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At least 271 records · Page 15

A Posteriori Ontology Engineering for Data-Driven Science

Science—and biology in particular—has a rich tradition in categorical knowledge management. This continues today in the generation and use of formal ontologies. Unfortunately, the link between hard data and ontological content is predominately qualitative, not quantitative. The usual approach is to construct ontologies of qualitative concepts, and then annotate the data to the ontologies. This process has seen great value, yet it is laborious, and the success to which ontologies are managing and organizing the full information content of the data is uncertain. An alternative approach is the converse: use the data itself to quantitatively drive ontology creation. Under this model, one generates ontologies at the time they are needed, allowing them to change as more data influences both their topology and their concept space. We outline a combined approach to achieve this, taking advantage of two technologies, the mathematical approach of Formal Concept Analysis (FCA) and the semantic web technologies of the Web Ontology Language (OWL).

Gessler, Damian Dg↗

Bringing Fenton Hill into the Digital Age: Data Conversion in Support of the Geothermal Technologies Office Code Comparison Study Challenge Problems

The Geothermal Technologies Office Code Comparison Study (GTO-CCS) was established by the U.S. Department of Energy to facilitate collaboration among members of the geothermal modeling community and to evaluate and improve upon the ability of existing codes to simulate thermal, hydrological, mechanical, and chemical processes associated with complex enhanced geothermal systems (EGS). The first stage of the project, which has been completed, involved comparing simulations for seven benchmark problems that were primarily designed using well-prescribed, simplified data sets. In the second stage, the participating teams are tackling two challenge problems based on the EGS research conducted in hot dry rock (HDR) at Fenton Hill, near Los Alamos, New Mexico. The Fenton Hill project, conducted by Los Alamos National Laboratory (LANL) from 1970 to 1995, was the world’s first HDR demonstration project. One of the criteria for selecting this experiment as the basis for the challenge problems was the amount and availability of data for generating model inputs. The Fenton Hill HDR system consisted of two reservoirs – an earlier Phase I reservoir tested from 1974 to 1981 and a deeper Phase II reservoir tested from 1980 to 1995. Detailed accounts of both phases of the HDR project have been presented in a number of books and reports, including a recently published summary of the lessons learned and a final report with a chronological description of the Fenton Hill project, prepared by LANL. Project documents and records have been archived and made public through the National Geothermal Data System (NGDS). Some of the data acquired from Phase II are available in electronic format readable on modern computers. These include the microseismic data from some of the important experiments (e.g. the massive hydraulic fracturing test conducted in 1983) and the injection/production wellhead data from the circulation tests conducted between 1992-1995. However, much of the data collected during the project, while publicly available, currently only exist in the form of tables or graphs within scanned documents. Therefore, in support of the GTO-CCS, the data needed for developing simulation inputs are being compiled and converted to platform independent, open readable formats so that all participating teams will have access to the same electronic data set. In some cases this requires conversion using optical character recognition, digitizing existing images, and generating the appropriate metadata from project documents. The GTO-Velo knowledge management framework, developed by Pacific Northwest National Laboratory (PNNL), was used for the benchmark problem stage of the comparison study and will also be used as the data repository for the challenge problem data sets. It is staggering and impractical to convert all published data for the Fenton Hill site, so the focus is on data that supports simulations for the three topical areas defined by the study for the challenge problems: 1) reservoir creation/stimulation, 2) reactive and passive transport, and 3) thermal recovery. Conversion of these data provide value not only to GTO-CCS participants, but also to members of the geothermal community at large who may be interested in revisiting the Fenton Hill experiment in the future.

Code Comparison Study↗

Knowledge catalysts

A computer implemented method integrates data from remote disparate data sources by processing a non-transitory media. The non-transitory media stores instructions for detecting data sets in different formats hosted in a plurality of heterogeneous databases that are accessible through a distributed network. The method extracts schema data from the plurality of heterogeneous databases and identifies related fields in two or more of the heterogeneous databases. The method links the related fields in the two or more of the plurality of heterogeneous databases and makes the data accessible through a virtual warehouse. As schemas change, as new data sources and analysis artifacts are created, the computer implemented method and system can act as a meta-data store, a provenance tracking device, and/or a knowledge management service.

