This document discusses version control and file management for PhD students. It covers topics such as creating a logical folder structure, file naming conventions, deciding what files to keep, tracking relationships between files, and managing literature references. It also discusses applications for synchronizing files across devices and collaborating on documents in real-time, such as SURFdrive, OneDrive, SharePoint, OneNote, Google Docs and Overleaf. The document provides examples and recommendations for best practices in organizing research documents and files.
"Hands Off! Best Practices for Code Hand Offs"Naomi Dushay
The document discusses best practices for code handoffs based on a presentation by Naomi Dushay. It recommends writing code that is well-documented, tested, and follows conventions so that it is readable by others. Code should be written as if a stranger needs to understand it. Documentation includes comments, README files, and testing code. Automated testing should demonstrate how code works and catch errors. Tools and libraries should be chosen carefully, with consideration of existing expertise and adoption. Code quality is maintained through practices like continuous integration, KISS (Keep It Simple Stupid) and DRY (Don't Repeat Yourself).
DSpace is an open source repository software platform designed for academic and research institutions to capture, store, distribute and preserve digital materials. It provides tools to organize content such as articles, reports, datasets and multimedia into an institutional repository that is accessible over time. DSpace uses Dublin Core metadata standards and has customizable workflows, user interfaces and technological features like OAI-PMH protocol support to facilitate interoperability between repositories. It is widely used with a large user community and supports long-term digital preservation goals.
The document discusses file management concepts including file structures, directories, file allocation methods, and access rights. It describes common file structures like sequential, indexed sequential, and direct files. It also covers directory structures, file sharing concepts like simultaneous access and access rights, and secondary storage management techniques like preallocation and allocation methods.
This document discusses file management and data organization. It covers moving and copying files between folders and storage devices, searching for files using wildcards, understanding different file formats, sorting files, and working with multiple applications simultaneously. The key topics covered are moving and copying files, searching for files in different ways, recognizing file extensions, sorting files by name, size and date, and opening multiple applications at once in Windows.
File management systems allow for organization and access of files on a computer system. They display details of files like owners and creation dates. Files can contain different types of data like text, images, or other formats. A file management system provides services for storing, accessing, and performing operations on files through standardized interfaces. It aims to guarantee data validity, optimize performance, and prevent data loss through features like backups and recovery.
This document discusses creating a digital library service using DSpace. It begins with an introduction to DSpace, a digital content management system. It then covers digital preservation philosophy and strategies used by DSpace. Key differences between institutional repositories and digital libraries are outlined. The document provides details on the features, architecture, standards, and administration of DSpace installations. It presents examples of possible content and concludes with a scenario for making digital resources openly available electronically using DSpace.
File management systems allow users to organize and keep track of files on their computer. Examples of online file management systems include Zamzar, which allows users to convert different file formats, Word2pdf for converting Word documents to PDF, and Dropbox and Sky Drive which allow uploading, storing, and sharing files through client software and syncing folders between devices. These systems provide functions beyond basic file organization offered by operating systems.
This document discusses file management concepts including files, file attributes, file operations, file types, file structure, and access methods. Key points include:
- Files represent named collections of related information stored on secondary storage.
- File attributes include name, identifier, type, location, size, protection, and time/date information.
- Basic file operations are creating, writing, reading, repositioning, deleting, and truncating files.
- File types include ordinary files, directory files, and special files which represent devices.
- File structure and access methods like sequential, direct, and indexed access determine how information is organized and retrieved from files.
"Hands Off! Best Practices for Code Hand Offs"Naomi Dushay
The document discusses best practices for code handoffs based on a presentation by Naomi Dushay. It recommends writing code that is well-documented, tested, and follows conventions so that it is readable by others. Code should be written as if a stranger needs to understand it. Documentation includes comments, README files, and testing code. Automated testing should demonstrate how code works and catch errors. Tools and libraries should be chosen carefully, with consideration of existing expertise and adoption. Code quality is maintained through practices like continuous integration, KISS (Keep It Simple Stupid) and DRY (Don't Repeat Yourself).
DSpace is an open source repository software platform designed for academic and research institutions to capture, store, distribute and preserve digital materials. It provides tools to organize content such as articles, reports, datasets and multimedia into an institutional repository that is accessible over time. DSpace uses Dublin Core metadata standards and has customizable workflows, user interfaces and technological features like OAI-PMH protocol support to facilitate interoperability between repositories. It is widely used with a large user community and supports long-term digital preservation goals.
The document discusses file management concepts including file structures, directories, file allocation methods, and access rights. It describes common file structures like sequential, indexed sequential, and direct files. It also covers directory structures, file sharing concepts like simultaneous access and access rights, and secondary storage management techniques like preallocation and allocation methods.
This document discusses file management and data organization. It covers moving and copying files between folders and storage devices, searching for files using wildcards, understanding different file formats, sorting files, and working with multiple applications simultaneously. The key topics covered are moving and copying files, searching for files in different ways, recognizing file extensions, sorting files by name, size and date, and opening multiple applications at once in Windows.
File management systems allow for organization and access of files on a computer system. They display details of files like owners and creation dates. Files can contain different types of data like text, images, or other formats. A file management system provides services for storing, accessing, and performing operations on files through standardized interfaces. It aims to guarantee data validity, optimize performance, and prevent data loss through features like backups and recovery.
This document discusses creating a digital library service using DSpace. It begins with an introduction to DSpace, a digital content management system. It then covers digital preservation philosophy and strategies used by DSpace. Key differences between institutional repositories and digital libraries are outlined. The document provides details on the features, architecture, standards, and administration of DSpace installations. It presents examples of possible content and concludes with a scenario for making digital resources openly available electronically using DSpace.
