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It guides planning for data collection by defining key variables using controlled vocabulary terms, specifying formats, formats’ shareability, preservation of access if formats become obsolete, and any conversion or copying needs. It also covers responsibilities and resources, dataset organization and naming/version control, an anticipated processing workflow, storage and backup using the 3-2-1 rule, and sharing, reuse, licensing, and preservation practices via data repositories and DOIs.",{"@graph":63,"@context":119},[64,80,102],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":11,"@type":70,"position":76},"https://docshare.wps.com/template/presentations/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/data-management-plan-template/244898/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/data-management-plan-template/244898.png","ImageObject",442,249,{"name":88,"@type":89},"Lucas Martin","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-19","2026-09-12",true,{"@type":98,"interactionType":99,"userInteractionCount":101},"InteractionCounter",{"@type":100},"ViewAction",10,{"@type":103,"mainEntity":104},"FAQPage",[105,111,115],{"name":106,"@type":107,"acceptedAnswer":108},"How should key variables be documented for data collection?","Question",{"text":109,"@type":110},"List all key parameters using controlled vocabulary (CV) terms, including any abbreviations and units. 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List the parameters using controlled vocabulary (CV) terms, include any abbreviations, and units for all key parameters of your study. The National Oceanographic Centre has a CV term builder you may use.  \nBriefly, what is the purpose of collecting these data and who are the intended users? How are you addressing the users’ needs?  \nWhat is the expected timeline for data collection?  \nWhere will data collection take place? What are the spatial bounds?  \nWhat is the platform from which data collection will take place? (e.g. boat name, marine station name)  \nWhat kind of data do you expect to collect? (e.g. profiles, transects, gridded data, time series, etc)  \nWhat file formats do you expect to collect (e.g. .doc, .csv, .jpg, . mov)? Are these file formats easy to share with other researchers from different disciplines? In the event that one of your  \nchosen file formats becomes obsolete (or is no longer supported) how will you ensure access to the research data?  \nDoes your data need to be copied to a new media or cloud platform, or converted to a different file format when you store or publish your datasets? Guidance: Proprietary file formats requiring specialized software or hardware to use are not recommended, but may be necessary for certain data collection or analysis methods. (e.g. raw CTD data files)  \nResponsibilities and Resources  \nWho will be responsible for data collection and serve as a future point of contact? What institution will be responsible for data collection?  \nWho will record metadata for your project and serve as the future point of contact? How will you support data longevity in the event this person leaves? Indicate a succession strategy for these data.  \nWho will take responsibility for ensuring data are correctly deposited in a data repository?  \nWhat hardware, software and human resources will you need?  \nWhat is your estimated budget for data management? Guidance: Common purchases are hard drives, cloud storage or software access. TU Delft’s Data Management Costing Tool is helpful to determine the share of human labor ( FTE) that should be allocated for research data management.  \nDataset Organization  \nHow will you structure, name and version-control your files to help someone outside your research team understand how your data are organized? Describe your naming convention below. Make sure the convention only uses alphanumeric characters, dashes and underscores.  \nIn general, file names should be 32 characters or less and contain the date and the version number (e.g.: “P1-MUS023_2020-02-29_051_raw.tif” and  \n“P1-MUS023_2020-02-29_051_clean_v1 .tif”) .  \nWhat is your ideal workflow? Document your anticipated processing steps between raw data and final data formats (e.g. record any data cleaning protocols and thresholds, binning procedures or formatting anticipated to take place during data QAQC between collection and publishing. )  \nWhat tools or strategies will you use to document your workflow as it evolves during the course of the project? (e.g. Git Hub for version control of code modifications)  \nHow will you make sure that a) your primary data collection methods are documented with transparency and b) your secondary data sources (i.e. , data you did not collect yourself)—are easily identified and cited? Guidance: Document your process: It is useful to consult regularly with members of the research team to capture potential changes in data collection/processing that need to be reflected in the documentation.  \nStorage and Backup  \nList your anticipated storage needs (e.g. , hard drives, cloud storage, shared drives) . List how long you intend to use each type and what capacities you may require. Guidance: Estimating data storage needs: Storage-space estimates should take into account requirements for file versioning, backups, and growth over time. If you ","cbCaiml533EZnzTt","https://ap.wps.com/l/cbCaiml533EZnzTt","pdf",144261,9,"English","# Data Collection\n## Data Variables and Purpose\n## Timeline, Location, and Platform\n## Expected Data and File Formats\n## Responsibilities and Resources\n# Dataset Organization\n## Naming, Version Control, and Workflow\n# Storage and Backup\n## Storage Capacity and Backup Schedule\n## Ethics-Driven Storage Timeframes\n# Sharing, Reuse, and Preservation\n## Access, Licensing, and Repositories","[{\"question\":\"How should key variables be documented for data collection?\",\"answer\":\"List all key parameters using controlled vocabulary (CV) terms, including any abbreviations and units. A CV term builder such as the National Oceanographic Centre’s tool may be used.\"},{\"question\":\"What guidance is given for file formats and long-term access?\",\"answer\":\"Choose file formats that are easy to share across disciplines. Avoid proprietary formats when possible; if specialized formats are necessary, define how access will be ensured if support becomes obsolete.\"},{\"question\":\"What backup strategy does the template recommend?\",\"answer\":\"Use the 3-2-1 backup rule: keep at least three copies, store them on two different media, and keep one offsite backup copy.\"}]","Data Management Plan Template | PDF",1789222800]