An information system is designed to capture, store, process, and provide access to information to support organizational processes and decision making. The document discusses the design of a resource registry information system to support a hybrid cloud-based infrastructure. The resource registry collects and manages metadata about software systems, resources, and their status to enable service discovery, monitoring, and elastic resource allocation. It implements an open model to flexibly support evolving resource types and management needs over the long lifespan of the infrastructure.
Data Management for the Digital HumanitiesThea Atwood
This document provides an overview of key concepts and best practices for data management in the digital humanities. It defines data and discusses its generation. Guidelines for developing a data management plan from funders like NEH and NSF are examined. The importance of data management is explained in terms of meeting requirements, increasing visibility, saving time and money, and facilitating new discoveries. Elements of an effective data management plan, such as roles and responsibilities, expected data, data formats and dissemination, and long-term storage and access are also outlined.
This document provides an overview of developing a data management plan. It discusses the Digital Curation Centre and the speaker's involvement with DMPs. A DMP is a plan for managing research data throughout the data lifecycle that addresses issues like data capture, documentation, access, storage, backup, and long-term preservation. Developing a DMP ensures good data practices and maximizes data reuse. It also benefits research by making the process more efficient, data more accessible and transparent, and findings more impactful. A DMP typically involves researchers, institutions, partners and other stakeholders. Funders like the European Union also have specific DMP requirements for projects seeking funding.
The document discusses training for data management planning. It covers topics like describing data, ethical and legal compliance, documentation, storage and backup during a research project, and opening, publishing and archiving data after a project. For storage and backup, it discusses considering things like the type of data, how it will be saved and shared, access control needs, and sensitivity. For opening, publishing and archiving, it discusses making data openly available or published according to FAIR principles in repositories that are well-established, curated, and provide identifiers for easy citation. It also discusses responsibilities for data management and required resources.
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.
Funder requirements for Data Management PlansSherry Lake
This document discusses funder requirements for data management and sharing. It notes that major funders like the National Science Foundation (NSF) and National Institutes of Health (NIH) require applicants to submit a data management plan. These plans describe how research data will be organized, preserved, and shared. The document provides details on what funders expect to see in a data management plan, including a description of the data, metadata standards, data access and sharing policies, and plans for long-term data preservation. It also lists other funders that require applicants to have a data management or sharing plan.
The document discusses challenges trainers may face when training researchers on data management planning and potential strategies to address these challenges. It identifies six common challenges: 1) researchers not understanding the need for data management planning, 2) researchers being unfamiliar with the concept of research data, 3) researchers not knowing how to describe their data, 4) researchers not thinking ethics and legal compliance applies to their work, 5) the complexity of data privacy and GDPR topics, and 6) researchers not understanding documentation and metadata. The document provides examples and explanations to help trainers overcome these challenges and motivate researchers on the importance of data management planning and its components.
An information system is designed to capture, store, process, and provide access to information to support organizational processes and decision making. The document discusses the design of a resource registry information system to support a hybrid cloud-based infrastructure. The resource registry collects and manages metadata about software systems, resources, and their status to enable service discovery, monitoring, and elastic resource allocation. It implements an open model to flexibly support evolving resource types and management needs over the long lifespan of the infrastructure.
Data Management for the Digital HumanitiesThea Atwood
This document provides an overview of key concepts and best practices for data management in the digital humanities. It defines data and discusses its generation. Guidelines for developing a data management plan from funders like NEH and NSF are examined. The importance of data management is explained in terms of meeting requirements, increasing visibility, saving time and money, and facilitating new discoveries. Elements of an effective data management plan, such as roles and responsibilities, expected data, data formats and dissemination, and long-term storage and access are also outlined.
This document provides an overview of developing a data management plan. It discusses the Digital Curation Centre and the speaker's involvement with DMPs. A DMP is a plan for managing research data throughout the data lifecycle that addresses issues like data capture, documentation, access, storage, backup, and long-term preservation. Developing a DMP ensures good data practices and maximizes data reuse. It also benefits research by making the process more efficient, data more accessible and transparent, and findings more impactful. A DMP typically involves researchers, institutions, partners and other stakeholders. Funders like the European Union also have specific DMP requirements for projects seeking funding.