File management systems allow users to organize and keep track of files on their computer. Examples of online file management systems include Zamzar, which allows users to convert different file formats, Word2pdf for converting Word documents to PDF, and Dropbox and Sky Drive which allow uploading, storing, and sharing files through client software and syncing folders between devices. These systems provide functions beyond basic file organization offered by operating systems.
This document discusses file management concepts including files, file attributes, file operations, file types, file structure, and access methods. Key points include:
- Files represent named collections of related information stored on secondary storage.
- File attributes include name, identifier, type, location, size, protection, and time/date information.
- Basic file operations are creating, writing, reading, repositioning, deleting, and truncating files.
- File types include ordinary files, directory files, and special files which represent devices.
- File structure and access methods like sequential, direct, and indexed access determine how information is organized and retrieved from files.
DSpace is an open source digital repository software package typically used to create open access repositories for scholarly content. It can store any digital media type and is optimized for text-based files. DSpace uses a Java platform with a PostgreSQL or Oracle database and has features like full-text search, persistent identifiers, and the ability to handle any file type. The community development model is open source under a BSD license.
The document presents information on files and directories. It discusses how files are structured, including unstructured, record structured, and tree structured formats. It also describes what a directory is and different types of directory structures like single-level, two-level, and hierarchical directories. Hierarchical directories allow users to create subdirectories to organize files in a tree structure.
This document provides guidance on managing research data. It discusses planning ahead by considering data needs, formats, volume and ethics. It also covers organizing data through file naming, metadata, references, remote access and safekeeping. Preserving data involves determining what to keep/delete and using long-term storage such as repositories. Reasons for sharing data include scientific integrity, funding mandates and increasing impact, while reasons for not sharing include financial or sensitive personal information.
Greenstone is open source software for building and distributing digital library collections. It provides a comprehensive system for constructing and presenting collections of documents in various formats, including text, images, audio and video. Greenstone allows users to organize information and publish it on the internet or CD-ROM as a fully searchable digital library. It was developed by the University of Waikato in New Zealand with the aim of empowering organizations to build their own digital libraries.
Born digital archives refer to personal and corporate archives that are created and stored in digital formats, rather than physical formats. They typically include draft works, diaries, correspondence, photographs, and other digital files and objects. These archives pose challenges for preservation due to the variety of file formats, operating systems, and storage media used over time as technologies become obsolete. Institutions must address issues related to representing relationships within archives, scaling workflows, data protection, and educating users on access to these archives.
Eprints is open source repository software developed at the University of Southampton for building institutional repositories. It was first released in 2000 and supports a variety of document types including articles, books, theses, and multimedia files. Eprints is widely used and allows users to upload, search, and export content. It uses traditional technologies like MySQL and Perl but newer versions provide more flexibility and control for repository managers. While it is easy to install and use, Eprints focuses only on repository functions rather than broader digital library needs.
Zotero is a free, open-source reference management software that allows users to organize research, cite sources, and share references. It works as a plugin with browsers to automatically capture citation data from websites. Users can tag, annotate, and attach files like PDFs to references. Zotero also has a web-based component that allows for syncing references across devices and collaborating in groups. While useful for managing citations, it has some limitations, such as an inability to search inside attached file contents other than PDFs.
Research data management: course OGO Quantitative research (21-11-2018)Leon Osinski
Research data management involves three key aspects: 1) protecting data through organized file naming and folder structures, 2) sharing data via collaboration platforms or archives to enable reproducibility and reuse, and 3) caring for data through tidy formatting, thorough metadata and documentation, and use of open standards to ensure understandability and usability.
This document describes a project to classify web documents using machine learning techniques. It involves three phases:
1. Collecting sets of web documents grouped by topic from DMOZ. The goal is to collect 100 documents across 5 topics with at least 20 documents per topic.
2. Performing feature extraction on the documents by selecting keywords and creating feature vectors representing whether each keyword is present in each document.
3. Applying machine learning algorithms to create models that can accurately classify new documents into the existing topics and evaluate the accuracy of the initial topic structure. The models will be used to automatically classify new web documents.
Presentation on email capture done at the Radical Archives of Philadelphia (http://www.phillyradicalarchives.org/). Presented at Archivists Being Awesome (June 17 meeting).
Data carving using artificial headers info sec conferenceRobert Daniel
This document proposes a new approach to data carving called File Recovery using Artificial Headers (FRAH) that can recover files with corrupted or missing headers. An evaluation of existing data carving tools found they have difficulty recovering fragmented files. FRAH works by inserting an artificial header onto files to circumvent missing headers. Testing showed FRAH could successfully recover files that standard tools could not. However, FRAH has limitations in recovering files where payload data is also missing. Further research is needed to make FRAH more robust.
The document discusses file systems and storage management. It covers key concepts like file structure, file attributes, file operations, open files, file locking, access methods including sequential and direct access, and directory operations and design including single-level, two-level, tree-structured, and acyclic graph directories. The goal of directory design is to provide efficiency in locating files, allow convenient naming of files to avoid collisions, and enable logical grouping of files.
This document discusses primary and secondary storage. Secondary storage is used for permanent storage of data in files and has greater storage capacity than primary storage. A file contains records with fields, and each record is uniquely identified by a key field like student ID. Logical files connect programs to physical files on secondary storage. Files can be accessed sequentially, randomly using indexing, or directly using the key value.
