The document discusses data in the context of research. It defines data as a reinterpretable representation of information that can be communicated, interpreted, or processed. Data takes many forms like bits, numbers, text, sounds, images, and physical specimens. The document outlines four main categories of data: observational, computational, experimental, and records. Data sources and types vary across disciplines like the sciences, social sciences, and humanities. For example, scientists may generate their own data or acquire it from repositories, while humanists work with archives, libraries, and published works. Overall, data plays a key role in research as alleged evidence that is analyzed to produce findings and answer research questions.
The document introduces ontology and describes what it is from both philosophical and computer science perspectives. An ontology in computers consists of a vocabulary to describe a domain, specifications of the meaning of terms, and constraints capturing additional knowledge about the domain. It then provides an example ontology and discusses applications of ontologies such as for the semantic web. It also discusses important considerations for building ontologies such as collaboration, versioning, and ease of use.
This document provides an overview of copyright and intellectual property for librarians. It defines intellectual property and copyright, outlines ownership rights and exceptions, discusses fair use and infringement, and provides resources on copyright policies and laws. Key points covered include what constitutes copyrightable work, how long copyright lasts, exceptions for educational institutions and libraries, and where to find additional information on copyright.
This document summarizes an e-book mobility professional development session. It includes outlines on mobile device requirements, hardware and software checklists, e-book formats and DRM, downloading e-books to mobile devices, library e-book collections, publishers, aggregators and vendors, and hands-on exercises for downloading e-books using mobile apps. Sample mobile apps like Bluefire and iBooks are provided, along with instructions for accessing library e-book collections through Ebscohost.
La Gran Depresión de 1929 tuvo su origen en una crisis económica en los Estados Unidos que se extendió rápidamente a Europa debido a las estrechas relaciones financieras y las deudas contraídas con EEUU. Las políticas liberales para salir de la crisis solo empeoraron la recesión con más desempleo y proteccionismo. Esto llevó a Keynes a proponer que los gobiernos estimulen la demanda incluso incurriendo en déficit públicos. Como resultado, los estados crearon sistemas de bienestar y regularon más la economía para
The document provides information about an upcoming networking event at the library on 5 February 2014. It includes the objectives, which are to engage users through the subject librarian system, learn about different networking styles, and provide tips for networking. The learning outcomes are to understand one's own networking style, describe traits of dominant styles, and list tips for others. It then discusses different networking styles including go-getter, promoter, examiner, and nurturer. The event schedule is presented with talks on various topics and slots for networking. Tips are provided for following up after meeting someone. A survey will be conducted to get feedback from librarians.
This document outlines the objectives and learning outcomes of a workshop on focusing objectives and outcomes. The workshop aims to help instructors understand the purpose of a literature review, how to conduct one properly, and common issues. The learning outcomes state that by the end of the workshop, participants will be able to describe the purposes of a literature review, list common student problems, use an idea mapping method for research, and choose an organization framework for writing.
This document discusses research data management and related issues. It defines research data as any information used in research, including observational, experimental, and simulated data. Proper research data management is important for data preservation, access, and reuse. Institutions should establish research data services and policies to address questions around data ownership, sharing standards, and long-term preservation.
The document discusses data management services at Purdue University Libraries, which has three strategic goals of learning, scholarly communication, and addressing global challenges, and provides data services throughout the entire research lifecycle from proposal preparation to final publication through initiatives like its research repository PURR and data curation profile toolkit.
This document outlines different methods for collecting experimental data in research. It discusses quantitative and qualitative data types, as well as primary and secondary sources of data. Three common data collection methods are described: questionnaires, interviews, and observation. Questionnaires can be structured or unstructured, closed or open-ended. Interviews may be conducted in-person, by telephone, in focus groups, or using depth or projective techniques. Both questionnaires and interviews are effective ways to gather information for descriptive or analytical research. The document emphasizes the importance of planning, designing, and critically examining different data collection methods in research.
The document provides an introduction to research methodology. It discusses the importance of research and outlines the basic steps in the research process. The objectives are for students to understand key concepts at each step, including formulating research questions. The contents cover the nature of research, basic research steps, and formulating research questions. Sample research questions are analyzed as an example.
The needs of researchers in key disciplines are changing rapidly and this has important implications for the library’s role in enhancing research productivity and impact.
Librarians can build a roadmap for supporting 21st Century research needs that draws on both published research sources and institution-specific user research. Several key trends from recent studies and ideas for institution-specific user research tools are highlighted within.
