skip to main content
10.1145/3400903.3400908acmotherconferencesArticle/Chapter ViewAbstractPublication PagesssdbmConference Proceedingsconference-collections
research-article

Towards Co-Evolution of Data-Centric Ecosystems

Authors Info & Claims
Published:30 July 2020Publication History

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.

References

  1. Sean Bechhofer, David De Roure, Matthew Gamble, Carole Goble, and Iain Buchan. 2010. Research Objects: Towards Exchange and Reuse of Digital Knowledge. Nature Precedings (2010).Google ScholarGoogle Scholar
  2. Philip A Bernstein, Jayant Madhavan, and Erhard Rahm. 2011. Generic Schema Matching, Ten Years Later. Proceedings of the VLDB Endowment 4, 11 (2011).Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. James F Brinkley, Shannon Fisher, Matthew P Harris, Greg Holmes, 2016. The FaceBase Consortium: a comprehensive resource for craniofacial researchers.Development (Cambridge, England) 143, 14 (2016), 2677–88.Google ScholarGoogle Scholar
  4. Alejandro Bugacov, Karl Czajkowski, Carl Kesselman, Anoop Kumar, Robert E. Schuler, and Hongsuda Tangmunarunkit. 2017. Experiences with DERIVA: An asset management platform for accelerating eScience. In Proceedings - 13th IEEE International Conference on eScience, eScience 2017. 79–88.Google ScholarGoogle ScholarCross RefCross Ref
  5. K. Chard, M. D’Arcy, B. Heavner, I. Foster, C. Kesselman, R. Madduri, A. Rodriguez, S. Soiland-Reyes, C. Goble, K. Clark, E. W. Deutsch, I. Dinov, N. Price, and A. Toga. 2016. I’ll take that to go: Big data bags and minimal identifiers for exchange of large, complex datasets. In 2016 IEEE International Conference on Big Data (Big Data). 319–328.Google ScholarGoogle Scholar
  6. Peter Pin-Shan Chen. 1976. The Entity-Relationship Model—toward a Unified View of Data. ACM Trans. Database Syst. 1, 1 (March 1976), 9–36.Google ScholarGoogle Scholar
  7. The ENCODE Project Consortium, Ian Dunham, Anshul Kundaje, Shelley F. Aldred, 2012. An integrated encyclopedia of DNA elements in the human genome. Nature 489 (09 2012), 57 EP –.Google ScholarGoogle Scholar
  8. Carlo Curino, Hyun Jin Moon, Alin Deutsch, and Carlo Zaniolo. 2013. Automating the Database Schema Evolution Process. The VLDB Journal 22, 1 (Feb. 2013), 73–98.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. C. A. Curino, H. J. Moon, M. Ham, and C. Zaniolo. 2009. The PRISM Workwench: Database Schema Evolution without Tears. In 2009 IEEE 25th International Conference on Data Engineering. 1523–1526.Google ScholarGoogle Scholar
  10. Karl Czajkowski, Carl Kesselman, Robert E. Schuler, and Hongsuda Tangmunarunkit. 2018. ERMrest: A Web Service for Collaborative Data Management. In Proceedings of the 30th International Conference on Scientific and Statistical Database Management(SSDBM ’18). ACM, New York, NY, USA, 13:1–13:12.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Jürgen Engel, Christian Herdin, and Christian Märtin. 2014. Evaluation of model-based user interface development approaches. In International Conference on Human-Computer Interaction. Springer, 295–307.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Jim Gray, David T. Liu, Maria Nieto-Santisteban, Alex Szalay, David J. DeWitt, and Gerd Heber. 2005. Scientific Data Management in the Coming Decade. SIGMOD Rec. 34, 4 (Dec. 2005), 34–41.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Kai Herrmann, Hannes Voigt, Jonas Rausch, Andreas Behrend, and Wolfgang Lehner. 2017. Living in Parallel Realities – Co-Existing Schema Versions with a Bidirectional Database Evolution Language. In SIGMOD’17, Proceedings of the 2017 International Conference on Management of Data, Chicago, IL, USA, May 14-19, 2017. ACM.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. S. Jansen, A. Finkelstein, and S. Brinkkemper. 2009. A sense of community: A research agenda for software ecosystems. In 2009 31st International Conference on Software Engineering - Companion Volume. 187–190.Google ScholarGoogle Scholar
  15. W James Kent, Charles W Sugnet, Terrence S Furey, Krishna M Roskin, Tom H Pringle, Alan M Zahler, and David Haussler. 2002. The human genome browser at UCSC. Genome research 12, 6 (06 2002), 996–1006.Google ScholarGoogle Scholar