Data Management for Undergraduate Researchers (updated - 02/2016)Rebekah Cummings
This document summarizes a seminar on data management for undergraduate researchers. It discusses what data is, why it needs to be managed, and key aspects of effective data management including data organization, metadata, storage and archiving. Specific topics covered include creating data management plans, file naming conventions, structuring folders, describing data through codebooks and documentation, backup strategies, and long-term archival options. The goal is to help researchers organize and document their data so it can be understood and preserved over time.
- File management involves organizing files in a hierarchical structure using directories, folders, and paths to track file locations.
- The operating system provides tools like File Explorer to manage files by renaming, copying, moving, and deleting them. Files are organized into folders and drives to improve organization.
- Key file attributes include the file name, extension, size, date created/modified, and format which is indicated by the extension and determines what application can open the file.
This document summarizes a seminar on data management for undergraduate researchers. It discusses what data is, why it needs to be managed, and key aspects of the data management process such as data organization, metadata, storage, and archiving. Topics covered include file naming best practices, version control, documentation, metadata standards, storage options, and long-term archiving. The goal is to help researchers organize and document their data so it can be understood, preserved, and reused.
This session covers topics related to data archiving and sharing. This includes data formats, metadata, controlled vocabularies, preservation, archiving and repositories.
Leveraging Cloud Storage In Your Job CampaignTom Eberle
More than ever it’s important to be organized and have access to your information in a minutes’ notice. This is particularly true for the job campaigner, juggling a multitude of documents on the run, from a variety of computers and mobile devices. In this presentation I’ll explain what cloud storage is, why it’s important to you, and how you can leverage it in your job campaign to simplify your life.
What you’ll learn:
· Cloud Storage –What is it anyway?
· How does it work?
· How can I use it in my job campaign?
· How can I use it at the job club?
· Comparison of cloud storage services
· Security Issues-What are they and how to overcome them
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.
This document provides information and recommendations for preventing data loss through proper storage, organization, and backup of research files. It discusses developing a consistent file naming convention and folder structure for projects. The document also recommends storing multiple copies of important files in different locations and using version control software to track changes over time. Activities are included to help attendees evaluate their current practices and develop improved plans for organizing, backing up, and locking important versions of their data and files.
Who says you can't do records management in SharePoint?John F. Holliday
Although records management features have steadily improved with each new SharePoint version, many industry observers are starting to express their doubts as to whether SharePoint is a viable platform for building real-world ERM solutions. This session will explore the enhanced RM capabilities of SharePoint 2013 and show how to leverage them to full advantage. The session will also introduce several third-party tools that further enhance the platform to enable true enterprise-class content lifecycle management.
DSpace is an open source digital repository software package typically used to create open access repositories for scholarly content. It can store any digital media type and is optimized for text-based files. DSpace uses a Java platform with a PostgreSQL or Oracle database and has features like full-text search, persistent identifiers, and the ability to handle any file type. The community development model is open source under a BSD license.
The document presents information on files and directories. It discusses how files are structured, including unstructured, record structured, and tree structured formats. It also describes what a directory is and different types of directory structures like single-level, two-level, and hierarchical directories. Hierarchical directories allow users to create subdirectories to organize files in a tree structure.
This document provides guidance on managing research data. It discusses planning ahead by considering data needs, formats, volume and ethics. It also covers organizing data through file naming, metadata, references, remote access and safekeeping. Preserving data involves determining what to keep/delete and using long-term storage such as repositories. Reasons for sharing data include scientific integrity, funding mandates and increasing impact, while reasons for not sharing include financial or sensitive personal information.
Greenstone is open source software for building and distributing digital library collections. It provides a comprehensive system for constructing and presenting collections of documents in various formats, including text, images, audio and video. Greenstone allows users to organize information and publish it on the internet or CD-ROM as a fully searchable digital library. It was developed by the University of Waikato in New Zealand with the aim of empowering organizations to build their own digital libraries.
Born digital archives refer to personal and corporate archives that are created and stored in digital formats, rather than physical formats. They typically include draft works, diaries, correspondence, photographs, and other digital files and objects. These archives pose challenges for preservation due to the variety of file formats, operating systems, and storage media used over time as technologies become obsolete. Institutions must address issues related to representing relationships within archives, scaling workflows, data protection, and educating users on access to these archives.
Eprints is open source repository software developed at the University of Southampton for building institutional repositories. It was first released in 2000 and supports a variety of document types including articles, books, theses, and multimedia files. Eprints is widely used and allows users to upload, search, and export content. It uses traditional technologies like MySQL and Perl but newer versions provide more flexibility and control for repository managers. While it is easy to install and use, Eprints focuses only on repository functions rather than broader digital library needs.
Zotero is a free, open-source reference management software that allows users to organize research, cite sources, and share references. It works as a plugin with browsers to automatically capture citation data from websites. Users can tag, annotate, and attach files like PDFs to references. Zotero also has a web-based component that allows for syncing references across devices and collaborating in groups. While useful for managing citations, it has some limitations, such as an inability to search inside attached file contents other than PDFs.
Research data management: course OGO Quantitative research (21-11-2018)Leon Osinski
Research data management involves three key aspects: 1) protecting data through organized file naming and folder structures, 2) sharing data via collaboration platforms or archives to enable reproducibility and reuse, and 3) caring for data through tidy formatting, thorough metadata and documentation, and use of open standards to ensure understandability and usability.
This document describes a project to classify web documents using machine learning techniques. It involves three phases:
1. Collecting sets of web documents grouped by topic from DMOZ. The goal is to collect 100 documents across 5 topics with at least 20 documents per topic.
2. Performing feature extraction on the documents by selecting keywords and creating feature vectors representing whether each keyword is present in each document.
3. Applying machine learning algorithms to create models that can accurately classify new documents into the existing topics and evaluate the accuracy of the initial topic structure. The models will be used to automatically classify new web documents.
