Socio-ecological informatics

Addressing issues in accessing and archiving data in social ecological systems research

Social-ecological systems (SES) is the study of interactions between environment, users, and governance of environmental resources. Examples include forests, fisheries, and irrigation systems.

SES data is longitudinal and long-tail data, pose questions such as:

  • How can we archive a longitudinal SES relational database?
  • How can we better represent and query this type of data?
  • How can we organize and access SES data featuring in long tail?


The IFRI case

A core motivator for the group is the International Forestry Resources and Institutions (IFRI) database, of The Vincent and Elinor Ostrom Workshop in Political Theory and Policy Analysis. The IFRI database stores nearly 20 years of longitudinal data since 1992 on forest resources, resource users, and forest governance at locations worldwide.

IFRI is a complex ongoing longitudinal relational database, and thus presents challenges in both access and preservation. Our IViSER solution is designed to meet these challenges.

IViSER system framework

This is system framework that was initially designed for the IFRI case while can also be generalized onto other SES databases. It contains these key modules:

SES archive generator

It generates XML metadata archive from the IFRI relational database based on the mapping from the database schema to nested logical objects. See [6] for details.

SES classifier

It classifies survey questions by mapping them to predefined SES categories in Ostrom’s SES framework ([3,4]). See [6,7] for details.

IViSER i-viewer

Important SES objects such as site visit objects and forest objects, are extracted and stored in MongoDB, and are then represented in an ontology and visualized. See [8] for details.

IViSER table viewer

It is a user-friendly query interface where researchers can choose variables from database tables to query the database without knowing the schema of the database.

Demo for IFRI TableViewer
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Figure 1: The sub-graph of a single IFRI site visit viewed in Neo4j’s web-browser interface.
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Figure 2: The species Maesopsis eminii has been found disappeared in three different sites, each for a different reason (like the reason “timber cutting” for the selected node in this graph).


[1] David Bender, Miao Chen, Scott Jensen, David Leake, and Beth Plale, Whitepaper: Archival Trustworthiness and Semantically Rich Feature Based Access in Legacy Scientific Relational Databases, April 1, 2011

[2] Scott Jensen, Michael Cox, David Bender, Miao Chen, Julie England, Beth Plale, and David Leake, Spatial Data in an Ontology for Research on Forest Resources, Presented at "Ontology of Spatial Thinking and Reasoning: Multidiciplinary Reconciliation, COSIT'11 Workshop, Belfast Maine, September 12, 2011, pp. 28-30.

[3] Elinor Ostrom, A diagnostic approach for going beyond panaceas, PNAS, September 25, 2007 vol. 104 no. 39 pp. 15181-15187.

[4] E. Ostrom, A General Framework for Analyzing Sustainability of Social-Ecological Systems, Science, 325(5939), pp. 419-422, 2009.

[5] Beth Plale discusses the investigation of the In-Situ Archive (video)

[6] Scott Jensen, Beth Plale, Xiaozhong Liu, Miao Chen, David Leake, and Julie England. Generalized Representation and Mapping for Social-Ecological Data: Freeing Data from the Database , 8th IEEE International Conference on eScience (eScience 2012), Chicago, Illinois, October 2012.

[7] Scott Jensen, Miao Chen, Xiaozhong Liu, Beth Plale, and David Leake. Mining Classifications from Social-Ecological Databases (extended abstract and poster), 75th Annual Meeting of the American Society for Information Science and Technology (ASIS&T), Baltimore, MD, October 2012.

[8] Chen, M., Pavalanathan, U., Jensen, S., & Plale, B. (2013, July). Modeling heterogeneous data resources for social-ecological research: a data-centric perspective . In Proceedings of the 13th ACM/IEEE-CS joint conference on Digital libraries (pp. 309-312). ACM.

[9] Chen, P., B. Plale, Y. - W. Cheah, D. Ghoshal, S. Jensen, and Y. Luo, Visualization of Network Data Provenance Workshop on Massive Data Analytics on Scalable Systems (DataMASS 2012), co-located with the IEEE International Conference on High Performance Computing (HiPC), Pune, India, Dec 2012.


  • Beth Plale
  • David Leake
  • Inna Kouper
  • Julie England
  • Xiaozhong Liu
  • Kavitha Chandrasekar
  • Peng Chen
  • Miao Chen

Previous team members

  • Scott Jensen
  • Michael Cox
  • David Bender
  • Kalani Ruwanpathirana
  • Umashanthi Pavalanathan


National Science Foundation
In-situ archiving of digital scientific data

Data to Insight Center
Indiana University Pervasive Technology Institute