  16. Ravi Madduri, Kyle Chard, Mike D’Arcy, Segun C. Jung, Alexis Rodriguez, Dinanath Sulakhe, Eric Deutsch, Cory Funk, Ben Heavner, Matthew Richards, Paul Shannon, Gustavo Glusman, Nathan Price, Carl Kesselman, and Ian Foster. 2019. Reproducible big data science: A case study in continuous FAIRness. PLOS ONE 14, 4 (04 2019), 1–22.Google ScholarGoogle Scholar
  17. Sergey Melnik, Erhard Rahm, and Philip A. Bernstein. 2003. Rondo: A Programming Platform for Generic Model Management. In Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data(SIGMOD ’03). ACM, New York, NY, USA, 193–204.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. PostgreSQL contributors. 2020. CREATE VIEW. https://www.postgresql.org/docs/12/sql-createview.html [Online; accessed 06-March-2020].Google ScholarGoogle Scholar
  19. Dong Qiu, Bixin Li, and Zhendong Su. 2013. An Empirical Analysis of the Co-Evolution of Schema and Code in Database Applications. In Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering(ESEC/FSE 2013). Association for Computing Machinery, New York, NY, USA, 125–135.Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Susanna-Assunta Sansone, Philippe Rocca-Serra, Marco Brandizi, Alvis Brazma, Dawn Field, Jennifer Fostel, Andrew G Garrow, Jack Gilbert, Federico Goodsaid, Nigel Hardy, 2008. The first RSBI (ISA-TAB) workshop:“can a simple format work for complex studies?”. OMICS A Journal of Integrative Biology 12, 2 (2008), 143–149.Google ScholarGoogle ScholarCross RefCross Ref
  21. Robert Schuler, Alejandro Bugacov, Matthew Blow, and Carl Kesselman. 2019. Toward FAIR Knowledge Turns in Bioinformatics. In 2019 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2019). IEEE, San Diego, CA.Google ScholarGoogle Scholar
  22. Robert Schuler, Carl Kesselman, and Karl Czajkowski. 2015. Data Centric Discovery with a Data-Oriented Architecture. In Proceedings of the 1st Workshop on The Science of Cyberinfrastructure: Research, Experience, Applications and Models(SCREAM ’15). ACM, New York, NY, USA, 37–44.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Robert E. Schuler and Carl Kesselman. 2019. A High-level User-oriented Framework for Database Evolution. In 31st International Conference on Scientific and Statistical Database Management (SSDBM ’19). ACM, New York, NY, USA, 12.Google ScholarGoogle Scholar
  24. Susan Leigh Star and James R. Griesemer. 1989. Institutional Ecology, ‘Translations’ and Boundary Objects: Amateurs and Professionals in Berkeley’s Museum of Vertebrate Zoology, 1907-39. Social Studies of Science 19, 3 (1989), 387–420.Google ScholarGoogle ScholarCross RefCross Ref
  25. M. Stonebraker, D. Deng, and M. L. Brodie. 2016. Database decay and how to avoid it. In 2016 IEEE International Conference on Big Data (Big Data). 7–16.Google ScholarGoogle ScholarCross RefCross Ref
  26. Michael Stonebraker, Dong Deng, and Michael L Brodie. 2017. Application-database co-evolution: A new design and development paradigm. New England Database Day(2017), 1–3.Google ScholarGoogle Scholar
  27. Juan Antonio Vizcaíno, Attila Csordas, Noemi Del-Toro, José A Dianes, 2016. 2016 update of the PRIDE database and its related tools. Nucleic acids research 44, D1 (2016), D447–D456.Google ScholarGoogle Scholar
  28. Wikipedia contributors. 2020. Object-relational mapping. https://en.wikipedia.org/wiki/Object-relational_mapping [Online; accessed 06-March-2020].Google ScholarGoogle Scholar
  29. Mark D. Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3 (03 2016), 160018 EP –.Google ScholarGoogle Scholar

Recommendations

Comments

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Sign in
  • Published in

    cover image ACM Other conferences
    SSDBM '20: Proceedings of the 32nd International Conference on Scientific and Statistical Database Management
    July 2020
    241 pages
    ISBN:9781450388146
    DOI:10.1145/3400903

    Copyright © 2020 ACM

    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 30 July 2020

    Permissions

    Request permissions about this article.

    Request Permissions

    Check for updates

    Qualifiers

    • research-article
    • Research
    • Refereed limited

    Acceptance Rates

    Overall Acceptance Rate56of146submissions,38%

PDF Format

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format .

View HTML Format