Presentation on email capture done at the Radical Archives of Philadelphia (http://www.phillyradicalarchives.org/). Presented at Archivists Being Awesome (June 17 meeting).
Data carving using artificial headers info sec conferenceRobert Daniel
This document proposes a new approach to data carving called File Recovery using Artificial Headers (FRAH) that can recover files with corrupted or missing headers. An evaluation of existing data carving tools found they have difficulty recovering fragmented files. FRAH works by inserting an artificial header onto files to circumvent missing headers. Testing showed FRAH could successfully recover files that standard tools could not. However, FRAH has limitations in recovering files where payload data is also missing. Further research is needed to make FRAH more robust.
The document discusses file systems and storage management. It covers key concepts like file structure, file attributes, file operations, open files, file locking, access methods including sequential and direct access, and directory operations and design including single-level, two-level, tree-structured, and acyclic graph directories. The goal of directory design is to provide efficiency in locating files, allow convenient naming of files to avoid collisions, and enable logical grouping of files.
This document discusses primary and secondary storage. Secondary storage is used for permanent storage of data in files and has greater storage capacity than primary storage. A file contains records with fields, and each record is uniquely identified by a key field like student ID. Logical files connect programs to physical files on secondary storage. Files can be accessed sequentially, randomly using indexing, or directly using the key value.
Data Management for Undergraduate Researchers (updated - 02/2016)Rebekah Cummings
This document summarizes a seminar on data management for undergraduate researchers. It discusses what data is, why it needs to be managed, and key aspects of effective data management including data organization, metadata, storage and archiving. Specific topics covered include creating data management plans, file naming conventions, structuring folders, describing data through codebooks and documentation, backup strategies, and long-term archival options. The goal is to help researchers organize and document their data so it can be understood and preserved over time.
- File management involves organizing files in a hierarchical structure using directories, folders, and paths to track file locations.
- The operating system provides tools like File Explorer to manage files by renaming, copying, moving, and deleting them. Files are organized into folders and drives to improve organization.
- Key file attributes include the file name, extension, size, date created/modified, and format which is indicated by the extension and determines what application can open the file.
This document summarizes a seminar on data management for undergraduate researchers. It discusses what data is, why it needs to be managed, and key aspects of the data management process such as data organization, metadata, storage, and archiving. Topics covered include file naming best practices, version control, documentation, metadata standards, storage options, and long-term archiving. The goal is to help researchers organize and document their data so it can be understood, preserved, and reused.
This session covers topics related to data archiving and sharing. This includes data formats, metadata, controlled vocabularies, preservation, archiving and repositories.
Leveraging Cloud Storage In Your Job CampaignTom Eberle
More than ever it’s important to be organized and have access to your information in a minutes’ notice. This is particularly true for the job campaigner, juggling a multitude of documents on the run, from a variety of computers and mobile devices. In this presentation I’ll explain what cloud storage is, why it’s important to you, and how you can leverage it in your job campaign to simplify your life.
What you’ll learn:
· Cloud Storage –What is it anyway?
· How does it work?
· How can I use it in my job campaign?
· How can I use it at the job club?
· Comparison of cloud storage services
· Security Issues-What are they and how to overcome them
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.
This document provides information and recommendations for preventing data loss through proper storage, organization, and backup of research files. It discusses developing a consistent file naming convention and folder structure for projects. The document also recommends storing multiple copies of important files in different locations and using version control software to track changes over time. Activities are included to help attendees evaluate their current practices and develop improved plans for organizing, backing up, and locking important versions of their data and files.
Who says you can't do records management in SharePoint?John F. Holliday
Although records management features have steadily improved with each new SharePoint version, many industry observers are starting to express their doubts as to whether SharePoint is a viable platform for building real-world ERM solutions. This session will explore the enhanced RM capabilities of SharePoint 2013 and show how to leverage them to full advantage. The session will also introduce several third-party tools that further enhance the platform to enable true enterprise-class content lifecycle management.
File system in operating system e learningLavanya Sharma
This document provides an overview of operating system file systems. It defines what a file is and discusses different file structures, directory structures like single level, two-level, tree-structured and acyclic graph structures. It also covers file types, file operations, space allocation techniques, security and protection methods. The document concludes with describing the basic architecture and commands of the Linux operating system.
http://kulibrarians.g.hatena.ne.jp/kulibrarians/20170222
Presentation by Cuna Ekmekcioglu (The University of Edinburgh)
- Creating and Managing Digital Research Data in Creative Arts: An overview (2016)
CC BY-NC-SA 4.0
Data Analytics: HDFS with Big Data : Issues and ApplicationDr. Chitra Dhawale
This document provides information about a course on data analytics. It outlines the course outcomes, which include developing scalable systems using Apache and Hadoop, writing MapReduce applications, differentiating SQL and NoSQL, and analyzing and developing big data solutions using Hive and Pig. The document also describes some of the topics that will be covered in the course, including distributed file systems and their issues, an introduction to big data, characteristics of big data, types of big data, and comparisons between traditional and big data approaches.
10-15-13 “Metadata and Repository Services for Research Data Curation” Presen...DuraSpace
“Hot Topics: The DuraSpace Community Webinar Series," Series Six: Research Data in Repositories” Curated by David Minor, Research Data Curation Program, UC San Diego Library. Webinar 2: “Metadata and Repository Services for Research Data Curation”
Presented by Declan Fleming, Chief Technology Strategist, Arwen Hutt, Metadata Librarian & Matt Critchlow, Manager of Development and Web ServicesUC, San Diego Library.