Introduction To Critical Enquiry ResearchTerry Flew
?
This document provides an introduction to approaches and methodologies for critical enquiry research in the creative industries. It discusses key concepts like defining problems, gathering evidence, analyzing evidence, and drawing conclusions. It also outlines various qualitative research techniques like action research, interviews, surveys, case studies, ethnography, and discourse analysis. Finally, it touches on entering the research industry by discussing how to present research, apply for funding, and manage projects and timelines.
Qualitative research involves in-depth exploration and description to understand individuals' experiences and meanings. It focuses on understanding viewpoints rather than generalization. Key characteristics include naturalistic inquiry, an emphasis on interpretation over causation, and the researcher being embedded in the research. Common qualitative methods include ethnography, phenomenology, grounded theory, action research, and case studies. Data collection involves interviews, observations, and documents, while analysis identifies patterns and themes through coding and interpreting data. Ensuring quality requires justifying interpretations, verifying findings, spending prolonged time in the field, and reflecting on the researcher's role.
This document discusses data management practices for researchers. It defines what constitutes data, such as observations, experiments, simulations, and documents. It outlines the roles of librarians in advising on data management plans, metadata practices, and archiving data. It also discusses why data management is important for validation, replication of research, and compliance with funder requirements. The document provides examples of file structures, naming conventions, metadata, codebooks, and archiving data in institutional repositories to facilitate long-term access and reuse of research data.
Social Media Use by Canadian Academic LibrariansCARLsurvey2010
?
The document describes the design of a phase II survey of Canadian academic librarians that builds on findings from a previous phase I survey. The phase II survey aims to elicit qualitative data through open-ended questions about librarians' motivation, attitudes, and behaviors regarding social media use. Responses will be analyzed using grounded theory and triangulation approaches to identify major factors influencing social media adoption among academic librarians.
This document discusses issues related to attributing and citing scientific data. It addresses technical, scientific, institutional, and socio-cultural challenges. Key questions are outlined regarding data citation standards and practices. The roles of different actors in the research enterprise are also discussed. Effective data attribution requires consideration of provenance, ethics, discoverability, relationships between data, intellectual property issues, and policies. Metrics for data use must be grounded in scientific theory to ensure their validity and reliability.
There are many online and in-person courses available for librarians to learn about research data management, data analysis, and visualization, but after you have taken a course, how do you go about applying what you have learned? While it is possible to just start offering classes and consultations, your service will have a better chance of becoming relevant if you consider stakeholders and review your institutional environment. This lecture will give you some ideas to get started with data services at your institution.
Alenka Sauperl: Qualitative Research Methods in Information and Library Science?ISK FF UK
?
This document provides an overview of qualitative research methods in information and library science. It compares qualitative and quantitative methods, describing key differences such as qualitative research focusing on discovery, themes, and understanding events in natural settings using tools like observation, interviews, and content analysis. The document discusses examples and considerations for using these qualitative methods, emphasizing that the researcher is the main research tool and qualitative validity relies on techniques like triangulation.
The document discusses steps in the social research process, including moving from a research question to research design. It covers choosing indicators to measure concepts, and planning the project by breaking it into phases and using a Gantt chart to manage timelines and resources. Philosophy influences research design and outcomes, so researchers should reflect on their assumptions. Overall planning and defining indicators are important for effective research design.
This document provides an overview of research data and the role of libraries in supporting research data services. It discusses that research data takes many forms and differs across disciplines. Libraries can help with research data in several ways, including learning about data practices in their organizations, identifying gaps, and helping researchers find and manage data through various services and skills like data analysis and visualization. The document outlines potential areas libraries can provide support and ways to continue building data skills, such as through online courses and conferences.
STEM Mom facilitates discussion among teachers at Princeton University during their annual YSAP (Young Science Achievers Program) event. [April 20, 2013]
This event is for teachers who already implement student research and who are highly successful in encouraging students to DO science, integrated with TEM! This is the powerpoint used during our full-day workshop.
The document provides an overview of the Big Six Skills approach to conducting dissertation research. It discusses the steps involved: 1) defining the research task, 2) selecting appropriate information sources, 3) locating and accessing relevant information, 4) applying the information, 5) synthesizing information from multiple sources, and 6) evaluating the research process and findings. For each step, it provides guidance on strategies and skills needed to effectively complete dissertation research.
Research Data Management in the Humanities and Social SciencesCelia Emmelhainz
?
