Ready, set, data
Kick off your research data journey with some data basics.
Research data comes in many shapes and sizes. Kick off your research data journey and start sharing your stories.
- Getting started is for you if you are just beginning to learn about research data
- Learn more is if you know a bit but want to know more
- Challenge me is often more technical or assumes that you are familiar with at least the basics of managing and wrangling research data.
Do I have to do them all? No - you can pick'n'mix a different stream each week, or stay in the one stream. You can do as much or as little as you want to do, or need to know.
Research data is critical to solving the big questions of our time. So what are some of the issues we face in managing research data?
- Getting started: Watch a cartoon about what happens when a researcher hasn't managed their data (at all…) What could possibly go wrong!?
- Learn more: the 5Vs about Big Data everyone must know
- Challenge me: what are the issues when data is part of an eLab Notebook?
Data and its management change over time. Here we look at data and research lifecycles and make connections between them.
- Getting started: follow the pink circles around the data lifecycle
- Learn more: how would you modify a Lifecycle model for your institution?
- Challenge me: share the current emerging opportunities for institutions to integrate management systems for your research data assets
Repositories and portals play an important role in making research data discoverable and accessible.
- Getting started: explore Research Data Australia to find research data
- Learn more: what's in (and what's not in) the 2,000+ data repositories in re3data?
- Challenge me: can we Trust that repository and how would we know?
Research data may be shared in many ways. This week we look at 3 ways:
- Getting started looks at sharing data via access methods: Open, Shared and Closed Data
- Learn more explores data sharing trends of some countries and by disciplines
- Challenge me dips into ensuring that data can be shared for a long time via some preservation tools
Ensuring data stays accessible and reusable into the future. Learn about the curation of data and try out a free tool for managing file formats.
- Getting started: how would you advise someone what to do to make sure their fragile born digital data is robust and long lived?
- Learn more: how does archiving, preserving and curating data "Stack" up?
- Challenge me: what's in a (PRO)NOM?
Citation analysis and citation metrics are important to the academic community. Find out where data fits in the citation picture.
- Getting started: how to cite data
- Learn more: may the FORCE(11) be with you (while you cite data)
- Challenge me: are some data formats more likely to be cited?
What are Digital Object Identifiers (DOIs) and how do they support data citation and metrics for data and related research objects?
- Getting started: what are DOIs and why are they critical for accurate citation metrics?
- Learn more: delves into altmetrics (and donuts!)
- Challenge me: what about minting DOIs for software, algorithms and grey literature?
Did you know? You don't need to do all three streams, or even stay in the same stream. 23 Things is about picking which Things and streams you want to explore or know more about.
Understand the importance of data licensing and learn about Creative Commons.
- Getting started: don’t let CC pass you BY!
- Learn more: Licensing - a keystone for innovation and business
- Challenge me: How does Licensing work in tricky or complex situations?
Sharing sensitive data requires careful consideration, but it can be done. Find out how.
- Getting started: If it’s so sensitive - how can it possibly be shared and published?!
- Learn more: Who are the “data gatekeepers”?
- Challenge me: Make me anonymous
Metadata are the lifeblood for finding and reusing research data. Data is only as valuable as the metadata which describes and connects it.
- Getting started: What is metadata and what sort of metadata is critical for research data?
- Learn more: Metadata schema go formal and become standards
- Challenge me: Hands on with ANZLIC or XML - You choose!
Data descriptor, keyword, subject … these are all terms commonly used when discussing metadata. Learn about the use of controlled vocabularies to enhance data discovery.
- Get started: Control your language, please!
- Learn more: Make a contribution to Research Vocabularies Australia
- Challenge me: KWA - the CSIRO Science Keyword Aggregator - a service and widget
There are times when metadata created using one standard will need to be transformed or crosswalked to another standard so that metadata can been shared between systems.
- Getting started: start walking the crosswalks for metadata
- Learn more: Hands on with crosswalking Dublin Core
- Challenge me: Hands-on with XSLT
Identifiers are crucial to disambiguation of people, accurate attribution and impact metrics. We look at identifiers for people - specifically the global people identifier: ORCID, and stray into the fascinating world of linked data.
- Getting started: What is ORCID and why is the Australian academic world buzzing about it?
- Learn more: Choose from 3 ways to cultivate your own ORCIDs
- Challenge me: Get hands on with linked data and the semantic web.
Some research institutions and research funders now require researchers to submit a Data Management Plan (DMP) for new projects. What should a DMP cover? Could you help with one?
- Getting started: What’s a DMP?
- Learn more: Why machine-actionable DMPs?
- Challenge me: Exploring DMP Tools
Data sharing policies are becoming increasingly common in Australia and internationally. Learn why research funders and journal publishers are particularly influential when it comes to encouraging data availability.
- Getting started: experience what it’s like to navigate journal data policies
- Learn more: this newly announced journal data policy might affect data around the globe...
- Challenge me: 2020 vision about the future of data and funders
What resources exist for building an inclusive culture of data literacy - not just scientists and science disciplines? Find resources and think about the skills we need as information and data professionals
- Getting started: enjoy a quirky video and find some resources to build data literacy
- Learn more: tinker, tailor, soldier, sailor?: is data literacy the same for all of us?
- Challenge me: B(uild)YO data technical skills through the 4 Carpentries
Learn some tips and tricks for responding to data queries and starting a data conversation.
- Getting started: asking the essential questions to create metadata records, or find out about research data needs
- Learn more: conversations starters about research data services, or think about how interviews uncover vital information useful for data planning
- Challenge me: in depth interviews reveal the extent to which data reuse is dependent on tools and software - what’s your advice?
APIs and Apps are the engines behind making data usable. Find out what they are and how they make data accessible to us all. Get hands on to explore and use APIs relevant to research data including services offered by ANDS and the National Library of Australia.
- Getting started: try some Culture Collage and get some apps to become a citizen scientist
- Learn more: explore the API treasures of Trove
- Challenge me: play with some APIs for ANDS services
It has been said that 80% of all research data has a geographic or spatial component.
- Getting started: get inspired by geospatial data saving lives and kick starting our economy
- Learn more: geospatial metadata is often the ‘missing link’ for cross disciplinary studies - find out how to fill in this missing link
- Challenge me: R, free GIS and Fusion are all available to tempt you for this Thing!
Dig in to dirty data. What is it? Why should we care? Try your hand at using an open source data cleansing tool.
- Getting started: Pregnant men? The data says so! Getting down and dirty with data
- Learn more: Turn a PDF ‘tabula rasa’ into usable data with Tabula
- Challenge me: OpenRefine is a powerful tool for cleaning up lots of dirty data
Learn about the key players in Australia’s research data management ecosystem and how these players combine to make generation, management and publication big data possible.
- Getting started: sample some acronym soup
- Learn more: it doesn’t get much bigger than a telescope which is a square kilometre big!
- Challenge me: explore some virtual laboratories and continental maps
Keep learning and stay connected after 23 (research data) Things. Take time to celebrate and reflect on all you've learned since joining the 23 (research data) Things.