This document provides an overview of data management best practices for graduate students presented in a workshop. It discusses what constitutes research data, the importance of managing data, how to create a data management plan, file naming conventions, metadata, data storage and backup strategies, and archiving options. The workshop covers topics like using a structured folder system, creating codebooks and documentation to describe data, and ensuring long-term access and preservation of research data. University librarians are available to help students with all aspects of responsible data management.
The document discusses different aspects of file systems and file management. It covers:
1) File systems organize computer files and data to make them easy to access. They involve maintaining the physical location of files.
2) Files have attributes like name, size, location, and protection settings. Information is stored in directory structures on disks.
3) There are different methods to access files, including sequential, direct, and indexed sequential access.
4) Directory structures organize large numbers of files in a hierarchy using concepts like single level, two level, and tree level directories. Operations on directories include searching, creating, deleting and renaming files.
Big Data Architecture Workshop - Vahid Amiridatastack
Big Data Architecture Workshop
This slide is about big data tools, thecnologies and layers that can be used in enterprise solutions.
TopHPC Conference
2019
Similar to Powerpoint versiebeheer there is no such thing as a final version 1 (20)
This document summarizes the activities of the Agricultural Data Interest Group (IGAD) at various RDA meetings between 2013-2017. It discusses the establishment of IGAD and several working groups focused on specific data types like wheat, rice, and farm data. It also outlines several deliverables produced by each working group, including standards, frameworks, and guidelines related to data management, sharing, and interoperability for different agricultural domains. Finally, it emphasizes that the RDA structure enables collaboration across geographic and topical divisions to address diverse data issues in agriculture.
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.
Agricultural science: three bibliometric systems comparedHugo Besemer
Here are my thoughts on your questions:
On agricultural journal categories: More specific categories could potentially help groups that focus on very narrow topics like fisheries. Broad categories may not fully capture the nuances of specific fields. However, more categories also means articles have more places they could potentially be categorized, so precision is lost.
On open citation data: Making citation data openly available could help bibliometric analysis by allowing researchers to analyze citations in different ways than predefined categories. It would give them more flexibility to explore topics across boundaries. However, publishers may be reluctant to share proprietary citation data. Also, open data requires efforts to clean, normalize and organize the information for analysis.
In summary, more specific categories and open data each have
This document outlines the deliverables, dates, and responsible partners for tasks in Work Package 1 (WP1) of a project. It includes:
- An online database to map existing standards by month 6-12 and 24, led by FAO
- Gap analysis reports of standards by month 6-12 and 18, led by Agro-Know
- Recommendations to fill gaps in standards by month 18-22, led by ODI
- Specifications for standard interoperability services by month 24, led by ODI
- An online help desk for data publication by month 20, led by Agro-Know
- Standard interoperability services for pilot interventions by month 28-36,
This document provides an overview of the reference manager Mendeley. It discusses registering for Mendeley and installing the software. It then covers creating a Mendeley library by adding references and PDFs manually or importing from other reference managers. The document also explains how to manage references by deduplicating, marking documents, annotating PDFs, and searching the library. Additionally, it discusses citing references using the Mendeley Microsoft Word plug-in and sharing documents and references by creating groups.
This document discusses best practices for research data management. It recommends creating a data management plan that considers short and long-term storage needs for oneself, colleagues, funders and journals. The plan should include all raw, processed and supplementary materials needed to understand and reproduce the research. Short term storage options like personal computers, servers and cloud services are discussed alongside folder structure, file naming conventions and documentation standards. Long term archiving through discipline repositories is also covered to ensure research can be understood, verified and built upon by others in the future.
This document discusses altmetrics and how they can be used to measure the impact of scholarly publications. It provides background on the origins of altmetrics in 2010 and examines how altmetric data from sources like tweets, Mendeley readership counts, and blog citations compare to traditional citation metrics. While altmetrics can provide additional insights, the document also notes limitations such as differences in altmetric baselines across disciplines and the role of automated Twitter accounts.
Open Science refers to making scientific research and data accessible to all levels of an inquiring society. It encompasses initiatives related to open access publishing, open data, citizen science, collaboration tools, reproducibility, and enabling better incentives for scientists. The document discusses how discussions of open science evolved from earlier concepts of open source, open access, open data, and e-science/data-driven discovery. It outlines the different areas of open science according to common frameworks and provides examples of how the UK Royal Society, Dutch science council, and EU Open Science Policy Platform address each area through their initiatives.
Publishing and impact : presentation for PhD Infoirmation Literacy courseHugo Besemer
This document discusses tools and metrics for publishing and measuring research impact, including article, author, journal, and research group metrics. It covers analyzing search results to find interesting journals and researchers, using tools like Scopus and Web of Science. It also discusses choosing journals, open access, journal acceptance rates, coverage in databases, and networking to promote publications. Metrics covered include citations, impact factors, and Essential Science Indicators.
This document discusses an information literacy assignment for a class on finding information. It outlines the assignment which involves students working in groups to research a topic and submit a report. It provides instructions on submitting the assignment and notes there will be a question related to information literacy on the final exam. The document then covers various aspects of finding information for the assignment, including defining information needs, searching techniques, evaluating sources and managing references. It also addresses challenges students may face in finding relevant data and examples of unreliable data sources.