97 MATHEMATICS AND COMPUTING↗

Enhancing Lifeline Infrastructure Resilience

Establish operational critical infrastructure research environment with focus on control systems security Continue enhancement of critical infrastructure cyber-physical interdependency analysis and knowledge management capabilities

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Adaptation of Commercially Available Robots for Conditioning and Packaging ILW at Sellafield - 18282

The Legacy Ponds and Silos at Sellafield site contain some of the most hazardous Intermediate Level Waste (ILW) in the UK. As part of a multi-billion pound decommissioning programme, this waste will be retrieved and transported across the site for conditioning and packaging in the Box Encapsulation Plant (BEP). Current plans are to commence plant active commissioning in 2022, which will represent a major milestone in the UK nuclear decommissioning programme. Within the plant, skips of waste will be transferred from the shielded transport package into standard 3 cubic metre ILW containers. Waste from the Pile Fuel Storage Pond and First Generation Magnox Storage Pond will be immobilised in cementitious grout before being transferred to an adjacent store. Waste from the Magnox Swarf Storage Silo will not be immobilised in grout, but will be packaged, providing multi-barrier containment. During the concept design, the project team selected commercially available robots as the most viable technology for carrying out the numerous dexterous and repetitive tasks involved in characterising, conditioning and packaging the waste within the shielded 'hot' cells. Significant technical challenges had to be overcome during the design to adapt a commercially available robot for use within a high radiation / high contamination environment, where human access is not safe even for short periods of time. These challenges included: - Designing robot assemblies that could be retrofitted into the existing cell structure that was constructed as part of an earlier project but never completed; - Designing robot assemblies that could be recovered to their 'transport' position without requiring manual intervention; - Designing robot assemblies that could be remotely removed and replaced with new ones if they failed part way through the plant operational life; - Designing through-wall service and power connections that allow maintenance and recovery; - Designing control systems and human-machine interfaces that enable both manual and automated operation of the robot, whilst avoiding collisions with the in-cell cranes and other in cell furniture; - Assessing the radiation tolerance of all items. Bespoke computer simulations and full-scale development trials have been carried out, using non-active test materials, in order to demonstrate the Technology Readiness Level (TRL) required by Sellafield Limited (SL) at each stage of the project [1]. The results of these trials have been recorded in both video and written form so that they can form part of the project's Knowledge Management database. Detailed designs and specifications for the robot assemblies have been updated to incorporate the recommendations from the development trials. Procurement and manufacture of robot assemblies has already commenced to deliver two waste handling robots, two waste container lidding / swabbing robots and associated critical spares. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

MIKA: Manager for Intelligent Knowledge Access Toolkit for Engineering Knowledge Discovery and Information Retrieval

Repositories of safety reports are often underutilized and only analyzed manually by trained experts, despite safety management systems requiring reports. These collections of documents contain a wealth of information from past projects and operations that could improve system safety and design. Advances in natural language processing techniques have improved information extraction and retrieval in consumer technology, biomedicine, and finance, for instance, but have not been applied to engineering documents on the same scale. To this end, the Manager for Intelligent Knowledge Access (MIKA) open-source toolkit has been developed for rapid knowledge discovery and information retrieval in safety engineering applications. The MIKA toolkit uses state-of-the-art natural language processing algorithms and allows a user to apply these methods to their own dataset. This paper describes the MIKA toolkit and its two primary capabilities, knowledge discovery and information retrieval, and demonstrates the toolkit via a case study on National Transportation Safety Board (NTSB) reports.

Machine Learning↗

MIKA: Manager for Intelligent Knowledge Access Toolkit for Engineering Knowledge Discovery and Information Retrieval

Repositories of safety reports are often underutilized and only analyzed manually by trained experts, despite safety management systems requiring reports. These collections of documents contain a wealth of information from past projects and operations that could improve system safety and design. Advances in natural language processing techniques have improved information extraction and retrieval in consumer technology, biomedicine, and finance, for instance, but have not been applied to engineering documents on the same scale. To this end, the Manager for Intelligent Knowledge Access (MIKA) open-source toolkit has been developed for rapid knowledge discovery and information retrieval in safety engineering applications. The MIKA toolkit uses state-of-the-art natural language processing algorithms and allows a user to apply these methods to their own dataset. This paper describes the MIKA toolkit and its two primary capabilities, knowledge discovery and information retrieval, and demonstrates the toolkit via a case study on National Transportation Safety Board (NTSB) reports.

Systems Engineering↗

Integrating Indigenous Traditional, Local and Scientific Knowledge for Improved Management, Policy and Decision-Making in Reindeer Husbandry in the Russian Arctic

As scientists and policy-makers from both indigenous and non-indigenous communities begin to build closer partnerships to address common sustainability issues such as the health impacts of climate change and anthropogenic activities, it becomes increasingly important to create shared information management systems which integrate all relevant factors for optimal information sharing and decision-making. This paper describes a new GIs-based system being designed to bring local and indigenous traditional knowledge together with scientific data and information, remote sensing, and information technologies to address health-related environment, weather, climate, pollution and land use change issues for improved decision/policy-making for reindeer husbandry. The system is building an easily-accessible archive of relevant current and historical, traditional, local and remotely-sensed and other data and observations for shared analysis, measuring, and monitoring parameters of interest. Protection of indigenous culturally sensitive information will be respected through appropriate data protocols. A mechanism which enables easy information sharing among all participants, which is real time and geo-referenced and which allows interconnectivity with remote sites is also being designed into the system for maximum communication among partners. A preliminary version of our system will be described for a Russian reindeer test site, which will include a combination of indigenous knowledge about local conditions and issues, remote sensing and ground-based data on such parameters as the vegetation state and distribution, snow cover, temperature, ice condition, and infrastructure.

