Environmental Data Science

Environmental Informatics applies data systems and analytical tools to extract insights and understanding from large volumes of environmental data. Battelle’s data systems support all kinds of environmental programs and research projects, including restoration projects, ecological research and long-term environmental monitoring programs.

Our team can: 

• Optimize Environmental Data Systems: The volume, velocity and variety (three “Vs”) of environmental data collection puts tremendous stress on data systems. At the same time, the pace of decision making and increasingly sophisticated questions from researchers, regulators and other stakeholders demand systems that accelerate data throughput and enable integration of varied lines of evidence. We will design—or redesign—your environmental data systems to improve data stability, preserve data integrity and make your data more accessible and usable for all of your stakeholders.
• Improve and Preserve Environmental Data Quality: Our data scientists will work with you to develop data quality systems and methods that improve the accuracy, precision, completeness, replicability and representativeness of your data. We will optimize your data collection and management systems and standardize data collected from disparate sources so your data products are accurate, comparable and repeatable. 
• Reveal Defensible Insights From Environmental Data: Making effective remediation, policy or regulatory decisions requires going beyond “number crunching.” Our systems allow data to be used to answer complicated environmental questions, draw defensible conclusions and communicate complex information to all stakeholders. 

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Battelle combines subject matter expertise in environmental sciences and information technology to design practical data quality systems tailored to environmental research programs. Our Environmental Informatics team builds customized informatics solutions, using world-class data science informed by a deep understanding of the realities of environmental data collection and focusing on the research questions that users need to answer. 

Environmental Data System Design and Optimization 

Environmental Data System Design: Our data systems are built around your lines of evidence, data quality objectives, data collection methods, interoperability needs, security requirements and budget. 

Decision Support and Conceptual Site Modeling: Battelle ensures that your data work more effectively in environmental research, restoration or policy decisions because our system designs are framed that way. 

Workflow-Based Requirements Analyses & Acceptability Testing: We use workflow-based requirements analyses to design systems for complex environmental investigations. 

Legacy System Migrations or Improvement via Distributed Services: Battelle helps clients retain the value of legacy systems while also exploiting newer technologies, approaches or efficiencies. 

Data Quality Systems

Quality Management Plans: Our quality management plans address program quality and organizational leadership. We’ll design a quality system for you that holds up from the field to the lab to the decision. 

Lifecycle Management of Sample Custody and Lab Providers: Our barcode-based sample management systems let you track environmental samples every step of the way from field collection plans to final recording of laboratory results. Our electronic data deliverable (EDD) protocols handle diverse formats used by Laboratory Information Management Systems (LIMS). 

Cyberinfrastructure with Embedded Quality Control: Battelle addresses data quality, beginning at the moment of capture through real-time QC, with synchronized lexicons and place-specific constraints so data producers can solve issues immediately. 

Data Analytics, Visualization and Query 

Data Analytics: Because decision models are the foundation of Battelle’s system designs, our data analytics tools readily convert environmental data into relevant information, intuitive visualizations, reliable predictions and defensible decisions. Our flexible, iterative analytical models enable sensitivity analyses, human health risk projections and decision tradeoffs.

Data Visualization: Our data visualization tools turn complex environmental data into easily digestible information in the form of charts, graphs, maps or animations. They allow users to quickly see patterns and trends in environmental data and communicate complex information to non-technical stakeholders. 

Semantic Search: Battelle applies advanced analytical methods—including machine learning, natural language processing and ontology development—to help researchers find fast answers to complex questions. Using our ontology-based approach, our semantic programs quickly return relevant and meaningful results, reducing the time required to analyze large datasets or find relevant information from large libraries of scientific literature. 

When you come to Battelle, you can have confidence that your data systems will be optimized for your specific needs and built to preserve data quality, validity and comparability. Our systems are designed to enable effective data-driven decisions for your environmental programs.