This document provides an introduction to research data management for humanities and social sciences librarians. It discusses why data management is an important part of a librarian's role in supporting faculty research, and some key concepts in data management including data formats, storage, security, preservation, and sharing. The document emphasizes that while librarians do not need to be data experts, having a basic understanding of data management concepts can help librarians better serve faculty research needs and expand their role on campus.
This document provides an overview of the steps involved in conducting a systematic review and meta-analysis. It discusses defining a research question, developing search strategies to identify relevant studies, establishing inclusion/exclusion criteria, selecting studies, extracting effect sizes from studies, and conducting a statistical analysis to summarize results. The goal is to synthesize research evidence in a transparent, reproducible manner to answer the research question.
Boosting MySQL with Vector Search Scale22X 2025.pdfAlkin Tezuysal
?
As the demand for vector databases and Generative AI continues to rise, integrating vector storage and search capabilities into traditional databases has become increasingly important. This session introduces the *MyVector Plugin*, a project that brings native vector storage and similarity search to MySQL. Unlike PostgreSQL, which offers interfaces for adding new data types and index methods, MySQL lacks such extensibility. However, by utilizing MySQL's server component plugin and UDF, the *MyVector Plugin* successfully adds a fully functional vector search feature within the existing MySQL + InnoDB infrastructure, eliminating the need for a separate vector database. The session explains the technical aspects of integrating vector support into MySQL, the challenges posed by its architecture, and real-world use cases that showcase the advantages of combining vector search with MySQL's robust features. Attendees will leave with practical insights on how to add vector search capabilities to their MySQL
This document outlines different methods for collecting experimental data in research. It discusses quantitative and qualitative data types, as well as primary and secondary sources of data. Three common data collection methods are described: questionnaires, interviews, and observation. Questionnaires can be structured or unstructured, closed or open-ended. Interviews may be conducted in-person, by telephone, in focus groups, or using depth or projective techniques. Both questionnaires and interviews are effective ways to gather information for descriptive or analytical research. The document emphasizes the importance of planning, designing, and critically examining different data collection methods in research.
The document provides an introduction to research methodology. It discusses the importance of research and outlines the basic steps in the research process. The objectives are for students to understand key concepts at each step, including formulating research questions. The contents cover the nature of research, basic research steps, and formulating research questions. Sample research questions are analyzed as an example.
The needs of researchers in key disciplines are changing rapidly and this has important implications for the library’s role in enhancing research productivity and impact.
Librarians can build a roadmap for supporting 21st Century research needs that draws on both published research sources and institution-specific user research. Several key trends from recent studies and ideas for institution-specific user research tools are highlighted within.
Introduction To Critical Enquiry ResearchTerry Flew
?
This document provides an introduction to approaches and methodologies for critical enquiry research in the creative industries. It discusses key concepts like defining problems, gathering evidence, analyzing evidence, and drawing conclusions. It also outlines various qualitative research techniques like action research, interviews, surveys, case studies, ethnography, and discourse analysis. Finally, it touches on entering the research industry by discussing how to present research, apply for funding, and manage projects and timelines.
Qualitative research involves in-depth exploration and description to understand individuals' experiences and meanings. It focuses on understanding viewpoints rather than generalization. Key characteristics include naturalistic inquiry, an emphasis on interpretation over causation, and the researcher being embedded in the research. Common qualitative methods include ethnography, phenomenology, grounded theory, action research, and case studies. Data collection involves interviews, observations, and documents, while analysis identifies patterns and themes through coding and interpreting data. Ensuring quality requires justifying interpretations, verifying findings, spending prolonged time in the field, and reflecting on the researcher's role.
This document discusses data management practices for researchers. It defines what constitutes data, such as observations, experiments, simulations, and documents. It outlines the roles of librarians in advising on data management plans, metadata practices, and archiving data. It also discusses why data management is important for validation, replication of research, and compliance with funder requirements. The document provides examples of file structures, naming conventions, metadata, codebooks, and archiving data in institutional repositories to facilitate long-term access and reuse of research data.
Social Media Use by Canadian Academic LibrariansCARLsurvey2010
?
The document describes the design of a phase II survey of Canadian academic librarians that builds on findings from a previous phase I survey. The phase II survey aims to elicit qualitative data through open-ended questions about librarians' motivation, attitudes, and behaviors regarding social media use. Responses will be analyzed using grounded theory and triangulation approaches to identify major factors influencing social media adoption among academic librarians.
