funder's policy. It provides an overview of key elements to include in a plan such as file formats, organization, sharing, and preservation. The document also reviews funder requirements and available tools to create plans, noting they can be tailored to different funders' guidelines.
presentation at Electronic Resources & Libraries, April 5, 2016
http://erl2016.sched.org/event/5ZQN/s45-sharing-and-reuse-of-scientific-and-research-data-risky-for-privacy
A template for a basic data management plan. Handout to accompany the presentations Introduction to Research Data Management and Preparing Your Research Data for the Future.
This document discusses the importance of managing research data and provides best practices and resources for doing so. It notes that data is a valuable product of research that should be stored securely and potentially shared. Guidelines recommend developing a data management plan, organizing and documenting data, storing data securely in multiple locations, considering ethics and copyright, and potentially sharing data. The document provides links to Bond University's research data management toolkit and other resources to help researchers manage their data responsibly.
Supporting the Research data management process- a guide for Librarians. .ALISS
This document discusses research data management (RDM) and the need to support researchers in managing the large amount of digital data produced during research projects. It defines RDM as the organization and storage of all digital materials created during research, not just publications. The roots of RDM lie in the expansion of digital research and collaboration. Practical examples of research data are provided. The document outlines key aspects of RDM that libraries and research support staff can assist with, such as data storage, metadata, research ethics, and data management planning.
RDAP 15: Virginia Tech University Libraries’ Data Service Pilot with the Coll...ASIS&T
Research Data Access and Preservation Summit, 2015
Minneapolis, MN
April 22-23, 2015
Natsuko Nicholls, Research Data Consultant, Virginia Tech
Andi Ogier, Research Data Consultant, Virginia Tech
Kyrille Goldbeck DeBose, College Librarian for Natural Resources and Environment and Animal Sciences, Virginia Tech
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
RDM Roadmap to the Future, or: Lords and Ladies of the DataRobin Rice
Story of the new 2017-2020 University of Edinburgh RDM Roadmap, with a Tolkienesque theme for IASSIST-CARTO 2018 in Montreal: "Once upon a data point: sustaining our data storytellers".
Overview of the Research on Open Educational Resources for Development (ROER4D) Open Data initiative, highlighting data management principles, the five pillars of the ROER4D data publication approach and the project de-identification approach.
Data and Donuts: How to write a data management planC. Tobin Magle
This presentation describes best practices for how to write a data management plan for your research data. Additionally, it provides information about finding funder requirements, metadata standards, and repositories.
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.
Creating a Data Management Plan for your ResearchRobin Rice
This document provides an overview of creating a data management plan (DMP). It discusses what a DMP is, the benefits of creating one, and what funders require. A DMP defines what data will be collected, documented, stored, shared, and preserved. Developing a DMP helps avoid problems and ensures data are reliable and secure. The document outlines six key themes a DMP should address: data types and standards, ethics, access and sharing, storage, preservation, and resources. Support is available to help researchers develop effective DMPs.
This document provides information about developing a data management plan for grant proposals. It discusses the goals of the workshop which are to learn about data management planning, available resources, develop a draft plan, and receive feedback. It then covers what good data management involves, who requires data management plans, examples of requirements from agencies like NSF, and parts of a generic data management plan. Finally, it discusses resources available for creating plans like the DMPTool.
- The document summarizes a workshop on research data management given by Stephanie Simms from the California Digital Library.
- It discusses an overview of research data management and the "SupportYour Data" program, which aims to help researchers better organize, save, document, and share the outputs of their work.
- The workshop covered assessing current data management practices, accessing tools and resources, and data-related services available at Kyoto University.
This document summarizes the results of a needs assessment survey conducted by UNC Greensboro Library to understand faculty research data management practices and needs. The survey found that the top research data formats were text, PDFs, and spreadsheets. Most faculty backed up their data to external drives but not automatically. Three quarters of respondents did not anticipate sharing their data. The greatest needs identified were assistance with storage, backup, and meeting data sharing requirements. The library collaborated with campus partners to address these needs through new storage services, training, and guidance on developing data management plans.
Librarians can provide valuable data management services to researchers on campus. An effective strategy includes surveying researchers to identify needs, communicating service offerings through workshops and consultations, and providing in-depth guidance on data management plans and long-term data preservation. Developing workshops involves setting learning objectives, evaluating content, and securing resources like space and food. Consultations allow librarians to help with specific topics like choosing file formats or finding metadata standards. Creating a data management plan requires detailing a data inventory, metadata description, long-term preservation and access methods. Trusted disciplinary repositories and use of stable identifiers help ensure long-term findability and access.
