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NASA NTRS2007

A Support Database System for Integrated System Health Management (ISHM)

The development, deployment, operation and maintenance of Integrated Systems Health Management (ISHM) applications require the storage and processing of tremendous amounts of low-level data. This data must be shared in a secure and cost-effective manner between developers, and processed within several heterogeneous architectures. Modern database technology allows this data to be organized efficiently, while ensuring the integrity and security of the data. The extensibility and interoperability of the current database technologies also allows for the creation of an associated support database system. A support database system provides additional capabilities by building applications on top of the database structure. These applications can then be used to support the various technologies in an ISHM architecture. This presentation and paper propose a detailed structure and application description for a support database system, called the Health Assessment Database System (HADS). The HADS provides a shared context for organizing and distributing data as well as a definition of the applications that provide the required data-driven support to ISHM. This approach provides another powerful tool for ISHM developers, while also enabling novel functionality. This functionality includes: automated firmware updating and deployment, algorithm development assistance and electronic datasheet generation. The architecture for the HADS has been developed as part of the ISHM toolset at Stennis Space Center for rocket engine testing. A detailed implementation has begun for the Methane Thruster Testbed Project (MTTP) in order to assist in developing health assessment and anomaly detection algorithms for ISHM. The structure of this implementation is shown in Figure 1. The database structure consists of three primary components: the system hierarchy model, the historical data archive and the firmware codebase. The system hierarchy model replicates the physical relationships between system elements to provide the logical context for the database. The historical data archive provides a common repository for sensor data that can be shared between developers and applications. The firmware codebase is used by the developer to organize the intelligent element firmware into atomic units which can be assembled into complete firmware for specific elements.

FROM↗

NASA NTRSDate not supplied

Exploring Lightning and Convective Processes Using the Ground-Radar Multiplatform Precipitation Feature Database

The Multiplatform Precipitation Feature (MPF) database synthesizes coincident spaceborne and ground-based lightning and radar data in a framework of storm-based features, fusing broader spaceborne detection capabilities with process-based, storm-level analysis practices. The MPF database was designed to extend the scale and scope of investigations into the complex connections between precipitation, updrafts, and lightning. The NASA International Space Station Lightning Imaging Sensor (ISS LIS) serves as the source of lightning information for the database. The first iteration of the MPF database leveraged the NASA Global Precipitation Measurement (GPM) mission spaceborne Dual-frequency Precipitation Radar (DPR) to define features, along with contributions of microphysics data and vertical wind retrievals from the GPM Validation Network (VN) of ground-based radar data. The dependency on coincident ISS and GPM satellite overpasses of radars in a dual-Doppler configuration significantly limited the size of the initial database of features, referred to as VNMPFs, but established the database infrastructure and feasibility. We present here a second iteration of the MPF database that omits the GPM DPR and VN, instead incorporating data directly from selected proximal installations of the operational Next Generation Radar (NEXRAD) network that facilitate vertical wind retrievals via dual-Doppler analysis. These features based exclusively on ground-based polarimetric Doppler radar are hereafter referred to as Ground-Radar MPFs (GRMPFs). Removing the restriction of a coincident GPM overpass appreciably increases the size of the GRMPF database while incorporating more detailed information from higher-resolution radar data and retrievals. This expansion allows for unprecedented broad, robust statistical analyses of the electrical, kinematic, and microphysical characteristics of deep convective processes. These results highlight the potential for advancements in lightning meteorology made possible by combining multiple perspectives from global lightning measurements and ground-based radar data.

