2016 ESIP Summer Meeting

The AGU Data Management Maturity (DMM) Workshop is an opportunity to learn more about the process areas included in the DMM reference model as it applies to the Earth and space sciences. We will discuss important process inter-dependencies, and how to characterize the level of data management capability for your organization. You will learn about common data management weaknesses and specific steps you can take to improve your own data management practices as soon as you get home. This is a great workshop for any data curation team, repository of any size, or anyone working with data.

When managing and providing effective stewardship to digital Earth Science data products in the era of Big Data and Open Data, reference frameworks for assessing dataset quality are key components in helping with the major challenges of consistently describing and systematically integrating quality information to diverse audiences of data users. The natural evolution of user base and data tools over time require continuous monitoring and flexible--but consistent--methods of rating and signaling data quality and maturity. This workshop consists of two sessions. The first session ( (http://commons.esipfed.org/node/9036) will bring together a panel of experts in the fields of exploring quantifiably measurements of product, stewardship, and service maturity levels for digital data in order to help data managers, data producers, or institutions to identify the strength and gaps in their procedures or practices applied to individual data products.They will examine the current states of the cutting-edge research, following by Q&A and panel discussion. The second session will provide updates on use case studies of various maturity assessment models. It follows by training/working time for attendees to get familiar with and apply the assessment models, including the data stewardship maturity model, to their datasets. Use case study update presentation focus areas Shelley Stall - AGU Data Management Assessment Program using the Data Management Maturity framework use case study Sophie Hou and Ruth Duerr - ESIP DSMM use case study Nancy Ritchey and Ge Peng - NCEI DSMM use case study AGU's Data Management Assessment Program Use Case Study AGU conducted two assessments as part of the introduction and piloting of the Data Management Maturity (DMM) framework. Each organization assessed has different data management objectives in support of their organization's strategic goals. We'll discuss the flexibility of the DMM Framework, the assessment approach used for each organization, and the results of each assessment. Pilot #1: USGS ScienceBase Repository - Data Release Team Pilot #2: The Biological and Chemical Oceanography Data Management Office (BCO-DMO) Team The purposes of the ESIP Data Stewardship Maturity Matrix (DSMM) Use Case Study Evaluate and improve DSMM and generalize its across-disciplines application Evaluate and improve the DSMM self-assessment template Develop community-wide dataset-centric stewardship requirements and guidance The purposes of the NCEI Data Stewardship Maturity Matrix (DSMM) Use Case Study Demonstrate the utility of DSMM, ensure and improve consistency of its application to various NCEI data types Establish baselines for high-utility/impact NCEI core datasets Explore requirements for collecting and capturing content-rich quality metadata

Complete documentation of scientific data is the surest way to facilitate discovery and reuse, particularly if you use a metadata dialect that has been standardized. What is complete metadata though? How can you be sure that what you include in the metadata is not only relevant to your organization's work, but understandable to your scientific community and beyond? In this session we will be demonstrating a process to analyze the content of metadata in many standard dialects with respect to over 20 different recommendations of particular interest to the earth, space, and ecological scientific communities. You only need a connected web browser or Microsoft Excel to participate in this hands-on activity. Participants can use metadata collections from their own organizations as long as it is submitted in advance, but we will also provide some sample data if you just want to drop in. Please contact Sean Gordon for submission details. I will use XSL prior to the lab to mine the collections for concept content. In the lab you will learn how to utilize the resultant data and a recommendation's concepts to assess the completeness of records in the collections, and how to use that information to inform an iterative design process to improve the completeness of current records and prepare future metadata creation for success. More information: http://esipfed.org/node/9254