This document discusses issues related to attributing and citing scientific data. It addresses technical, scientific, institutional, and socio-cultural challenges. Key questions are outlined regarding data citation standards and practices. The roles of different actors in the research enterprise are also discussed. Effective data attribution requires consideration of provenance, ethics, discoverability, relationships between data, intellectual property issues, and policies. Metrics for data use must be grounded in scientific theory to ensure their validity and reliability.
There are many online and in-person courses available for librarians to learn about research data management, data analysis, and visualization, but after you have taken a course, how do you go about applying what you have learned? While it is possible to just start offering classes and consultations, your service will have a better chance of becoming relevant if you consider stakeholders and review your institutional environment. This lecture will give you some ideas to get started with data services at your institution.
Alenka Sauperl: Qualitative Research Methods in Information and Library Science?ISK FF UK
?
This document provides an overview of qualitative research methods in information and library science. It compares qualitative and quantitative methods, describing key differences such as qualitative research focusing on discovery, themes, and understanding events in natural settings using tools like observation, interviews, and content analysis. The document discusses examples and considerations for using these qualitative methods, emphasizing that the researcher is the main research tool and qualitative validity relies on techniques like triangulation.
The document discusses steps in the social research process, including moving from a research question to research design. It covers choosing indicators to measure concepts, and planning the project by breaking it into phases and using a Gantt chart to manage timelines and resources. Philosophy influences research design and outcomes, so researchers should reflect on their assumptions. Overall planning and defining indicators are important for effective research design.
This document provides an overview of research data and the role of libraries in supporting research data services. It discusses that research data takes many forms and differs across disciplines. Libraries can help with research data in several ways, including learning about data practices in their organizations, identifying gaps, and helping researchers find and manage data through various services and skills like data analysis and visualization. The document outlines potential areas libraries can provide support and ways to continue building data skills, such as through online courses and conferences.
STEM Mom facilitates discussion among teachers at Princeton University during their annual YSAP (Young Science Achievers Program) event. [April 20, 2013]
This event is for teachers who already implement student research and who are highly successful in encouraging students to DO science, integrated with TEM! This is the powerpoint used during our full-day workshop.
The document provides an overview of the Big Six Skills approach to conducting dissertation research. It discusses the steps involved: 1) defining the research task, 2) selecting appropriate information sources, 3) locating and accessing relevant information, 4) applying the information, 5) synthesizing information from multiple sources, and 6) evaluating the research process and findings. For each step, it provides guidance on strategies and skills needed to effectively complete dissertation research.
Research Data Management in the Humanities and Social SciencesCelia Emmelhainz
?
This document provides an introduction to research data management for humanities and social sciences librarians. It discusses why data management is an important part of a librarian's role in supporting faculty research, and some key concepts in data management including data formats, storage, security, preservation, and sharing. The document emphasizes that while librarians do not need to be data experts, having a basic understanding of data management concepts can help librarians better serve faculty research needs and expand their role on campus.
This document provides an overview of the steps involved in conducting a systematic review and meta-analysis. It discusses defining a research question, developing search strategies to identify relevant studies, establishing inclusion/exclusion criteria, selecting studies, extracting effect sizes from studies, and conducting a statistical analysis to summarize results. The goal is to synthesize research evidence in a transparent, reproducible manner to answer the research question.
Boosting MySQL with Vector Search Scale22X 2025.pdfAlkin Tezuysal
?
As the demand for vector databases and Generative AI continues to rise, integrating vector storage and search capabilities into traditional databases has become increasingly important. This session introduces the *MyVector Plugin*, a project that brings native vector storage and similarity search to MySQL. Unlike PostgreSQL, which offers interfaces for adding new data types and index methods, MySQL lacks such extensibility. However, by utilizing MySQL's server component plugin and UDF, the *MyVector Plugin* successfully adds a fully functional vector search feature within the existing MySQL + InnoDB infrastructure, eliminating the need for a separate vector database. The session explains the technical aspects of integrating vector support into MySQL, the challenges posed by its architecture, and real-world use cases that showcase the advantages of combining vector search with MySQL's robust features. Attendees will leave with practical insights on how to add vector search capabilities to their MySQL
Design Data Model Objects for Analytics, Activation, and AIaaronmwinters
?
Explore using industry-specific data standards to design data model objects in Data Cloud that can consolidate fragmented and multi-format data sources into a single view of the customer.
Design of the data model objects is a critical first step in setting up Data Cloud and will impact aspects of the implementation, including the data harmonization and mappings, as well as downstream automations and AI processing. This session will provide concrete examples of data standards in the education space and how to design a Data Cloud data model that will hold up over the long-term as new source systems and activation targets are added to the landscape. This will help architects and business analysts accelerate adoption of Data Cloud.
