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. 2020 Jul:2020:4.
doi: 10.1145/3400903.3400908. Epub 2020 Jul 30.

Towards Co-Evolution of Data-Centric Ecosystems

Robert Schuler  1 , Karl Czajkowski  1 , Mike D'Arcy  1 , Hongsuda Tangmunarunkit  1 , Carl Kesselman  1
Affiliations

Towards Co-Evolution of Data-Centric Ecosystems

Robert Schuler et al. Sci Stat Database Manag. 2020 Jul.

Abstract

Database evolution is a notoriously difficult task, and it is exacerbated by the necessity to evolve database-dependent applications. As science becomes increasingly dependent on sophisticated data management, the need to evolve an array of database-driven systems will only intensify. In this paper, we present an architecture for data-centric ecosystems that allows the components to seamlessly co-evolve by centralizing the models and mappings at the data service and pushing model-adaptive interactions to the database clients. Boundary objects fill the gap where applications are unable to adapt and need a stable interface to interact with the components of the ecosystem. Finally, evolution of the ecosystem is enabled via integrated schema modification and model management operations. We present use cases from actual experiences that demonstrate the utility of our approach.

Keywords: application-database co-evolution; model management; schema evolution; software ecosystems.

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Figures

Figure 1:
Figure 1:
A typical data-driven ecosystem based on Deriva including (clockwise from top-right) web clients, command-line clients, export bundles, and visualization.
Figure 2:
Figure 2:
Example ER model (left) with schema annotations (middle) specifying model mappings for a model-adaptive interactive application (top-right) and a model-neutral command-line client (bottom-right).
Figure 3:
Figure 3:
Conceptual structure of expressions used for mapping entities from one context to another.
Figure 4:
Figure 4:
Anatomy of a boundary object.
Figure 5:
Figure 5:
Overview of the three primary patterns of database-client interaction.
Figure 6:
Figure 6:
Conceptual steps enacted by model-adaptive database clients.
Figure 7:
Figure 7:
Conceptual steps enacted by model-neutral database clients.
Figure 8:
Figure 8:
Decoupling and mediation of model-bound clients from the data service via a model-neutral service layer for producing and consuming boundary objects.
Figure 9:
Figure 9:
Architecture diagram highlighting extensions for integrating MMO capabilities.
Figure 10:
Figure 10:
Major schema evolution events in the FaceBase Data Hub: initial schema (S0), revised for greater experimental details (S1), and evolved for better reproducibility (S2).
Figure 11:
Figure 11:
Illustration of a bioinformatics pipeline supported by “bag” (boundary object) collections in the decoupled interaction model.
Listing 1:
Listing 1:
Rule definitions to translate assignment (logical) expressions into Create, Alter (and Rename), and Drop (physical) operators
See this image and copyright information in PMC

References

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