Lightning↗

DOE OSTI2023

Design and requirements of a hydrogen component reliability database (HyCReD)

Hydrogen technologies are expected to play a key role in the decarbonization of several sectors including energy storage and transportation. Rigorous investigation and quantification of the risk and reliability issues associated with hydrogen technologies will be critical to ensuring both their wider adoption and safe, economical operations. Quantitative risk assessment (QRA) is an important tool that has been used to enable the safe deployment of many engineering systems, including hydrogen fueling stations and hydrogen storage systems. However, QRA studies require reliability data which is currently lacking for expanding applications of hydrogen systems. Here, to address this gap, we present a new structure for a hydrogen component reliability database (HyCReD) that can be used to generate reliability data to be used in QRA, reliability, safety studies, maintenance planning, and more. Building on our previous work examining four major hydrogen safety data collection tools (West et al., 2022) [1], our approach in this work was to consult scientific literature on reliability data collection as well as a number of existing reliability engineering databases in the oil & gas, chemical processing, and nuclear power plant sectors. The evaluation of these databases led to identifying best practices to be implemented in a data collection framework for a hydrogen component reliability database. Based on these best practices, a set of 24 requirements for the proposed database are presented, covering its characteristics and the types of data to be collected. We define the structure of the HyCReD database and 25 data elements to be collected, spanning system description, failure, shutdown, or near-miss events, and maintenance events. The data elements are then defined according to international standards used in the safety and reliability practice and potential choice lists are provided for each field. Since this database is being piloted for hydrogen fueling stations, a generic station component hierarchy developed by West (2021) [2] is used to standardize system data. Finally, we demonstrate populating the database with information extracted from five narrative reports on hydrogen fueling station incidents.

08 HYDROGEN↗

NASA NTRS1992

VIEWCACHE: An incremental pointer-based access method for autonomous interoperable databases

One of biggest problems facing NASA today is to provide scientists efficient access to a large number of distributed databases. Our pointer-based incremental database access method, VIEWCACHE, provides such an interface for accessing distributed data sets and directories. VIEWCACHE allows database browsing and search performing inter-database cross-referencing with no actual data movement between database sites. This organization and processing is especially suitable for managing Astrophysics databases which are physically distributed all over the world. Once the search is complete, the set of collected pointers pointing to the desired data are cached. VIEWCACHE includes spatial access methods for accessing image data sets, which provide much easier query formulation by referring directly to the image and very efficient search for objects contained within a two-dimensional window. We will develop and optimize a VIEWCACHE External Gateway Access to database management systems to facilitate distributed database search.

Roussopoulos, N.↗

NASA NTRS1998

US Gateway to SIMBAD Astronomical Database

During the last year the US SIMBAD Gateway Project continued to provide services like user registration to the US users of the SIMBAD database in France. User registration is required by the SIMBAD project in France. Currently, there are almost 3000 US users registered. We also provide user support by answering questions from users and handling requests for lost passwords. We have worked with the CDS SIMBAD project to provide access to the SIMBAD database to US users on an Internet address basis. This will allow most US users to access SIMBAD without having to enter passwords. This new system was installed in August, 1998. The SIMBAD mirror database at SAO is fully operational. We worked with the CDS to adapt it to our computer system. We implemented automatic updating procedures that update the database and password files daily. This mirror database provides much better access to the US astronomical community. We also supported a demonstration of the SIMBAD database at the meeting of the American Astronomical Society in January. We shipped computer equipment to the meeting and provided support for the demonstration activities at the SIMBAD booth. We continued to improve the cross-linking between the SIMBAD project and the Astro- physics Data System. This cross-linking between these systems is very much appreciated by the users of both the SIMBAD database and the ADS Abstract Service. The mirror of the SIMBAD database at SAO makes this connection faster for the US astronomers. The close cooperation between the CDS in Strasbourg and SAO, facilitated by this project, is an important part of the astronomy-wide digital library initiative called Urania. It has proven to be a model in how different data centers can collaborate and enhance the value of their products by linking with other data centers.