HIRE MUYERN TRUST HACKER FOR AUTHENTIC CYBER SERVICESanastasiapenova16
?
It’s hard to imagine the frustration and helplessness a 65-year-old man with limited computer skills must feel when facing the aftermath of a crypto scam. Recovering a hacked trading wallet can feel like an absolute nightmare, especially when every step seems to lead you into an endless loop of failed solutions. That’s exactly what I went through over the past four weeks. After my trading wallet was compromised, the hacker changed my email address, password, and even removed my phone number from the account. For someone with little technical expertise, this was not just overwhelming, it was a disaster. Every suggested solution I came across in online help centers was either too complex or simply ineffective. I tried countless links, tutorials, and forums, only to find myself stuck, not even close to reclaiming my stolen crypto. In a last-ditch effort, I turned to Google and stumbled upon a review about MUYERN TRUST HACKER. At first, I was skeptical, like anyone would be in my position. But the glowing reviews, especially from people with similar experiences, gave me a glimmer of hope. Despite my doubts, I decided to reach out to them for assistance.The team at MUYERN TRUST HACKER immediately put me at ease. They were professional, understanding, and reassuring. Unlike other services that felt impersonal or automated, they took the time to walk me through every step of the recovery process. The fact that they were willing to schedule a 25-minute session to help me properly secure my account after recovery was invaluable. Today, I’m grateful to say that my stolen crypto has been fully recovered, and my account is secure again. This experience has taught me that sometimes, even when you feel like all hope is lost, there’s always a way to fight back. If you’re going through something similar, don’t give up. Reach out to MUYERN TRUST HACKER. Even if you’ve already tried everything, their expertise and persistence might just be the solution you need.I wholeheartedly recommend MUYERN TRUST HACKER to anyone facing the same situation. Whether you’re a novice or experienced in technology, they’re the right team to trust when it comes to recovering stolen crypto or securing your accounts. Don’t hesitate to contact them, it's worth it. Reach out to them on telegram at muyerntrusthackertech or web: ht tps :// muyerntrusthacker . o r g for faster response.
Valkey 101 - SCaLE 22x March 2025 Stokes.pdfDave Stokes
?
An Introduction to Valkey, Presented March 2025 at the Southern California Linux Expo, Pasadena CA. Valkey is a replacement for Redis and is a very fast in memory database, used to caches and other low latency applications. Valkey is open-source software and very fast.
官方办理文凭加拿大文凭购买,加拿大文凭定制,加拿大卡尔加里大学文凭补办【q薇1954292140】专业在线定制加拿大大学文凭可查文凭定购,定做加拿大本科文凭,【q薇1954292140】复制加拿大The University of Calgary completion letter。在线快速补办加拿大本科毕业证、硕士文凭证书,购买加拿大学位证、卡尔加里大学Offer,加拿大大学文凭在线购买。高仿真还原加拿大文凭证书和外壳,定制加拿大卡尔加里大学成绩单和信封。学历认证购买UC毕业证【q薇1954292140】办理加拿大卡尔加里大学毕业证(UC毕业证书)【q薇1954292140】毕业证书电子版卡尔加里大学offer/学位证毕业证样本、留信官方学历认证(永久存档真实可查)采用学校原版纸张、特殊工艺完全按照原版一比一制作。帮你解决卡尔加里大学学历学位认证难题。
特殊原因导致无法毕业,也可以联系我们帮您办理相关材料:
1:在卡尔加里大学挂科了,不想读了,成绩不理想怎么办???
2:打算回国了,找工作的时候,需要提供认证《UC成绩单购买办理卡尔加里大学毕业证书范本》【Q/WeChat:1954292140】Buy The University of Calgary Diploma《正式成绩单论文没过》有文凭却得不到认证。又该怎么办???加拿大毕业证购买,加拿大文凭购买,
3:回国了找工作没有卡尔加里大学文凭怎么办?有本科却要求硕士又怎么办?