The document discusses training for data management planning. It covers topics like describing data, ethical and legal compliance, documentation, storage and backup during a research project, and opening, publishing and archiving data after a project. For storage and backup, it discusses considering things like the type of data, how it will be saved and shared, access control needs, and sensitivity. For opening, publishing and archiving, it discusses making data openly available or published according to FAIR principles in repositories that are well-established, curated, and provide identifiers for easy citation. It also discusses responsibilities for data management and required resources.
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.
Funder requirements for Data Management PlansSherry Lake
This document discusses funder requirements for data management and sharing. It notes that major funders like the National Science Foundation (NSF) and National Institutes of Health (NIH) require applicants to submit a data management plan. These plans describe how research data will be organized, preserved, and shared. The document provides details on what funders expect to see in a data management plan, including a description of the data, metadata standards, data access and sharing policies, and plans for long-term data preservation. It also lists other funders that require applicants to have a data management or sharing plan.
The document discusses challenges trainers may face when training researchers on data management planning and potential strategies to address these challenges. It identifies six common challenges: 1) researchers not understanding the need for data management planning, 2) researchers being unfamiliar with the concept of research data, 3) researchers not knowing how to describe their data, 4) researchers not thinking ethics and legal compliance applies to their work, 5) the complexity of data privacy and GDPR topics, and 6) researchers not understanding documentation and metadata. The document provides examples and explanations to help trainers overcome these challenges and motivate researchers on the importance of data management planning and its components.
The document summarizes the agenda and goals of the KAPTUR Project Steering Group meeting on January 8th, 2013 in London. The project aims to investigate research data in the visual arts, apply technology to support its collection and preservation, and develop policies and case studies to share best practices. The agenda covers updates on partner reports, technical demonstrations, sustainability, and conclusion of the project.
The document summarizes the agenda and discussions from the 8th January 2013 steering group meeting for the JISC KAPTUR project. The meeting discussed the importance of effectively managing research data and definitions of visual arts research data. It provided an overview of the KAPTUR work packages, sponsors, and steering group roles. Metrics for gathering evidence on the benefits of the project were also presented, such as improved rates of data management plan creation and awareness of research data management issues.
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 document outlines a conference on research data in the visual arts. It discusses the objectives of the KAPTUR project to investigate the nature of research data in the visual arts, develop appropriate policies and systems, and showcase good practices. The project aims to address challenges such as the varied nature of research outputs and lack of research data management infrastructure in arts institutions. The conference will include discussions on defining research data in the arts, policy adoption, infrastructure requirements, and next steps.
This document provides guidance on questions to consider when developing a technical plan or data management plan for a research funding application. It covers four sections: (1) digital outputs and technologies used in the project; (2) technical methodology including standards, formats, hardware/software, and data processing; (3) technical support and experience; and (4) preservation, sustainability and access including preservation methods, continued access, and intellectual property considerations. The questions aim to ensure digital outputs are well-planned, fit-for-purpose, and preserved/accessible after the project ends.
Birgit Plietzsch “RDM within research computing support” SALCTG June 2013SALCTG
An overview of Research Data Management: the research process from developing ideas to preservation of data; funder perspectives, the impact on the wider service, Data Asset Frameworks, preservation and access, and cost implications.
I shall provide a summary of JISC work in the area of ‘Big Data’. My primary focus will be on how to manage the huge amount of research data produced in UK Universities. I shall cover the history of JISC interventions to improve research data management and look at next steps. I shall touch on some other areas of work like ‘Digging into Data’ and web archiving which also deal with ‘big data’.
Presentation given by Sarah Jones and Martin Donnelly outlining the UK RDM landscape, JISC MRD programmes, and DCC initiatives.
The presentation was given at Statistics New Zealand on 28th March, ANDS webinars on 29th & 30th March and Monash University on 2nd April 2012.
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...EUDAT
| www.eudat.eu | 2nd Session: July 14, 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 and the Digital Curation CentreMartin Donnelly
Slides from a couple of webinars given while visiting ANDS in Canberra, Australia. (N.B. We also gave short talks at Statistics New Zealand and Monash University - the slides are more or less the same.)
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
This slideshow was used in a Research Data Management Planning course taught at IT Services, University of Oxford, on 2014-10-27. 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.