Eichhorn, G.↗

NASA NTRS2010

Exploring Discretization Error in Simulation-Based Aerodynamic Databases

This work examines the level of discretization error in simulation-based aerodynamic databases and introduces strategies for error control. Simulations are performed using a parallel, multi-level Euler solver on embedded-boundary Cartesian meshes. Discretization errors in user-selected outputs are estimated using the method of adjoint-weighted residuals and we use adaptive mesh refinement to reduce these errors to specified tolerances. Using this framework, we examine the behavior of discretization error throughout a token database computed for a NACA 0012 airfoil consisting of 120 cases. We compare the cost and accuracy of two approaches for aerodynamic database generation. In the first approach, mesh adaptation is used to compute all cases in the database to a prescribed level of accuracy. The second approach conducts all simulations using the same computational mesh without adaptation. We quantitatively assess the error landscape and computational costs in both databases. This investigation highlights sensitivities of the database under a variety of conditions. The presence of transonic shocks or the stiffness in the governing equations near the incompressible limit are shown to dramatically increase discretization error requiring additional mesh resolution to control. Results show that such pathologies lead to error levels that vary by over factor of 40 when using a fixed mesh throughout the database. Alternatively, controlling this sensitivity through mesh adaptation leads to mesh sizes which span two orders of magnitude. We propose strategies to minimize simulation cost in sensitive regions and discuss the role of error-estimation in database quality.

Aftosmis, Michael J.↗

NASA NTRS2011

Development of the Orion Crew Module Static Aerodynamic Database: Hypersonic - Part 1

The Orion aerodynamic database provides force and moment coefficients given the velocity, attitude, configuration, etc. of the Crew Exploration Vehicle (CEV). The database is developed and maintained by the NASA CEV Aerosciences Project team from computational and experimental aerodynamic simulations. The database is used primarily by the Guidance, Navigation, and Control (GNC) team to design vehicle trajectories and assess flight performance. The initial hypersonic re-entry portion of the Crew Module (CM) database was developed in 2006. Updates incorporating additional data and improvements to the database formulation and uncertainty methodologies have been made since then. This paper details the process used to develop the CM database, including nominal values and uncertainties, for Mach numbers greater than 8 and angles of attack between 140deg and 180deg. The primary available data are more than 1000 viscous, reacting gas chemistry computational simulations using both the Laura and Dplr codes, over a range of Mach numbers from 2 to 37 and a range of angles of attack from 147deg to 172deg. Uncertainties were based on grid convergence, laminar-turbulent solution variations, combined altitude and code-to-code variations, and expected heatshield asymmetry. A radial basis function response surface tool, NEAR-RS, was used to fit the coefficient data smoothly in a velocity-angle-of-attack space. The resulting database is presented and includes some data comparisons and a discussion of the predicted variation of trim angle of attack and lift-to-drag ratio. The database provides a variation in trim angle of attack on the order of +/-2deg, and a range in lift-to-drag ratio of +/-0.035 for typical vehicle flight conditions.

Bibb, Karen L.↗

NASA NTRS2018

Building a QC Database of Meteorological Data From NASA KSC and the United States Air Force's Eastern Range

The National Aeronautics and Space Administration's (NASA) Marshall Space Flight Center (MSFC) Natural Environments Branch (EV44) has provided atmospheric databases and analysis in support of space vehicle design and day-of-launch operations for NASA and commercial launch vehicle programs launching from the NASA Kennedy Space Center (KSC), co-located on the United States Air Force's Eastern Range (ER) at the Cape Canaveral Air Force Station. The ER is one of the most heavily instrumented sites in the United States measuring various atmospheric parameters on a continuous basis. An inherent challenge with the large databases that EV44 receives from the ER consists of ensuring erroneous data are removed from the databases, and thus excluded from launch vehicle design analyses. EV44 has put forth great effort in developing quality control (QC) procedures for individual meteorological instruments; however, no standard QC procedures for all databases currently exist resulting in QC databases that have inconsistencies in variables, methodologies, and periods of record. The goal of this activity is to use the previous efforts by EV44 to develop a standardized set of QC procedures from which to build flags within the meteorological databases from KSC and the ER, while maintaining open communication with end users from the launch community to develop ways to improve, adapt and grow the QC database. Details of the QC checks are described. The flagged data points will be plotted in a graphical user interface (GUI) as part of a manual confirmation that the flagged data do indeed need to be removed from the archive. As the rate of launches increases with additional launch vehicle programs, more emphasis is being placed to continually update and check weather databases for data quality before use in launch vehicle design and certification analyses.