Maynard, Nancy G.↗

Machine intelligence and autonomy for aerospace systems

The present volume discusses progress toward intelligent robot systems in aerospace applications, NASA Space Program automation and robotics efforts, the supervisory control of telerobotics in space, machine intelligence and crew/vehicle interfaces, expert-system terms and building tools, and knowledge-acquisition for autonomous systems. Also discussed are methods for validation of knowledge-based systems, a design methodology for knowledge-based management systems, knowledge-based simulation for aerospace systems, knowledge-based diagnosis, planning and scheduling methods in AI, the treatment of uncertainty in AI, vision-sensing techniques in aerospace applications, image-understanding techniques, tactile sensing for robots, distributed sensor integration, and the control of articulated and deformable space structures.

Heer, Ewald↗

Capturing, using, and managing quality assurance knowledge for shuttle post-MECO flight design

Ascent initialization values used by the Shuttle's onboard computer for nominal and abort mission scenarios are verified by a six degrees of freedom computer simulation. The procedure that the Ascent Post Main Engine Cutoff (Post-MECO) group uses to perform quality assurance (QA) of the simulation is time consuming. Also, the QA data, checklists and associated rationale, though known by the group members, is not sufficiently documented, hindering transfer of knowledge and problem resolution. A new QA procedure which retains the current high level of integrity while reducing the time required to perform QA is needed to support the increasing Shuttle flight rate. Documenting the knowledge is also needed to increase its availability for training and problem resolution. To meet these needs, a knowledge capture process, embedded into the group activities, was initiated to verify the existing QA checks, define new ones, and document all rationale. The resulting checks were automated in a conventional software program to achieve the desired standardization, integrity, and time reduction. A prototype electronic knowledge base was developed with Macintosh's HyperCard to serve as a knowledge capture tool and data storage.

Peters, H. L.↗

Knowledge-Based System for Flight Information Management

The use of knowledge-based system (KBS) architectures to manage information on the primary flight display (PFD) of commercial aircraft is described. The PFD information management strategy used tailored the information on the PFD to the tasks the pilot performed. The KBS design and implementation of the task-tailored PFD information management application is described. The knowledge acquisition and subsequent system design of a flight-phase-detection KBS is also described. The flight-phase output of this KBS was used as input to the task-tailored PFD information management KBS. The implementation and integration of this KBS with existing aircraft systems and the other KBS is described. The flight tests are examined of both KBS's, collectively called the Task-Tailored Flight Information Manager (TTFIM), which verified their implementation and integration, and validated the software engineering advantages of the KBS approach in an operational environment.

Ricks, Wendell R.↗

White Paper on Data Repository Reorganization Proposal for the xLPR Project

As the xLPR project moves along, it is important to properly manage the knowledge generated by the different groups. We focus specifically on the knowledge and communications written in files, including general documents, source code and executable files. Data generated through the project are different in nature and, for this reason, need to be treated differently. To that end, ORNL put in place a series of tools that facilitate proper storage and management of project data, document and code changes, group collaboration, knowledge transfer, transparency, accountability and auditability. This paper describes the approaches/tools that we recommend for moving the project forward on knowledge management.

Klasky, Hilda B.↗

Department of Energy Training Institute Improves Delivery of Training - 17040

The Department of Energy Training Institute (DTI) was established in March 2016 to provide training enhancements for the DOE enterprise. Effective training improves worker safety and directly supports the completion of DOE missions. The overall intent of DTI is to reduce redundant training, improve safety, and avoid duplicate course training development and subsequently reduce future training maintenance costs. Implementation of the DTI initiatives of training reciprocity, common core fundamental course materials, instructor certification, and providing training support tools such as the Course and Related Data System (CARDS) has resulted in direct and indirect cost avoidances. (authors)

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Building a Knowledge Graph for the Air Traffic Management Community

Historically, most of the focus in the knowledge graph community has been on the support for web, social network, or product search applications. This paper describes some of our experience in developing a large-scale applied knowledge graph for a more technical audience with more specialized information access and analysis needs - the air traffic management community. We describe ATMGRAPH (NASA's Air Traffic Management (ATM) Knowledge Graph), a knowledge graph created by integrating various sources of structured aviation data, provided in large part by US federal agencies. We review some of the practical challenges we faced in creating this knowledge graph.

Air Traffic Information Management↗

Beyond knowledge capture: creating useful work-centric systems

Once you have successfully captured knowledge, the challenge then becomes one of creating an affective way to use that knowledge. Two high knowledge content systems developed at the Jet Propulsion Laboratory are presented as examples of work-centric systems, where the primary value to the user is in the content.

knowledge management environment knowledge capture↗