This document summarizes a panel discussion on ResearchGate held at Wageningen UR Library. The panel addressed 7 questions: [1] What data access does ResearchGate have and what are the risks? [2] How do copyright and open access apply? [3] Who uses ResearchGate? [4] Can you get reliable answers on ResearchGate? [5] What are the differences between ResearchGate and other networks like Academia.edu? [6] How should the ResearchGate score be used or interpreted? [7] How can you integrate ResearchGate with other profiles like ORCID and LinkedIn? The panel provided information on ResearchGate's terms of use, copyright policies, user base, factors that influence
social media cafe / organize your author identitiesHugo Besemer
This document discusses organizing author identities across various scholarly profiles and databases. It recommends creating an ORCID profile to integrate all author identities and profiles. Key profiles discussed include search engine profiles (Google Scholar, Web of Science, Scopus), local profiles like WE@WUR and Staff Publications, and scholarly social media sites like ResearchGate, Academia.edu and Mendeley. The document provides guidance on populating profiles, linking profiles to each other using ORCID, and keeping profiles up to date to improve online visibility and identification of authored works.
Data management planning. Means, goals and culturesHugo Besemer
This document discusses data management from the perspectives of different groups at Wageningen University. It identifies two main "cultures": infrastructure builders and empirical scientists. Infrastructure builders see data as evidence that can be copied and formatted, while scientists view data as residing in a specific physical location. Builders focus on metadata and open licensing, while scientists consider agreements and notes. Both have different views on storage, archiving, and publishing. The document advocates being aware of these cultural differences to effectively address institutional data management issues.
Publishing and impact Wageningen University IL for PhD 20141202Hugo Besemer
This document provides information on publishing and metrics for impact. It discusses publishing articles and choosing journals, as well as different metrics for measuring impact at the article, author, journal, and research group levels. These include metrics like the h-index for authors and journal impact factors. It also provides information on bibliometric databases and analyzing citation data to calculate relative impact compared to baselines in different subject areas. Exercises are included to help readers practice applying these bibliometric concepts.
Publishing and citing presentation for VLAG graduate school BaarloHugo Besemer
This document discusses publishing and impact metrics for PhD students. It covers motivations for publishing, different types of metrics including article, author, journal, and research group metrics. It also discusses citation databases, journal choice factors like impact factor and acceptance rate, and ways to increase citations like networking and claiming publications. Key metrics covered include the h-index, journal impact factor, and relative impact. The document provides examples and interpretations for bibliometric analysis.
This document provides information on publishing and metrics for PhD students. It discusses topics like motives for publishing, types of publications, peer review, choosing journals, open access, rejection/acceptance rates, journal circulation, coverage in databases, making publications known through networking and cooperation, author metrics like the h-index, journal metrics from sources like Journal Citation Reports, and analyzing research group metrics and quality over time. Exercises are provided to help students learn how to analyze citation data, journal rankings, and perform bibliometric analyses.
GODAN presentation for RDA Agricultural SIG, 2014-09-22 AmsterdamHugo Besemer
Global Open Data for Agriculture and Nutrition (GODAN) is an initiative launched in 2013 by the USDA and DFID to support global efforts in sharing open agricultural and nutritional data. GODAN has numerous partners from government, research, NGOs, businesses, and intergovernmental organizations. These partners are working to make various data openly available, including open public data, open research data, open access publications, open educational resources, and infrastructures, though some data remains difficult to classify as open. GODAN aims to address policies around open data at institutional, national, and international levels for both public and private organizations, and advocates for the open release and reusability of data.
This document provides information on publishing and impact for PhD students. It discusses motives for publishing, choosing appropriate journals, peer review processes, open access options, and metrics for measuring impact such as citations, journal impact factors, and the H-index. It emphasizes developing a publishing strategy, choosing high quality journals, building networks through collaboration, and promoting one's work to increase citations and impact.
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
PPT on Direct Seeded Rice presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
(June 12, 2024) Webinar: Development of PET theranostics targeting the molecu...Scintica Instrumentation
Targeting Hsp90 and its pathogen Orthologs with Tethered Inhibitors as a Diagnostic and Therapeutic Strategy for cancer and infectious diseases with Dr. Timothy Haystead.
Authoring a personal GPT for your research and practice: How we created the Q...Leonel Morgado
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
Immersive Learning That Works: Research Grounding and Paths ForwardLeonel Morgado
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
ESR spectroscopy in liquid food and beverages.pptx
Powerpoint versiebeheer there is no such thing as a final version 1
1. Version Control and Management
PhD Workshop Carousel
20170407, Hilde van Zeeland & Hugo Besemer
2. Categories in survey feedback
• What is a logical folder/file structure?
• Choices what to keep
• Multiple computers & syncing
• Collaborating on documents
• Relationships between files
• We’re human and other facts of life
New at the meeting: “what did I read and wgere did I read it”
3. Program
• Part 1: Managing folders and files
– What is a logical file and folder structure?
File naming
– Choosing what to keep
– Relationships between files
– Literature and ‘what did I read where?’
• Part 2: Applications and platforms
– Synchronising files
– Collaborating on files
4. Program
• Part 1: Managing folders and files
– What is a logical file and folder structure?
– File naming
– Choosing what to keep
– Relationships between files
– Literature and ‘what did I read where?’
• Part 2: Applications and platforms
– Synchronising files
– Collaborating on files
5. What is a logical folder structure?
• Rule of thumb: ≤ 15 items per folder
• Maximum 4 levels (some say three)
• Do not mix subject content and form
Hierdense beek Pictures
??
Hierdensebeek.tif
My organization of folders seemed intuitive when
I made it at the beginning of my PhD, but now it's
a bit of a mess and I end up searching through
trees of folders, hoping I filed it where I think it
should be...