Brenton, James C.↗

DOE OSTI2025

TropiRoot 1.0: Database of tropical root characteristics across environments

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

FRED↗

DOE OSTI2023

Cross-database comparisons on the greenhouse gas emissions, water consumption, and fossil-fuel use of plastic resin production and their post-use phase impacts

Resin production and post-use pathways have cross-database discrepancies due to different temporal/geographic representation, technologies, and assumptions. These differences can distort comparisons across alternatives and confound efforts to establish standards based on the plastics’ life-cycle impacts. Thus, this study quantifies the degree and identifies the sources of cross-database discrepancies across four LCA databases (GREET, USLCI, Ecoinvent, and GaBi) for five resin production pathways and three post-use phases. For resin production pathways, all resins showed significant cross-database discrepancy in their global warming impacts: the degree of discrepancy was significant to recommend a consistent choice of database to users any LCA comparisons across different products. For post-use phases, landfill datasets had relatively lower degree of cross-database discrepancy than incineration and mechanical recycling. Different metadata characteristics were the sources of some cross-database discrepancies while other parts could be explained by the original differences in the life-cycle inventory sourced from different producers and plants.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2015

SmallSat Database

The SmallSat has an unrealized potential in both the private industry and in the federal government. Currently over 70 companies, 50 universities and 17 governmental agencies are involved in SmallSat research and development. In 1994, the U.S. Army Missile and Defense mapped the moon using smallSat imagery. Since then Smart Phones have introduced this imagery to the people of the world as diverse industries watched this trend. The deployment cost of smallSats is also greatly reduced compared to traditional satellites due to the fact that multiple units can be deployed in a single mission. Imaging payloads have become more sophisticated, smaller and lighter. In addition, the growth of small technology obtained from private industries has led to the more widespread use of smallSats. This includes greater revisit rates in imagery, significantly lower costs, the ability to update technology more frequently and the ability to decrease vulnerability of enemy attacks. The popularity of smallSats show a changing mentality in this fast paced world of tomorrow. What impact has this created on the NASA communication networks now and in future years? In this project, we are developing the SmallSat Relational Database which can support a simulation of smallSats within the NASA SCaN Compatability Environment for Networks and Integrated Communications (SCENIC) Modeling and Simulation Lab. The NASA Space Communications and Networks (SCaN) Program can use this modeling to project required network support needs in the next 10 to 15 years. The SmallSat Rational Database could model smallSats just as the other SCaN databases model the more traditional larger satellites, with a few exceptions. One being that the smallSat Database is designed to be built-to-order. The SmallSat database holds various hardware configurations that can be used to model a smallSat. It will require significant effort to develop as the research material can only be populated by hand to obtain the unique data required. When completed it will interface with the SCENIC environment to allow modeling of smallSats. The SmallSat Relational Database can also be integrated with the SCENIC Simulation modeling system that is currently in development. The SmallSat Relational Database simulation will be of great significance in assisting the NASA SCaN group to understand the impact the smallSats have made which have populated the lower orbit around our mother earth. What I have created and worked on this summer session 2015, is the basis for a tool that will be of value to the NASA SCaN SCENIC Simulation Environment for years to come.

Small Satellites↗

DOE OSTI2026

SoK: What does it Mean to Benchmark Database Forensics?