帮您解决在加拿大卡尔加里大学未毕业难题(The University of Calgary)文凭购买、毕业证购买、大学文凭购买、大学毕业证购买、买文凭、日韩文凭、英国大学文凭、美国大学文凭、澳洲大学文凭、加拿大大学文凭(q薇1954292140)新加坡大学文凭、新西兰大学文凭、爱尔兰文凭、西班牙文凭、德国文凭、教育部认证,买毕业证,毕业证购买,买大学文凭,购买日韩毕业证、英国大学毕业证、美国大学毕业证、澳洲大学毕业证、加拿大大学毕业证(q薇1954292140)新加坡大学毕业证、新西兰大学毕业证、爱尔兰毕业证、西班牙毕业证、德国毕业证,回国证明,留信网认证,留信认证办理,学历认证。从而完成就业。
如果您在英、加、美、澳、欧洲等留学过程中或回国后:
1、在校期间因各种原因未能顺利毕业《UC成绩单工艺详解》【Q/WeChat:1954292140】《Buy The University of Calgary Transcript快速办理卡尔加里大学教育部学历认证书毕业文凭证书》,拿不到官方毕业证;
2、面对父母的压力,希望尽快拿到;
3、不清楚认证流程以及材料该如何准备;
4、回国时间很长,忘记办理;
5、回国马上就要找工作《正式成绩单卡尔加里大学成绩单COPY》【q薇1954292140】《毕业证如何办理UC毕业证如何办理》办给用人单位看;
6、企事业单位必须要求办理的;
7、需要报考公务员、购买免税车、落转户口、申请留学生创业基金。
加拿大文凭卡尔加里大学成绩单,UC毕业证【q薇1954292140】办理加拿大卡尔加里大学毕业证(UC毕业证书)【q薇1954292140】国外本科offer在线制作卡尔加里大学offer/学位证学历认证证书电子版、留信官方学历认证(永久存档真实可查)采用学校原版纸张、特殊工艺完全按照原版一比一制作。帮你解决卡尔加里大学学历学位认证难题。
【q薇1954292140】办理卡尔加里大学毕业证(UC毕业证书)学位证书成绩单代办服务【q薇1954292140】卡尔加里大学offer/学位证、留信官方学历认证(永久存档真实可查)采用学校原版纸张、特殊工艺完全按照原版一比一制作加拿大卡尔加里大学毕业证(UC毕业证书)学位证书成绩单代办服务
主营项目:
1、真实教育部国外学历学位认证《加拿大毕业文凭证书快速办理卡尔加里大学文凭样本》【q薇1954292140】《论文没过卡尔加里大学正式成绩单》,教育部存档,教育部留服网站100%可查.
2、办理UC毕业证,改成绩单《UC毕业证明办理卡尔加里大学留学生学历学位认证书》【Q/WeChat:1954292140】Buy The University of Calgary Certificates《正式成绩单论文没过》,卡尔加里大学Offer、在读证明、学生卡、信封、证明信等全套材料,从防伪到印刷,从水印到钢印烫金,高精仿度跟学校原版100%相同.
3、真实使馆认证(即留学人员回国证明),使馆存档可通过大使馆查询确认.
4、留信网认证,国家专业人才认证中心颁发入库证书,留信网存档可查.
《卡尔加里大学揭秘加拿大毕业证书办理UC成绩单温感光标》【q薇1954292140】学位证1:1完美还原海外各大学毕业材料上的工艺:水印,阴影底纹,钢印LOGO烫金烫银,LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。
毕业证办理的详细过程加拿大文凭卡尔加里大学成绩单【q薇1954292140】复刻成绩单加拿大卡尔加里大学毕业证(UC毕业证书)毕业证详解细节 卡尔加里大学毕业证办理,极速办加拿大卡尔加里大学文凭办理,加拿大卡尔加里大学成绩单办理和真实留信认证、留服认证、卡尔加里大学学历认证。学院文凭定制,卡尔加里大学原版文凭补办,扫描件文凭定做,100%文凭复刻。【q薇1954292140】Buy The University of Calgary Diploma购买美国毕业证,购买英国毕业证,购买澳洲毕业证,购买加拿大毕业证,以及德国毕业证,购买法国毕业证(q薇1954292140)购买荷兰毕业证、购买瑞士毕业证、购买日本毕业证、购买韩国毕业证、购买新西兰毕业证、购买新加坡毕业证、购买西班牙毕业证、购买马来西亚毕业证等。包括了本科毕业证,硕士毕业证。
留信认证的作用:
1. 身份认证:留信认证可以证明你的留学经历是真实的,且你获得的学历或学位是正规且经过认证的。这对于一些用人单位来说,尤其是对留学经历有高度要求的公司(如跨国公司或国内高端公司),这是非常重要的一个凭证。
专业评定:留信认证不仅认证你的学位证书,还会对你的所学专业进行评定。这有助于展示你的学术背景,特别是对于国内公司而言,能够清楚了解你所学专业的水平和价值。
国家人才库入库:认证后,你的信息将被纳入国家人才库,并且可以在国家人才网等平台上展示,供包括500强公司等大型公司挑选和聘用人才。这对于回国找工作特别是进入大公司,具有非常积极的作用。
2. 留信认证对就业的好处
提高竞争力:通过留信认证,尤其是对你所学专业的认证,可以大大提高你在国内求职时的竞争力。许多公司对留学生背景和所学专业有很高的要求,认证后的信息能够帮助公司快速识别符合条件的候选人。
增强信任度:公司往往会对没有认证的学历背景产生疑虑,而留信认证为你的学历背景提供了第三方权威机构的背书,增强了雇主的信任。
对接高端岗位:通过认证后,留学生的个人信息被纳入国家人才库,这也意味着你可以被更多的高端岗位、国有大公司和跨国公司注意到,特别是那些招聘具有国际化背景的人才的公司。
The Role of Christopher Campos Orlando in Sustainability Analyticschristophercamposus1
?
