Legacy Data Models in UML etc. can be Recycled into Graph Data Models
There 70+ ERD-supporting data modeling tools and a list of 50+ UML tools. This translates to hundreds of thousands of good, reusable data models! Why waste such a large resource of business metadata?
New edition: Now also supports FileMaker(R) data models!
Much similar to data science we need to be able to (in "Metadata Science") to read, transform, scope / reduce / enhance and adapt to modern database technologies. Not least graph databases, if you ask me.
This book contains all you need to do this for the legacy data models - scripts, models and flows.
Why waste time remodeling the same data again, because you change platform? Explore how to auto-generate graph data models (for Neo4j) from legacy data models in UML, XML, ERD, concept maps and other formats. And it includes a design of a metadata repository giving you full scale control.
There are 7 different contexts supported so far:
- A Concept Map (CmapTools, CXL/XML format)
- An OASIS OData CSDL Definition XML-file
- A XML Schema
- A StarUML Class Model in XPD-format
- An Eclipse PapyrusUML Class Model in a XMI-file
- A UML Class Model in SparxSystems’ EA Tool in a XMI-file
- A Data Model from FileMaker in a database report in XML format
The book also explains how to build a simple graph-based metadata repository for:
- Business level concept models
- Solution level logical data models, and
- Physical models.
Cypher-scripts for repository handling are indeed also part of the book (under a MIT license)..
We suggest a choice of two approaches:
- Fast Track Data Models (agile)
- Super Data Models (crafted, using the repository):