Valuing Information Management and IT ArchitectureGoutama Bachtiar
Delivered in guest lecture session for International Business Accounting Program, Faculty of Business and Management, Petra Christian University, Surabaya, East Java, Indonesia.
A benchmarking tool developed by the DCC to assess research data infrastructure. The presentation also outlines alternative versions developed by the University of the West of England and an EPSRC-compliance version
This slideshow was used in a Research Data Management Planning course taught at IT Services, University of Oxford, on 2015-02-18 and 2015-05-13. 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 document summarizes the agenda and goals of the KAPTUR Project Steering Group meeting on January 8th, 2013 in London. The project aims to investigate research data in the visual arts, apply technology to support its collection and preservation, and develop policies and case studies to share best practices. The agenda covers updates on partner reports, technical demonstrations, sustainability, and conclusion of the project.
The document summarizes the agenda and discussions from the 8th January 2013 steering group meeting for the JISC KAPTUR project. The meeting discussed the importance of effectively managing research data and definitions of visual arts research data. It provided an overview of the KAPTUR work packages, sponsors, and steering group roles. Metrics for gathering evidence on the benefits of the project were also presented, such as improved rates of data management plan creation and awareness of research data management issues.
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 document outlines a conference on research data in the visual arts. It discusses the objectives of the KAPTUR project to investigate the nature of research data in the visual arts, develop appropriate policies and systems, and showcase good practices. The project aims to address challenges such as the varied nature of research outputs and lack of research data management infrastructure in arts institutions. The conference will include discussions on defining research data in the arts, policy adoption, infrastructure requirements, and next steps.
This document provides guidance on questions to consider when developing a technical plan or data management plan for a research funding application. It covers four sections: (1) digital outputs and technologies used in the project; (2) technical methodology including standards, formats, hardware/software, and data processing; (3) technical support and experience; and (4) preservation, sustainability and access including preservation methods, continued access, and intellectual property considerations. The questions aim to ensure digital outputs are well-planned, fit-for-purpose, and preserved/accessible after the project ends.
Birgit Plietzsch “RDM within research computing support” SALCTG June 2013SALCTG
An overview of Research Data Management: the research process from developing ideas to preservation of data; funder perspectives, the impact on the wider service, Data Asset Frameworks, preservation and access, and cost implications.
I shall provide a summary of JISC work in the area of ‘Big Data’. My primary focus will be on how to manage the huge amount of research data produced in UK Universities. I shall cover the history of JISC interventions to improve research data management and look at next steps. I shall touch on some other areas of work like ‘Digging into Data’ and web archiving which also deal with ‘big data’.
Presentation given by Sarah Jones and Martin Donnelly outlining the UK RDM landscape, JISC MRD programmes, and DCC initiatives.
The presentation was given at Statistics New Zealand on 28th March, ANDS webinars on 29th & 30th March and Monash University on 2nd April 2012.
EUDAT & OpenAIRE Webinar: How to write a Data Management Plan - July 14, 2016...EUDAT
| www.eudat.eu | 2nd Session: July 14, 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 and the Digital Curation CentreMartin Donnelly
Slides from a couple of webinars given while visiting ANDS in Canberra, Australia. (N.B. We also gave short talks at Statistics New Zealand and Monash University - the slides are more or less the same.)
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
This slideshow was used in a Research Data Management Planning course taught at IT Services, University of Oxford, on 2014-10-27. 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.
Valuing Information Management and IT ArchitectureGoutama Bachtiar
Delivered in guest lecture session for International Business Accounting Program, Faculty of Business and Management, Petra Christian University, Surabaya, East Java, Indonesia.
A benchmarking tool developed by the DCC to assess research data infrastructure. The presentation also outlines alternative versions developed by the University of the West of England and an EPSRC-compliance version
This slideshow was used in a Research Data Management Planning course taught at IT Services, University of Oxford, on 2015-02-18 and 2015-05-13. 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.
DEVELOPING A KNOWLEDGE MANAGEMENT SPIRAL FOR THE LONG-TERM PRESERVATION SYSTE...cscpconf
This document discusses the development of a knowledge management system for long-term digital preservation on a semantic grid. It presents a conceptual model that integrates knowledge management principles with archival workflows. A logical architecture is described that realizes this model using a semantic datagrid infrastructure based on the OAIS reference model. The goal is to support flexible management of distributed digital archives while enabling new knowledge discovery and value creation through dynamic semantic annotations over time.
