The MIT Libraries run various workshops to help you gain new skills in research data management, including:
- Quick & dirty data management: the 5 things you should absolutely be doing with your data now
Do you have data? (Who doesn’t?!?) Learn about the five basic things you can do now to manage your data for future happiness. These tools and techniques support practical data management, and you can start using them immediately. Work with your personal data or research data but start working now to ensure a future where you are secure in the existence, understandability, and reusability of your data! Slides from the latest Quick & Dirty Tips (pdf).
- Data Management: 101
Do you manage research data here at MIT? This workshop provides you with basic strategies to manage research data. Topics include: best practices for retention and archiving, effective directory structures and naming conventions, good file formats for long-term access, data security and backup options, and metadata, tagging, and citation options. Slides from the latest Data Management 101 (pdf).
- Data management for postdocs and research scientists
Are you creating or managing research data? This hands-on workshop will provide an overview of data management topics, including file organization and naming, data security and backups, tools for collaborating with others in the lab, and data publishing, storage and sharing. We’ll also cover journal publisher requirements and writing the data management plans that are required by most funders, as well as data management issues related to closing out projects and moving between institutions. Slides from the latest data management for postdocs and research scientists workshop (pdf).
- Data Management: Data Management Planning and the DMPTool
Are you required to submit a data management plan (DMP) to a funder? Are you looking to create a data management plan and aren’t sure where to start or what to include? This session will run through the components of a good data management plan and introduce the DMPTool, an online (and MIT-customized) tool for crafting funder-specific data management plans. Slides from the latest Data Management Plans and DMPTool (pdf).
- Data Management: File Organization
Do you struggle with organizing your research data? This workshop teaches practical techniques for organizing your data files. Topics include: file and folder organizational structures and file naming. Slides from the latest Data Management File Organizations (pdf) plus materials to help you establish your file organization system.
- Data Management: Using Metadata to Find, Interpret & Share Your Data
Ever struggle to find that file you tucked away last semester (or last week)? Having trouble remembering details in order to re-use your own data? Need others to understand & use your data? This workshop will introduce you to the power of metadata: what it is, why it’s so important, and how to get started with it. Stop wasting time in finding, interpreting or sharing your data. Whether you are new to thinking about metadata or you’re looking to build off some basic knowledge, this workshop is for you! Slides from the latest Using Metadata (pdf).
- Data Management: Strategies for Data Sharing and Storage
Not sure how to publish and share your data? Unclear on the best formats and information to include for optimal data reuse? This workshop will review existing options for long-term storage and strategies for sharing data with other researchers. Topics will include: data publication and citation, persistent identifiers, versioning, data formats and metadata for reuse, repositories, cost models and management strategies. Slides from the latest Strategies for Data Sharing and Storage Slides (pdf)
- Do Right by Your (research) Data: Research Data Rights, Responsibilities, and Licenses
Congratulations–you’ve got research data! This session will walk you through the dos and don’ts associated with research data and artifacts, all of those associated bits of information necessary to understand research data. These can include structured data, images, unstructured data, metadata, analysis scripts, analysis environment, code books, data dictionaries, computational workflows, models, algorithms, Jupyter notebooks, code libraries, etc. We’ll cover the tools and resources available to you for making decisions about your research data (and associated bits) with regard to use agreements, security requirements, and copyright and licensing. We will also explore some case studies for some practical applications exercise. Slides from the latest Research Data Rights, Responsibilities, and Licenses (pdf).
- Managing Your Research Code
Do you write software? Have you been required by funders or publishers to share your code, or do you want to make it accessible to others to use? Documenting, sharing and archiving your research software can make your research more transparent and reproducible, and can help you get credit for your work. This workshop reviews reasons to share your software, best practices and considerations for documenting your software and making it citable, and options for archiving and publishing research software, including software papers and managing software with associated data sets, and some best practices for citing and documenting all of the software that you use. Slides from the latest Managing Your Research Code workshop (pdf).
- Data bites: Backing up your stuff
Computers can get lost or stolen. Data can become corrupted. Hardware can fail. Setting up a solid backup system is key to avoiding data loss and restoring your data when catastrophe strikes. This session will cover what a good backup system looks like and what resources are available at MIT to help you confidently back up your stuff. Slides from the latest Backing up your stuff workshop (pdf).
- Data bites: Finding a data repository
Do you have a long-term home for your research data? Somewhere it can be persistently accessed so that other researchers can replicate your research or to comply with journal or funder requirements? There are many options out there, but we’re here to help you narrow it down. This short workshop runs through MIT Libraries’ recommendations for data repositories, as well as some of the main characteristics to consider as you decide where your data should be made available. Slides from the latest Finding a data repository (pdf).
- Data bites: Writing Better READMEs
README files are standard for software, but they provide useful basic documentation for datasets as well. Get up to speed on efficiently writing useful README files for datasets and software in this short class. We’ll cover some common things you should include in these files, as well as how to provide a citation to ensure you get credit for your hard work, and we will share links to resources. Save yourself time and trouble – if you are sharing data or software, you need READMEs! Slides from the latest Writing Better READMEs workshop (pdf).
- Data bites: Writing better Data Availability Statements
- Data Management: Version Control
Are you or your research group having trouble tracking versions of your datasets? This workshop covers techniques and software to help you manage your versions. See our Version Control handout (pdf).