6. Example
Study to examine the effects of diet on health
- Conducted over 3 years by 3 researchers – Peter, Lisa
and Anna
There are many ways to organise the data. We will look at
three:
- By researcher
- By year
- By activity
7. Example
It is now the summer holidays in 2016. Peter and Anna
are on holiday, and Lisa has received some urgent
questions from the reviewers. They need to know:
the procedure used to produce the high protein diet
which bureau measured the data
what sort of preprocessing was carried out on the data.
8. A librarians tale :
Pre-coordination and post-coordination
• Pre-coordination: systematic shelfing of books ,
e.g. Universal Decimal Classification
– 63 agriculture
• 636 livestock
– 636.2 cattle
» 636.2.033
– 636.4 Poultry
» 636.4.033 Meat poultry
– Post-coordination: the book can be anywhere if you
can search
• Keyword Poultry AND Keyword meat
9. A librarian’s tale 2
• Some systems (Google docs / drive) allow you to
have the same file in the same folder (see there)
• In Windows and other operating systems you can
have shortcuts
• The are local search engine applications (“Google
desktop”)
“Metadata: take half of what you think you need,
and throw away half of that”
Tim Bray – author XML specification
10. Program
• Part 1: Managing folders and files
– What is a logical file and folder structure?
– File naming
– Choosing what to keep
– Relationships between files
– Literature and ‘what did I read where?’
• Part 2: Applications and platforms
– Synchronising files
– Collaborating on files
11. File naming
• What to do:
– Keep names consistent
– Keep names short (max. 25 characters)
– Use ‘_’ or ‘-’ instead of spaces or dots
– Avoid special characters (&%$#)
– Use the date convention YYYY-MM-DD or YYYYMMDD (ISO 8601)
– Go from generic to specific
– Avoid endings such as ‘new_version’, ‘latest_version’, ‘final_version’,
‘final_final_version)
– Use file versioning (v_01, v_02, etc.)
• Note in a separate document (e.g. a README-file) what codes in
your filenames mean, and what changes your versions include
12. How would you name the file?
12
a. MA_NTC023_20141031.xls
b.MA@NTC#23~20141031.xls
c. MicroArrayData_NetherlandsToxicogenomicsCentreP
roject023_20141031.xls
d.microarrayntc02320141031.xls
e. MA_NTC023_31102014.xls
f. MA/NTC/Project23/OCT31st/data.xls
13. Filename conventions
DO:
• Note in a separate document what element
codes in your filename mean
• Keep short and relevant, about 25 characters.
• Go from generic to specific (handy with sorting
and finding)
• Use ‘_’ or ‘-’ 13
Use fixed elements in your filename:
Version number, date, description content, project
number, name researcher/team.
taken from: Data management Workshop For Researchers
by Tessa Pronk (Utrecht University Library)
14. Filename conventions
DON'T:
• Use special characters (&%$#) or points or whitespace.
• Name your files 'new_version' 'newer_version',
'newest_version'.
• Duplicate files in different folders
• Trust computer-metadata with your file
14
15. Program
• Part 1: Managing folders and files
– What is a logical file and folder structure?
– File naming
– Choosing what to keep
– Relationships between files
– Literature and ‘what did I read where?’
• Part 2: Applications and platforms
– Synchronising files
– Collaborating on files
16. What to keep
• Keeping all intermediate files?
– Mock sense of safety
– “So you are not sure what so delete!”
– Define milestones, and keep milestone files
“Sometimes a document (e.g. a graph, a powerpoint or a piece of text) is used
for different purposes and has to be adapted for the specific purpose. This
leads to a large number of slightly different versions of almost the same
thing."
17. Program
• Part 1: Managing folders and files
– What is a logical file and folder structure?
– File naming
– Choosing what to keep
– Relationships between files
– Literature and ‘what did I read where?’
• Part 2: Applications and platforms
– Synchronising files
– Collaborating on files
18. Relationships between files
.”.....It can be difficult to keep track of changes in different R
scripts, and different plots (esp. which sub-sets are used/the
reasoning behind different sets)........”
20. Relationships between files
This only indicates that these files
and versions co-existed in a file
system. Every other relationship
should be handled in your script or
document history
21. Program
• Part 1: Managing folders and files
– What is a logical file and folder structure?
– File naming
– Choosing what to keep
– Relationships between files
– Extra: what did I read and where did I read it?
• Part 2: Applications and platforms
– Synchronising files
– Collaborating on files
22. What did I read and where did I read
it?
• Many people use Endnote or Mendeley to
manage literature
• A reference manager should :
– be able to display references in different journal
styles
– Work seamlessly with e.g. MS/Word
– Organize references in folders and by adding tags
26. Program
• Part 1: Managing folders and files
– What is a logical file and folder structure?
– File naming
– Choosing what to keep
– Relationships between files
– Literature and ‘what did I read where?’
• Part 2: Applications and platforms
– Synchronising files
– Collaborating on files
27. • “I have multiple backups and manual syncing between
them makes it difficult to keep track.”
• “Problems with data backups on different locations that
are not synced.”
• “Similar (R) scripts, on two computers. Sometimes issues
with finding the most up to date one.”
Automatic syncing, across devices, of the latest version
Difficulties when synchronising files
28. Synchronising files
WUR-drives:
• W-drive (internal)
• M-drive (personal) - also syncs to C-drive on WURclient
Both accessible externally: myworkspace.wur.nl
Personal cloud storage:
• SURFdrive
• OneDrive for Business
Both discussed later
29. Program
• Part 1: Managing folders and files
– What is a logical file and folder structure?
– File naming
– Choosing what to keep
– Relationships between files
– Literature and ‘what did I read where?’
• Part 2: Applications and platforms
– Synchronising files
– Collaborating on files
30. • “Too many versions of the same document, that have
been under revision by multiple co-authors. Finding the
right document can be a pain.”