Sanjay Gupta is seeking a position in service delivery management or project management with over 24 years of experience in these fields. He currently works as a Project Automation Specialist at Fluor Daniel India Private Limited in Gurgaon. He has extensive experience managing teams, projects, and IT services, as well as skills in areas like service delivery management, project management, software design, and system analysis. He holds an M.Sc. in computer science and has received additional training in areas such as AVEVA PDMS, JavaScript, and Flash.
Sanjay Gupta is seeking a position in service delivery management or project management with over 24 years of experience in these fields. He currently works as a Project Automation Specialist at Fluor Daniel India Private Limited in Gurgaon. He has extensive experience managing teams, projects, and IT services, as well as skills in areas such as service delivery management, project management, software design, and system analysis. He holds an M.Sc. in computer science and has received additional training in areas such as AVEVA PDMS, JavaScript, and Flash.
The document provides an overview of the data analytics process (lifecycle). It discusses the key phases in the lifecycle including discovery, data preparation, model planning, model building, communicating results, and operationalizing. In the discovery phase, stakeholders analyze business trends and domains to build hypotheses. In data preparation, data is explored, preprocessed, and conditioned to create an analytics sandbox. This involves extract, transform, load processes to prepare the data for analysis.
The document summarizes the outputs and findings of the KAPTUR project. It produced four main outputs: an environmental assessment report, technical analysis report, costing model, and pilot demonstration service. The technical analysis report analyzed 17 data management systems and recommended further analysis of four top systems. The pilot used EPrints, Figshare, and DataStage to test supporting visual arts research data. The project identified challenges for researchers in managing and preserving their data.
The document summarizes the process of raising the profile of research data management (RDM) at the University of Chichester (UCA) through their participation in the Kaptur Project. It describes conducting interviews and analysis to understand current RDM practices, developing an RDM policy through discussion and testing a repository model, and obtaining approval of the draft policy. It reflects on the project's successes in establishing RDM processes and importance of ongoing communication and collaboration around RDM.
This document summarizes Goldsmiths' efforts to develop a research data management policy. A working group was formed to review existing policies, discuss data storage and training. They drafted a policy addressing the research data lifecycle, responsibilities of researchers, and the college's role in preserving access to data. A data repository was also created. Key recommendations include identifying stakeholders, being practical, and tying the policy to the university's strategic goals. The overall aim is to improve research support through better research data management.
Dr. Robin Burgess developed a research data management policy for the Glasgow School of Art to raise awareness of the importance of managing research data. Burgess conducted interviews that found arts research data takes many complex forms and is difficult to define. A policy was created through collaboration and defined research data broadly. It addressed roles, preservation, and tools to support implementation. Challenges included building support and understanding of data management, but the policy provides guidance tailored to the arts.
The document summarizes the development of a research data management (RDM) policy at University of the Arts London (UAL). A working group was formed and conducted surveys and interviews to understand research practices and data types. They determined practice-based research has unique data needs. The group defined research data for visual arts and drafted a RDM policy. Training was provided and the policy was approved, establishing procedures for archiving research data and processes at UAL.
The document provides a template for institutions to develop business, financial, and sustainability plans to support research data management (RDM) best practices after the end of the JISC KAPTUR project. The template includes sections for background, objectives, stakeholders, strategic alignment, options appraisal, risk management, cost analysis, and evaluation. It is intended to help institutions outline how they will take RDM best practices forward and ensure ongoing support beyond the project lifespan.
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.
This document summarizes drivers for research data management in UK higher education, including policies from research funders like RCUK and AHRC. It also describes resources for supporting research data management, such as the Jisc Managing Research Data programme, the Digital Curation Centre (DCC), and projects funded through the Jisc programme like CAiRO and KAPTUR. The DCC provides guidance on data management planning, training, and curation best practices. Research data is broadly defined as any digital evidence used or created during the research process to generate new knowledge.
Presentation given by Robin Burgess, KAPTUR Project Officer for The Glasgow School of Art, at the DCC Roadshow Northeast Scotland, University of Dundee, 5th December 2012
Presentation given by Leigh Garrett about the KAPTUR project and the importance of effective RDM practice at the UCA RDM training workshop, 16th January 2013.
