Like many data librarians and service providers, a lot of the questions RDS gets about data management and data management planning relate to metadata. Researchers often know what it means to them, but are not always clear on what metadata means in relation to developing and following through on DMPs. Often the term is broadly defined as "documentation," but as generalizations "documentation" or "data about data" aren't very helpful in terms of setting and meeting expectations around data discoverability, validity, replication, and reuse. Saying metadata is "data about data" is like getting the candy heart that says "You're Nice!" Nice is good, but we know we're always hoping for more.
Useful guidance is provided online at the DMP Tool (https://dmptool.org/), through our Data Management Libguide (http://libguides.unm.edu/data) and other resources. As a general rule, I like to encourage researchers to think about what they would need to know to find and use their own data in five or ten years. Alternately, what would a person who joins your research team mid-project need to know in order to get up to speed and start using data? Specifics may include things like
DataONE provides several case studies illustrating the importance of good documentation and metadata, which are also featured on today's page at Love Your Data Week 2017 (https://loveyourdata.wordpress.com/lydw-2017/tuesday-2017/).
Looking back at the bigger picture, we've all got data. Whether it is spreadsheets full of numbers, audio or video recordings, 3d data and renderings, genetic sequences, text extracted from manuscripts, census data, giant collectons of tweets, or medical images, your data deserve a little love. How do we show our data the love it deserves? By treating it with attention, trust, and respect.
We can show our data the attention it deserves by using the right tools to organize, analyze and visualize it. A growing list of specialized software packages are available in UNM's Libraries to allow for experimentation with best of breed tools for working with your data. Whether you are doing modeling in MATLAB, mapping and analysis in ArcGIS, statistical analysis in SPSS, qualitative research using NVIVO, or rolling your own tools using programming languages like Python and Jupyter notebooks the Library has what you need.
We can increase our trust in our data by developing data management and analysis workflows that are well documented, ensure the integrity of source data, and are replicable. Using technologies such as Jupyter notebooks (for Python- and R-based processes) can provide well documented analysis processes while also streamlining the creation of documentation of that process. For more complex analysis and management capabilities whole systems can be encapsulated into Docker containers that are portable across system and may be run in a wide variety of environments ranging from a single Windows or Mac laptop, to hundreds of servers in the cloud.
Repecting our data often is shown through how we talk about our data with others. To most effectively communicate our research results and the data upon which they are based we need to engage with our audience and clearly show the relevance of those result and data to the conclusions we are presenting. For a given presentation we may want to interact with map data using a Geographic Information System, creating dynamic multimedia content using the Adobe Create Suite, exhibit audio and video in a space that is designed to best convey the nuance of those materials, share your results with collaborators over the web, integrate materials into a virtual reality environment that enables user interaction with those data and products, or us of more traditional presentation tools like PowerPoint, Keynote and Prezi.
While some of these technologies are available throughout UNM's Libraries, All of them are available in the Centennial Science and Engineering Library's new collaborative research and learning space - the CSEL DEN.
Come see these tools in action in the CSEL DEN Open House this Friday (February 17, 2017) from 1-5 pm. We will be hosting a series of technology demonstrations in our workshop and presentation space and providing practice opportunities for our high-end analysis workstations that contain all of these software packages for your use.