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Investments

PNNL’s Laboratory Directed Research and Development, or LDRD, program is the primary mechanism for renewing capabilities within the Laboratory and introducing novel ideas that will become the next generation of science and technology. Over the last several years, PNNL has made LDRD investments to launch initiatives that have created new analytic algorithms, tools, and methods.

PNNL currently leads the following intiatives related to analytics:

Analysis in Motion Initiative

Analysis in Motion Initiative develops a new analysis paradigm to provide continuous, automated synthesis of new knowledge and dynamic control of measurement systems contemporaneously with observed phenomena.

The Analysis in Motion (AIM) Initiative will develop a new analysis paradigm to provide continuous, automated synthesis of new knowledge and dynamic control of measurement systems contemporaneously with observed phenomena. By focusing on new semi-automated methods for hypothesis construction from streaming data, and by rebalancing effort between humans and machines, AIM will result in an improved ability to rapidly put new observations in the context of evolving domain knowledge. To achieve this goal, AIM will focus its research activities on four areas, the combination of which accelerates a complete analysis cycle that connects data collection, interpretation, and action.

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Asymmetric Resilient Cybersecurity Initiative

The Asymmetric Resilient Cybersecurity Initiative is working to deliver the theory, processes, methodologies, and algorithms that will enable a resilient cyber infrastructure with an asymmetric advantage to thwart adversaries who seek to infiltrate and damage our national security through digital means.

The Asymmetric Resilient Cybersecurity Initiative is working to deliver the theory, processes, methodologies, and algorithms that will enable a resilient cyber infrastructure with an asymmetric advantage to thwart adversaries who seek to infiltrate and damage our national security through digital means. We hypothesize that we can create resilient infrastructures and simultaneously move the asymmetric advantage from the attacker to the defender thereby altering how cybersecurity is implemented today.

These capabilities will be driven by and measured by real-time security posture and cost-benefits metrics as well as integrated dynamic, multi-scale graph analytics. This resilient infrastructure will then:

  • protect energy generation and distribution SCADA systems thereby increasing energy infrastructure reliability
  • protect nuclear systems preventing their infiltration by malicious actors
  • improve the ability to anticipate, monitor, engage, and respond to threats, and thereby more effectively prevent and counter terrorism.

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Signature Discovery Initiative

Signature Discovery Initiative is enabling decision-makers' ability to anticipate future events by detecting precursor signatures.

A signature is a unique or distinguishing measurement, pattern, or collection of data that predicts, detects, or identifies a phenomenon (object, action, or behavior) of interest. Researchers at PNNL are developing a methodology that will enable decision-makers’ ability to

  • anticipate future events by detecting precursor signatures, such as combinations of line overloads that may lead to a cascading power failure, biomarkers for the onset of disease and mechanical and chemical hallmarks of material fatigue
  • diagnose current conditions by matching observations against known signatures, such as the characterization of chemical processes via comparisons against known emission spectra
  • analyze past events by examining signatures left behind, such as the identity of cyber hackers whose techniques conform to a known modus operandi. Such analyses can contribute to larger signature libraries which in turn serve as a resource for future anticipation and characterization.

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Platform for Regional Integrated Modeling and Analysis

PNNLís Platform for Regional Integrated Modeling and Analysis, or PRIMA, is a unique capability for simulating complex interactions among human and natural systems at decision-relevant spatial scales.

PNNL’s Platform for Regional Integrated Modeling and Analysis, or PRIMA, is a unique capability for simulating complex interactions among human and natural systems at decision-relevant spatial scales. By bringing together models of climate, socioeconomics, hydrology, agriculture, buildings, electricity, and other sectors in a consistent, multi-scale framework that accounts for larger-scale drivers and boundary conditions, PRIMA helps regional stakeholders develop and evaluate strategies for responding to complex socioeconomic and environmental changes.

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Control of Complex Systems Initiative

PNNLís new Control of Complex Systems Initiative is an internally funded research initiative that aims to develop mathematical foundations for how the many, diverse components of complex systems in our world collectively operate.

PNNL’s new Control of Complex Systems Initiative is an internally funded research initiative that aims to develop mathematical foundations for how the many, diverse components of complex systems in our world collectively operate. The Control of Complex Systems Initiative team will focus on the power grid and grid-connected buildings in the initiative’s initial phases, with an ultimate goal of understanding how the future power system could function. That knowledge would be used to power our homes and cities in a more efficient, seamless manner.

Future Power Grid Initiative

The Future Power Grid Initiative (FPGI) will deliver next-generation concepts and tools for grid operation and planning and ensure a more secure, efficient, and reliable future grid.

The Future Power Grid Initiative (FPGI) will deliver next-generation concepts and tools for grid operation and planning and ensure a more secure, efficient, and reliable future grid. Building on the Electricity Infrastructure Operations Center, PNNL’s national electric grid research facility, FPGI will advance the science and develop the technologies necessary for meeting the nation’s expectations for a highly reliable and efficient electric grid, reducing carbon emissions and our dependence on foreign oil.

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In the past, PNNL has led the following intiatives related to analytics:

Data Intensive Computing Initiative

The Data Intensive Computing Initiative (DICI) focused on the creation of tools and capabilities to address the data overload challenge in the fields of bioinformatics, energy, and cyber analytics.

The Data Intensive Computing Initiative (DICI) focused on the creation of tools and capabilities to address the data overload challenge in the fields of bioinformatics, energy, and cyber analytics. Through analytic algorithms, software architectures, and hybrid hardware architectures, DICI provided more than ten new means that feed into the mission of creating a world in which large amounts of data don’t impede human understanding. Since these tools were built, researchers and analysts both in and out of the laboratory have been able to move towards better scientific discoveries.

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Technosocial Predictive Analytics Initiative

The Threat Anticipation Initiative is a collaboration among Battelle, PNNL, and Oak Ridge National Laboratory to stimulate advances in computable scenario representation and evidence integration to help decision-makers and analysts anticipate novel threats.

The Technosocial Predictive Analytics Initiative (TPAI) is taking the next steps to addressing complex, interwoven issues with highly integrated, innovative models to help analysts and policy makers identify and counter strategic surprise. TPAI endeavors to support a multi-perspective approach to predictive analysis through integrated reasoning with knowledge insights from both the natural and social sciences. More specifically, TPAI define, develop, and evaluate novel modeling algorithms that integrate domain knowledge about interacting physical and human factors. In so doing, TPAI combines expertise from the natural and social sciences, and enables its modeling algorithms with ancillary capabilities aimed at procuring knowledge inputs and enhancing cognitive access.

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Threat Anticipation Initiative

The Threat Anticipation Initiative is a collaboration among Battelle, PNNL, and Oak Ridge National Laboratory to stimulate advances in computable scenario representation and evidence integration to help decision-makers and analysts anticipate novel threats. This multi-project initiative performs coordinated research in the areas listed below:

  • content analysis and information extraction
  • knowledgebase development and ontology integration
  • scenario schemata, datastores, and interfacing
  • inference engines and expert knowledge elicitation
  • representing socio-cultural understanding
  • serious gaming for scenario elicitation.

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Analytics at PNNL