The document discusses using a model-view-controller (MVC) architecture to manage data modeling projects. It describes using an abstract data module based on the DDI ontology with concrete modules for each project that inherit and extend the abstract module. A RESTful interface is proposed to access resources identified by URIs. The abstract data model is implemented as domain classes with attributes and relations according to MVC and can generate views, storage models, and abstract persistence APIs. Extending the DDI ontology allows projects to add custom fields while maintaining compatibility. Sharing source code and data modules between projects via version control is described.

1. DDI & Model-View-Controller:
An Architectural Perspective
Dennis Wegener, Matthäus
Zloch, Thomas Bosch (GESIS)
Dagstuhl, 23.10.2012

2. Overview Architecture Missy/StarDat
Presentation MVC
Business Logic
Abstract Persistence
Persistence
Page 2

3. Software Management - Maven & GIT
• Apache Maven
– software project management and comprehension tool
• Maven Modules for data modelling in our projects:
– Abstract module for DDI (based on DDI ontology) DDI model
– Concrete modules for each project that
• Inherit from abstract ddi module DDI model DDI model
• Add project-specific data fields + Missy + StarDat
Extensions Extensions
• Sharing via VersionControlSystem
– Project sources in internal VCS (GESIS-SVN)
– Data Module shared externally (GIT)
• https://github.com/missy-project/ddi-model

4. Missy Maven Structure

5. Data model & presentation - MVC
• MVC design pattern
• Model
– Domain classes
– Attributes
– Relations
• View
– Representation
– JSP, Velocity, XML, JSON, …
• Controller
– Commands
– RESTful interface

6. RESTful interface
• Well-defined interface based on HTTP
– With few basic methods: GET, POST, PUT, DELETE
– Response codes (e.g. 200 OK, 404 Not Found)
– Data supported described by MIME types (e.g. text/xml,
application/json)
• Resources are identified using URIs
– Collection URI (like http://missy.org/studies)
– Element URI (like http://missy.org/studies/studyZA1000)
• Resources could map to domain classes / entities of the
DDI ontology

7. Data model & persistance – API
• Once you have the model you can…
– Generate views / user interfaces
– Generate storage model (in RDB via hibernate)
• Abstract persistance API
– To be published …
• Concrete Implementations
– Relational DB
– DDI XML files
–…

8. Missy Example
• Question:
– DDI Ontology: class Question,
fields like dcterms_identifier, …, field question text
• Variable:
– DDI Ontology: class Variable,
fields like dcterms_identifier,…
– Missy: inherits class Variable,
adds fields variable name, variable label, classification, …
• Relation:
– Variable * hasQuestion 1 Question
– Defined at level of DDI Ontology

9. Missy Extension
DDI Ontology
Page 9

10. Key Messages & Questions
• DDI model implemented as abstract data model in OO
programming language
– According to MVC - domain classes with attributes & relations
– Do we need a standard REST interface?
• DDI model not directly based on XML representation
– „Data model vs. Data format“
– Export mechanisms for XML based representation
• DDI model integrated into project‘s architectures
– Does it make sense to create a reference architecture?
• Reuse of software modules is possible
– We already share modules/code between internal projects Missy & StarDat
– Is anyone else interested in sharing?