This document discusses drivers and organizational responses to research data management (RDM) maturity from transatlantic perspectives. It describes external funder mandates in the US and UK that require open sharing of research publications and data. Universities have responded by developing RDM policies, tools, expertise, and education/outreach for researchers. Key RDM components discussed include policies, storage and repository tools, expertise and staffing models, and outreach/education activities. Connecting electronic lab notebooks to other RDM infrastructure is presented as an approach to better integrate researcher workflows with institutional RDM. The document concludes with an invitation to provide comments on RDM maturity through an online survey.
This document discusses the importance of research data management. It covers the data lifecycle and components of a data management plan. The data lifecycle includes collecting, processing, analyzing, storing, preserving, and sharing data. A data management plan outlines how data will be managed and preserved during and after a research project. It includes information about the data, metadata, data sharing policies, long-term storage, and budget. Developing a data management plan helps keep data organized, track processes, control versions, prepare data for sharing and reuse, and ensure long-term access.
This document provides an overview of research data management and outlines the steps for creating a data management plan. It discusses why research data management is important, including enabling data reuse and sharing and meeting funder requirements. The document then walks through creating a data management plan, covering topics like the types and formats of data that will be generated, ethical and intellectual property issues, how data will be stored and backed up, and long-term preservation and deposition of data. It emphasizes that planning early helps ensure accurate, complete and secure data, and avoids problems down the line.
The webinar discussed FAIRDOM services that can help applicants to the ERACoBioTech call with their data management plans and requirements. FAIRDOM offers webinars on developing data management plans, and their platform and tools can help with organizing, storing, sharing, and publishing research data and models in a FAIR manner by utilizing metadata standards. Different levels of support are available, from general community resources through their hub, to premium customized support for individual projects. Consortia can include FAIRDOM as a subcontractor within the guidelines of the ERACoBioTech call.
Planning for Research Data Management: 26th January 2016IzzyChad
This document provides an overview of a session on planning for research data management. It discusses what research data management is, why it is important, and walks through the steps for creating a data management plan. The presenter explains the benefits of effective data management, such as helping researchers work more efficiently and enabling data sharing. Key aspects of a data management plan are also outlined, including describing the data, addressing ethics and intellectual property, determining how data will be stored and preserved, and making plans for data sharing and access.
Similar to S cook ands_ttt2_perth_rdm_training (20)
Presentation by Dr Steve McEachern, ADA, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Hugo Leroux and Liming Zhu, CSIRO, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
The document summarizes plans by the Australian Government to establish new legislation and institutions to streamline access to and use of public sector data. Key points include:
- A new Commonwealth Data Sharing and Release Act will be introduced in 2019 to provide consistent rules for sharing data and establish a National Data Commissioner to oversee the system.
- The National Data Commissioner will ensure transparency, accountability, security, and appropriate risk management in data sharing.
- New rules will focus on enabling data to be shared for purposes like research and policy-making, while protecting privacy and building public trust in data use.
- The government will continue consulting stakeholders on the legislation to address concerns and help the public understand the reforms.
Presentation by Prof Chris Rowe, ADNet, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Investigator-initiated clinical trials: a community perspectiveARDC
Presentation by Miranda Cumpston, ACTA, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Dr Merran Smith, PHRN, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
International perspective for sharing publicly funded medical research dataARDC
Presentation by Olivier Salvado, CSIRO, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Prof Lisa Askie, ANZCTR, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Dr Davina Ghersi, NHMRC, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
Presentation by Dr Adrian Burton, ARDC, to the 'Unlocking value from publicly funded Clinical Research Data' workshop, cohosted by ARDC and CSIRO at ANU on 6 March 2019.
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.