• “… having people use the same system to identify and
name documents.”
• “Difficulty with integrating comments from co-authors
into a single document (especially when using LaTeX).”
Easy document identification and processing
Difficulties when collaborating on files
31. Collaborating on files
Sharing without real-time collaboration:
• SURFdrive
• OneDrive for Business
• Sharepoint teamsite
Sharing with real-time collaboration:
• OneNote - for notes
• Google Docs / Word Online - for text
• Overleaf - for LaTeX
33. WITHOUT REAL-TIME COLLABORATION
SURFdrive
• share directly with other SURFdrive users at WUR, or with
others via external link (password / expiration date)
• version control
• contact servicedesk.it@wur.nl
34. WITHOUT REAL-TIME COLLABORATION
OneDrive for Business
• cloud service - store, sync and share
• synchronise with desktop client (Windows & Mac OSX, not Linux)
• free
• 1TB - but stored locally
• private by default, but easy to share (internal/external with link)
35. • version history (only for Office file formats):
• being piloted: contact servicedesk.it@wur.nl
• like SURFdrive: as it is personal storage space, it is best for
personal use and some file sharing, not for team projects.
WITHOUT REAL-TIME COLLABORATION
OneDrive for Business
37. Document library:
• ‘check out’ docs to
avoid simultaneous
authoring
• describe new versions
• be alerted of changes
to files / libraries
Request team site: https://sharepoint.wur.nl
Request X-account: https://www.xaccounts.wurnet.nl/
WITHOUT REAL-TIME COLLABORATION
Sharepoint team site
38. To keep in mind
Note from IT services:
‘Do not use OneDrive for Business [and SURFdrive] for
critical or secret documents … If you have sensitive or
secret data use our Sharepoint, the W-drive or your
M-drive, this way the data is stored on our servers in
Wageningen and is not synchronized to e.g. your iPad
that could be lost.’
‘The preferred solution for collaboration is our
Sharepoint platform.’
39. Collaborating on files
Sharing without real-time collaboration:
SURFdrive
OneDrive for Business
Sharepoint teamsite
Sharing with real-time collaboration:
OneNote - for notes
Google Docs / Word Online - for text
Overleaf - for LaTeX
41. • share notebooks to collaborate (send link / on teamsite)
• edits appear in real time
• version history, changes by page/author
• tips & tricks:
Data Management Support Hub
WITH REAL-TIME COLLABORATION
OneNote
42. WITH REAL-TIME COLLABORATION
Google Docs
• share and collaborate
on documents
(with a Google account)
• edits, comments, chats
• revisions by date/person
(only unlimited for
Google formats)
43. • Tip: Select a file and press
Shift+Z to move it to different
folders – all versions synced
• Do not use Google for
sensitive/secret data:
- US government can
ask Google for your data
- Google can use it too…
WITH REAL-TIME COLLABORATION
Google Docs
44. Google Terms of Service
When you upload, submit, store, send or receive
content to or through our Services, you give Google
(and those we work with) a worldwide license to use,
host, store, reproduce, modify, create derivative works
(…), communicate, publish, publicly perform, publicly
display and distribute such content.
Our automated systems analyze your content (including
emails) to provide you personally relevant product
features …
www.google.com/policies/terms
45. • Word editing in browser - from Sharepoint or OneDrive
• light-weight version of desktop Word
WITH REAL-TIME COLLABORATION
Word Online
47. • share with a link (editing or read-only)
• edits, comments
• manually save versions
WITH REAL-TIME COLLABORATION
Overleaf
48. Questions?
Also visit our Data Management Support Hub
Library > Expertise & Services > Data Management Support hub
www.wur.nl/en/Expertise-Services/Data-Management-Support-Hub.htm
49. Exercises: Google Docs and/or OneNote
Choose Google Docs and/or OneNote, and follow these steps:
OneNote
- Go to http://tinyurl.com/AccessOneNote
- Click ‘Edit in browser’
- Follow the instructions in the notebook. And just play
around a bit!
Google Docs
- Go to https://tinyurl.com/AccessGoogleDocs
- Follow the instructions in the document. And just play
around a bit!
Editor's Notes
Although good tools and software will help you, you don’t need specialised lab notebook software to produce good, well-structured data and documentation. For this example we simply use files stored in folders. With a little time and effort, even such a simple system will help you a great deal.
Keep names consistent – you should know what it in it just by reading the file name. NOT: mydata.csv
keep names short (max. 25 characters) – so its easy to find and search through
Note in a separate document what element codes in your filename mean
Use ‘_’ or ‘-’ instead of spaces or dots – some operating systems cannot handle these. Underscores and dashes are a good alternative
Avoid special characters (&%$#) – some operating systems cannot handle these. Underscores and dashes are a good alternativeUse the date convention YYYY-MM-DD or YYYYMMDD (ISO 8601) – files will then sort chronologically in your foldersGo from generic to specific - handy with sorting and finding
Avoid endings such as ‘new_version’, ‘latest_version’, ‘final_version’, ‘final_final_version)Use file versioning (v_01, v_02, etc.) – allows you to track your progress and easily revert to earlier versions of your file. Easy to jump back afew steps if you make mistakes in your analysis. Also very useful if you’re collaborating on a file and working on different locations: you always know which is the latest. You can also version your files by date, but you might find that you save the file more often (many dates) than you really see them as a new milestone version.
Note in a separate document what element codes in your filename mean
good: a
b: symbols
c: too long
d: hard to distinguish different parts of file name, but everything is there
e: OK, but date not converted to international format, better for sorting
f: folderstructure → year is missing; you need folder structure to understand what is in the file