Christopher Campos Orlando specializes in leveraging data to promote sustainability and environmental responsibility. With expertise in carbon footprint analysis, regulatory compliance, and green business strategies, he helps organizations integrate sustainability into their operations. His data-driven approach ensures companies meet ESG standards while achieving long-term sustainability goals.
Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures Data Science Lectures
3. Data are one part of scholarly capital, along with
human capital and instrumentation.
Data have become essential scholarly objects to be
captured, mined, used and reused.
Research in all academic fields relies on data.
4. Research Data
Lays out a nice definition of data and how they vary in different disciplines
The Digital Future is Now: A Call to Action for the Humanities
(please read sections 25-44).
[http://www.digitalhumanities.org/dhq/vol/3/4/000077/000077.html]
Presidential Chair & Professor of
Information Studies,
University of California, Los Angeles
Christine Borgman
5. Definitions associated with archival information systems offer a
useful starting point:
Definition of data
A reinterpretable representation of
information in a formalized manner suitable
for communication, interpretation, or
processing.
Examples of data include a sequence of bits, a
table of numbers, the characters on a page, the
recording of sounds made by a person speaking,
or a moon rock specimen.
Source: Reference model for an open archival information system 2002, 1-9.
[http://public.ccsds.org/publications/archive/650x0b1s.pdf]
Technical definition
6. Definition of data
In Buckland’s terms, data are
“alleged evidence”
Source: Buckland,M.K. (1991). “Information as thing.” Journal of the American Society for Information Science, 42 (5): 351-360.
Socio-technical definition
7. What are data?
Think about data by its origin.
In the context of cyberinfrastructure, the four categories of data identified in an influential
U.S. policy report Long-lived Data Collections 2005, and incorporated in National Science
Foundation strategy Cyberinfrastructure Vision for 21st Century Discovery 2007, are now
widely accepted.
1. Observational data- include weather measurements and
attitude surveys...
2. Computational data- result from executing a computer model
or simulation whether for physics or cultural virtual reality.
3. Experimental data- include results from laboratory studies
such as measurements of chemical reactions …
4. Records of government, business and public and private life
yield useful data for scientific, social scientific, and humanistic
research.
8. Example 1
Audio analyser
Frequency analyser
Intelligent Speech Analyser
MS Excel spread sheet
Audio clips
Text reports
Certain parts of the content for example 1 have been removed due to sensitive content
and copyright issue.
Please contact WY for more information.
Video recorders
Voice recorders
Diary
Video clips
Audio clips
Diary entries
9. Data Variety
To give you a better idea of what can be data, Christine Borgman
later expands on her examples and sources of data and how they
vary by branch of research.
10. Scientific data Social scientific data Humanities and arts data
Examples Ecology: weather, ground
water, sensor readings,
historical record
Medicine: xrays
Chemistry: protein structures
Astronomy: spectral surveys
Biology: specimens
Physics: events, objects
Documentation: Lab and field
notebooks, spreadsheets
Opinion polls
Surveys, interviews
Mass media
Laboratory experiments
Field experiments
Demographic records
Census records
Voting records
Economic indicators
Newspapers
Photographs
Letters
Diaries
Books, articles
Birth, death, marriage
records
Church records
Court records
School and college
yearbooks
Maps…
Sources Generate own data
Acquire from collaborators,
other scientists
Data repository
Generate own data
Acquire from other
scholars
Data repositories: Social
Surveys
Government records
Corporate records
Libraries, archives,
museums
Public records
Corporate records, mass
media
Acquire from other
scholars
Data repositories:
Beazley, Arts &
Humanities Data Service
(UK)
Table: Examples and sources of data from the major research branches. (Borgman)
11. Example 2
Example 2 has been removed due to sensitive content.