How to make your data count webinar, 26 Nov 2018ARDC
This document outlines the Make Data Count (MDC) initiative to standardize and promote the tracking of research data usage metrics. MDC has developed a Code of Practice for data usage logs, built an open hub to aggregate standardized usage data, and implemented tracking and display of usage metrics at their own repositories. They encourage other repositories to follow five simple steps to Make Their Data Count: 1) Read the Code of Practice, 2) Process usage logs, 3) Send logs to the hub, 4) Pull usage metrics from the hub, and 5) Display metrics. Future work includes outreach, iteration on implementations, and expanding metrics beyond DOIs.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
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إضغ بين إيديكم من أقوى الملازم التي صممتها
ملزمة تشريح الجهاز الهيكلي (نظري 3)
💀💀💀💀💀💀💀💀💀💀
تتميز هذهِ الملزمة بعِدة مُميزات :
1- مُترجمة ترجمة تُناسب جميع المستويات
2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
#فهم_ماكو_درخ
3- دقة الكتابة والصور عالية جداً جداً جداً
4- هُنالك بعض المعلومات تم توضيحها بشكل تفصيلي جداً (تُعتبر لدى الطالب أو الطالبة بإنها معلومات مُبهمة ومع ذلك تم توضيح هذهِ المعلومات المُبهمة بشكل تفصيلي جداً
5- الملزمة تشرح نفسها ب نفسها بس تكلك تعال اقراني
6- تحتوي الملزمة في اول سلايد على خارطة تتضمن جميع تفرُعات معلومات الجهاز الهيكلي المذكورة في هذهِ الملزمة
واخيراً هذهِ الملزمة حلالٌ عليكم وإتمنى منكم إن تدعولي بالخير والصحة والعافية فقط
كل التوفيق زملائي وزميلاتي ، زميلكم محمد الذهبي 💊💊
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Andreas Schleicher presents PISA 2022 Volume III - Creative Thinking - 18 Jun...EduSkills OECD
Andreas Schleicher, Director of Education and Skills at the OECD presents at the launch of PISA 2022 Volume III - Creative Minds, Creative Schools on 18 June 2024.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
The chapter Lifelines of National Economy in Class 10 Geography focuses on the various modes of transportation and communication that play a vital role in the economic development of a country. These lifelines are crucial for the movement of goods, services, and people, thereby connecting different regions and promoting economic activities.
How Barcodes Can Be Leveraged Within Odoo 17Celine George
In this presentation, we will explore how barcodes can be leveraged within Odoo 17 to streamline our manufacturing processes. We will cover the configuration steps, how to utilize barcodes in different manufacturing scenarios, and the overall benefits of implementing this technology.
1. Developing a Research Data Management
(101) Unit
INFORMATION MANAGEMENT & TECHNOLOGY
Sue Cook, Carmi Cronje, Katie Hannan | Data Librarians
17 May 2018
2. context
• CSIRO
• trainers: Research Data Support - Sue and Carmi
• audience: Agriculture and Food Data School participants
• subject : An introduction to Research Data Management
• pilot session for a pilot program
2 |
3. audience: Agriculture and Food Data school
● Data Literacy
● R
● Data visualisation and exploration
● Version control and git
● Python and systematic programming design
● Statistical Modelling
● HPC
● Databases
● Big Data Practical
● Literate Programming & Jupyter Notebooks
● Bioconductor/Biopython
● Machine Learning
● Networks
● Advanced Programming
● Synthesis project
● Research Data Management
3 |
4. content building
• lots of iteration
• 70 hours of work – learning curve
• scanned existing materials
• started by trying to be modular and reuse others materials
• refocused to suit those participants and face to face and
workshop
• wrote most of the final material from scratch
• consultation with organisers changed approach
• 4 versions
4 |
5. filtering
• current RDS guides
• data management in CSIRO
• general RDM materials and modules
• open science
• FAIR
• 5 star data rating
• publishing guides
• training guides
5 |
6. content
6 |
● Introductions
● Research data management (drivers, benefits)
● FAIR data principles
Activity - Finding other people’s data
● Data governance in CSIRO
● Introduction to CSIRO’s Data Access Portal
Activity - Creating a collection in the DAP
● Managing data across the research lifecycle
using FAIR data principles
Activity - Data management planning
7. content- details
• RDM definition
• FAIR
• Why manage data? To minimise risks
• Why manage data? To share with peers (including you)
• Challenges in sharing data
• Drivers to manage data
• Data governance in CSIRO
• DAP
• Licences
• FAIR during the life cycle
• Data management planning
7 |
8. Processing and analysing - planning
8 |
Identifiers > Version control. Are file IDs managed in a
systematic way across raw, processed, final data? Can
you find the files you need in order to repeat processes?
Metadata > Readme text files. Disciplinary metadata
standards and vocabularies. Metadata at field and
variable level. Can discipline-specific standards be used?
Is there enough information associated with each
process?
Access, storage > Access to different versions of data.
Where is the data located, is it backed up? Can you
access the files you need in order to repeat processes?
+ FAIR
principles
Research Data Management | Research Data Support
9. some of what we discarded
• open science
• specific schemas and vocabs
• videos
• background to FAIR/Force11
• policies of journals and funders
9 |
10. lessons (for THIS content with THIS audience)
• we planned to do ½ day but ended up a full day
• but they loved it
• generated lots of discussion- that was a goal for the organisers
• appreciated that we were a context setting session
• KISS
• less “hand holding” i.e. less providing the answers
• more hands on exercises
• next version will be a planned full day
• more iterating
• define role- facilitation
11. IMT
Carmi Cronje
Data Librarian
t +61 2 9325 3066
e carmi.cronje@csiro.au
w data.csiro.au
Thank you!
IMT
Sue Cook
Data Librarian
t +61 8 6436 8532
e sue.cook@csiro.au
w data.csiro.au