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 document outlines a method for estimating the IT costs of research data management systems over 10 years. It describes costing two types of systems: an externally hosted cloud-based system (Amazon Web Services) and an internally hosted open source system. Key factors that are costed include storage, hardware, software, staffing, and annual inflation. The document also notes some limitations, such as development costs being excluded and cloud pricing changing over time. An accompanying Excel spreadsheet model allows entering storage and other variables to calculate total costs for each system.
The technical report summarizes work from the KAPTUR project including:
1) An environmental assessment report analyzed researcher data practices and found they want to share research but with privacy.
2) A technical analysis reviewed 17 systems and recommended piloting Figshare and DataStage.
3) A costing model analyzed institutional vs cloud hosting and identified risks and integration challenges to cloud computing.
4) The meeting presented on piloting Figshare, DataStage, EPrints and CKAN as research data management systems.
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
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
THE SACRIFICE HOW PRO-PALESTINE PROTESTS STUDENTS ARE SACRIFICING TO CHANGE T...indexPub
The recent surge in pro-Palestine student activism has prompted significant responses from universities, ranging from negotiations and divestment commitments to increased transparency about investments in companies supporting the war on Gaza. This activism has led to the cessation of student encampments but also highlighted the substantial sacrifices made by students, including academic disruptions and personal risks. The primary drivers of these protests are poor university administration, lack of transparency, and inadequate communication between officials and students. This study examines the profound emotional, psychological, and professional impacts on students engaged in pro-Palestine protests, focusing on Generation Z's (Gen-Z) activism dynamics. This paper explores the significant sacrifices made by these students and even the professors supporting the pro-Palestine movement, with a focus on recent global movements. Through an in-depth analysis of printed and electronic media, the study examines the impacts of these sacrifices on the academic and personal lives of those involved. The paper highlights examples from various universities, demonstrating student activism's long-term and short-term effects, including disciplinary actions, social backlash, and career implications. The researchers also explore the broader implications of student sacrifices. The findings reveal that these sacrifices are driven by a profound commitment to justice and human rights, and are influenced by the increasing availability of information, peer interactions, and personal convictions. The study also discusses the broader implications of this activism, comparing it to historical precedents and assessing its potential to influence policy and public opinion. The emotional and psychological toll on student activists is significant, but their sense of purpose and community support mitigates some of these challenges. However, the researchers call for acknowledging the broader Impact of these sacrifices on the future global movement of FreePalestine.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
1. JISC KAPTUR project
Data Management Planning
16th January 2013
16th January 2013 Data Management Planning 1
2. Learning Objective Session Outline
10 minutes each section:
• Create a Data 0. Introduction
Management Plan 1. Summary
2. Technical Methodology
3. Support
4. Preservation
5. DMPOnline
16th January 2013 Data Management Planning 2
3. 0. Introduction
(10 minutes)
16th January 2013 Data Management Planning 3
4. Terminology
• Why VADS and research
data?
• Data Management Plan
• DMP
• Technical Appendix
(AHRC)
• Technical Summary and
Technical Plan (AHRC)
• Visual Arts research data
• Visual Arts research outputs
16th January 2013 Data Management Planning 4
5. Why is it essential to manage research data effectively?
16th January 2013 Data Management Planning 5
6. Why is it essential to manage research data effectively?
crucial to research and
innovation
a fundamental part of
maintaining our continued
success in research
aid the dissemination of art
and design research,
benefitting all
because it is required by the
UK Research Councils (£3
billion of funding)
16th January 2013 Data Management Planning 6
7. What do the AHRC expect?
• AHRC support for Practice-led research through our Research
Grants – practice-led and applied route (RGPLA)
“We expect all of our research projects to have some form of
documentation of the research process, which usually takes the
form of textual analysis or explanation to support the research’s
position and to demonstrate critical reflection.”
• Professor: ‘some form of’ documentation compared to going on a
walking holiday and suggesting you bring ‘some form of’ shoes.
16th January 2013 Data Management Planning 7
8. What do the EPSRC expect?
• Engineering and Physical Sciences Research Council
“EPSRC expects all those it funds to have developed a clear
roadmap to align their policies and processes with EPSRC’s
expectations by 1st May 2012, and to be fully compliant with
these expectations by 1st May 2015.”
