The first is the Four-Layer Framework for Data Standards. This framework has helped guide decisions about the Common Education Data Standards – what should be the scope and how CEDS should relate to other standards in the space. However, the framework is not limited to education standards. Any organization that's developing specifications for the exchange of data should think of these four layers and try to describe each part semi-independently.
Last year I developed A Taxonomy of Education Standards. This framework categorizes standards according to their purpose or the domain in which they are applied.
These education standards are not exclusively data standards. Academic Standards, which include Achievement Standards and Competency Standards describe skills that students should be able to demonstrate as they achieve certain levels of education. Nevertheless, there are data standards for describing Academic Standards and for aligning content to those standards.
In May of 2013 my friends at SETDA published Transforming Data to Information In Service of Learning. This is an enormously valuable survey of existing data standards with guidance on how organizations can apply them to improve learning and support interoperability of their learning technologies. In doing so, they used both the four-layer model and the taxonomy.
Shortly thereafter, I combined the models into a two-dimensional matrix with the four layers on the horizontal axis the taxonomy on the vertical axis. This allows us to plot existing and proposed standards against the two dimensions to see how they fit together.
At the iNACOL symposium two weeks ago Liz Glowa, Jim Goodell and I presented a workshop on "Competency Education Informed by Data". For that workshop I updated the matrix to reflect changes in the standards landscape over the last year. Here's the updated version:
And to tie these all together, here's a translation of the acronyms into the standards with links to their corresponding websites.
Updated: 25 Nov 2014 to add the OAI-PMH protocol.