Please contact WY for more information.
13. 1. Form a group based on subject or discipline.
[Those without subject role can join in any group]
2. Hands-on exercise for Librarians (please work in group)
- use OneSearch/ Databases/ DR-NTU/ Google to get an article published by
any of your faculty or researcher.
- quickly go through the research paper, particularly the methodology section.
3. Librarians among the group to ask and answer the following questions.
[see next slide]
4. Post the findings (title of the research article, question and answer) to PD blog.
Instructions:
14. 1.
Who are they? What research community do they belong to?
What larger discipline is that community a part of?
2.
What data are they creating (i.e., data types, formats, etc)?
How are they creating these data?
3.
What are the roles of data in their research?
15. Title: Librarian Class Attendance: Methods, Outcomes and Opportunities
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1757&context=iatul
http://www.iatul.org/doclibrary/public/Conf_Proceedings/2006/CmorMarshallpaper.pdf
Example sharing
16. 1. Who are they? What research community do they belong to? What larger discipline is that
community a part of?
Dianne Cmor and Victoria Marshall. Library science research community. Information Science.
2. What data are they creating (i.e., data types, formats, etc)? How are they creating these data?
1. Diary entries
2. Qualitative data from Ethnograph and SPSS
3. Reftracker report
4. Interview notes
5. Survey feedback
The data are mostly text and numeric social scientific and humanities & arts data.
3. What are the roles of data in their research?
The information collected was converted/ translated into data. The researchers analysed the
data and got the findings out from the data. They examined and evaluated the outcomes/
findings and then built a convincing evidence to answer all the questions they have posed
earlier for their research.
Example: [Before the interview]
17. Who are they? What research community do they belong to? What larger discipline is that community a part of?
Dianne Cmor is the lead researcher for a research project. Victoria Marshall is another member of the research project. Dianne
and Victoria are both librarian in a university library.
The project is a library related research and the topic of her research is "Librarian class attendance: methods, outcomes and
opportunities". [Library science research community]
The discipline of the research project belongs to Information Science.
What data are they creating (i.e., data types, formats, etc)? How are they creating these data?
The researchers attended a number of seminars called “Journal club” for about 9 weeks. They have jotted down all their
observation in the seminar on a diary. The diary entries were typed out in MS Word and eventually converted to some
qualitative data by using the Ethnograph software and SPSS software.
Reftracker was used each week to document time spent and associated outcomes in relation to meetings with students,
students’ attendance, and the creation of course support content.
The researchers conducted a few interview with the students and faculty members to collect information. A paper survey
form was also created to collect feedback from the students and some faculty members. The researchers typed out all the
notes collected from the interview and survey in MS Word.
The hard copy of the diaries and survey forms were scanned and saved in PDF format.
The data are mostly text and numeric social scientific and humanities & arts data.
What are the roles of data in their research?
The information collected through the observation at various university lectures and seminars/ tutorials, interviews and
survey conducted for students and faculty members was translated into data. The team analysed the data and got the findings
out from the data. They examined and evaluated the outcomes/ findings and then built a convincing evidence to answer all
the questions they have posed earlier for their research.
Example: [After the interview]
[For reference only]
18. Data Stage Output
# of Files / Typical
Size Format Other / Notes
Primary Data
Raw Diary, interview notes
and survey forms
25 files/ unknown Handwritten hard copy
Processed Diary and survey forms 2 files/ < 3MB PDF Scanned copy of the diary (1 file)
and survey forms (1 file).
Original data from the
diary, interview notes
and survey forms
3 files/ < 3MB .doc [MS Word] All entries in the diary, notes &
feedback from the interview and
survey were typed out in MS
Word.
Analyzed Qualitative and
quantitative data
2 files/ < 500KB .CHN [Ethnograph]
.csv [MS Excel]
The researchers used
Ethnograph software and SPSS
software to generate qualitative
data.
A report generated from
RefTracker.
Finalized Report [tables and
figures]
<100KB .csv [MS Excel]
Note: The data specifically designated by the scientist to make publicly available are indicated by the
rows shaded in gray (the “Analyzed” row is shaded here as an example). Empty cells represent cases in
which information was not collected or the scientist could not provide a response.
The data table [For reference only. You don’t have to do this]
Example: Data curation profile