• EPSRC expectations
Institutions to make metadata describing the research data
(digital and non-digital) available within 12 months of the data
being generated - with the aim of enabling access to the data
16th January 2013 Data Management Planning 8
9. AHRC Technical
Summary
Required for all AHRC
applications
One section of the Case
for Support
For digital and non-digital
outputs
16th January 2013 Data Management Planning 9
10. What should go in the Technical Summary?
Yes digital outputs or No digital outputs or
technologies technologies
- “provide a brief description of - state that your project will not
the project’s proposed digital use digital outputs or digital
outputs and/or digital technologies*
technologies”
- “complete a Technical Plan” - Technical Plan not required
* “web-pages containing information about the project”, use of “conventional software such as
word processing packages and ICT activities such as email” are not required to be stated in
the Technical Summary and do not require a Technical Plan 10
11. AHRC Technical Plan → Data Management Plan (Learning Objective)
• Separate attachment in Je-S* up to 4 sides of A4 in Arial font no
smaller than size 11
• Section 1: Summary of Digital Outputs and Digital Technologies
• Section 2: Technical Methodology
• Section 3: Technical Support and Relevant Experience
• Section 4: Preservation, Sustainability and Use
* Previously the AHRC Technical Appendix could be entered straight into
Je-S and character limits were specified for each section.
16th January 2013 Data Management Planning 11
12. 1: Summary
– What? and How?
– relationship to research
2: Technical Methodology
– 2a: Standards and Formats
– 2b: Hardware and Software
– 2c: Data Acquisition,
Processing, Analysis and
Use → workflow and
project management
16th January 2013 Data Management Planning 12
13. 3: Support
– roles and responsibilities
– managing risk
4: Preservation
– 4a: Preserving Your Data
→ for a minimum of 3
years → requires action
– 4b: Ensuring Continued
Access and Use of Your
Digital Outputs → selection
and awareness of costs of
continued access
16th January 2013 Data Management Planning 13
14. 1. Summary
(10 minutes)
16th January 2013 Data Management Planning 14
15. 1. Summary
• Define the digital outputs and/or digital
technologies that will be used in this
project.
• Why have they been chosen?
• Describe any source data or content.
• How will the outputs be used or the
technologies function?
• How do they relate to the research
questions?
• What type of access is envisaged?
16th January 2013 Data Management Planning 15
17. 2. Technical Methodology
• What file formats will be used and
why? State if different file formats
will be used for dissemination and
preservation.
• What standards will be used by
the project e.g. metadata schema,
controlled vocabulary, Web
standards for website creation?
• Ensure that hardware and
software selected is fit-for-
purpose.
• Outline the project workflow,
including back-up procedures.
16th January 2013 Data Management Planning 17
18. 3. Support
(10 minutes)
16th January 2013 Data Management Planning 18
19. 3. Support
• Consider project team roles and
technical expertise; outsource
technical support if required or
ensure appropriate training will be
received within the project timescale.
• Consult with the institution's IT
Department prior to the application
being submitted to AHRC to ensure
that appropriate support can be
provided e.g. back-ups, server
space.
• Consider any risks to the project
from lack of technical support.
16th January 2013 Data Management Planning 19
20. 4. Preservation
(10 minutes)
16th January 2013 Data Management Planning 20
21. 4. Preservation
• "freely available to the research community.“
for a minimum period of three years after the
end of the funding. For "on-line resources
this means keeping the full on-line system
working".
• What impact will your digital outputs have by
being made openly and publicly accessible
online?
• Intellectual Property, copyright, and/or
ethical considerations may define the limits
of sustainability or access.
• How will the resource be supported after the
end of the project funding? Is institutional
support available? Will the content require
updating? Will the technical system require
updating/maintenance/bug fixes? What
16th January 2013 costs are expected?
22. 5. DMPOnline
(10 minutes)
16th January 2013 Data Management Planning 22
23. 5. DMPOnline
https://dmponline.dcc.ac.uk/
free Data Management Planning
tool – login with Athens!
includes AHRC Technical Plan
as well as many other funder
plans
share your plans with individuals
or the whole institution
work with DCC to produce a
custom DMP for your institution
16th January 2013 Data Management Planning 23