Relational Database Management Systems are the backbone of modern enterprises and public-sector services, and are thus frequent targets of security incidents, insider threats, and thorough regulatory audits. Consequently, databases have become key sources of digital evidence, requiring investigators to reconstruct past activity from audit logs, transaction logs, and backups. Although benchmarking frameworks such as those developed by the Transaction Processing Performance Council (TPC) are widely used to evaluate database performance, they do not capture forensic requirements such as evidentiary completeness, tamper-evidence, chain of custody, or regulatory compliance under GDPR and CCPA. This survey examines the emerging domain of forensic database benchmarking. We gathered prior research on database forensics, secure logging, and tamper-evident data structures; we analyze modern forensic-ready features in commercial and open-source systems (SQL Server Ledger, Oracle Blockchain Tables, PostgreSQL pgAudit, Db2 Audit, Aurora Database Activity Streams, Oracle Real Application Security and IBM Guardium) and assess why existing benchmarks are insufficient. We propose forensic workloads, metrics, and methodologies that incorporate adversarial stressors, deleted-record recovery, and backup analysis. We also identify open research problems and call for a community-driven forensic benchmark suite. The result is an idea for evaluating not only database performance but also forensic soundness, bridging the gap between system engineering, compliance, and digital investigations.

Lenard, Ben↗

DOE OSTI2021

efam: an e xpanded, metaproteome-supported HMM profile database of viral protein fam ilies

Viruses infect, reprogram and kill microbes, leading to profound ecosystem consequences, from elemental cycling in oceans and soils to microbiome-modulated diseases in plants and animals. Although metagenomic datasets are increasingly available, identifying viruses in them is challenging due to poor representation and annotation of viral sequences in databases. Here, we establish efam, an expanded collection of Hidden Markov Model (HMM) profiles that represent viral protein families conservatively identified from the Global Ocean Virome 2.0 dataset. This resulted in 240 311 HMM profiles, each with at least 2 protein sequences, making efam >7-fold larger than the next largest, pan-ecosystem viral HMM profile database. Adjusting the criteria for viral contig confidence from ‘conservative’ to ‘eXtremely Conservative’ resulted in 37 841 HMM profiles in our efam-XC database. To assess the value of this resource, we integrated efam-XC into VirSorter viral discovery software to discover viruses from less-studied, ecologically distinct oxygen minimum zone (OMZ) marine habitats. This expanded database led to an increase in viruses recovered from every tested OMZ virome by ~24% on average (up to ~42%) and especially improved the recovery of often-missed shorter contigs (<5 kb). Additionally, to help elucidate lesser-known viral protein functions, we annotated the profiles using multiple databases from the DRAM pipeline and virion-associated metaproteomic data, which doubled the number of annotations obtainable by standard, single-database annotation approaches. Together, these marine resources (efam and efam-XC) are provided as searchable, compressed HMM databases that will be updated bi-annually to help maximize viral sequence discovery and study from any ecosystem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

The User Guide for the ComPro Database

An extensive database of glass composition and durability data has been compiled at Savannah River National Laboratory to support the development of nuclear waste glasses. This database is referred to as the Glass Composition-Properties Database (ComPro). The ComPro Database, Revision 3, contains 14,134 total rows of data and 125 columns of composition, durability, as defined by the Product Consistency Test, and other fabrication and characterization information, if available, for each glass. Of the 14,134 total rows, 8,484 rows have been classified as “Model” data and 5,650 rows have been classified as “Non-Model” data. An integral supplement to the ComPro database is the User Guide. The User Guide was developed as a tool to aid the End User in a more effective use of the ComPro database. The User Guide provides a road-map of the specific datasets that comprise the ComPro database (both “Model” and “Non-Model” data) as well as a technical basis for the terminology and definitions the End User will encounter. In this report, a general description of the format and information contained in the User Guide is provided. In addition, specific terminology used in the User Guide is also discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1994

Database tomography for commercial application

Database tomography is a method for extracting themes and their relationships from text. The algorithms, employed begin with word frequency and word proximity analysis and build upon these results. When the word 'database' is used, think of medical or police records, patents, journals, or papers, etc. (any text information that can be computer stored). Database tomography features a full text, user interactive technique enabling the user to identify areas of interest, establish relationships, and map trends for a deeper understanding of an area of interest. Database tomography concepts and applications have been reported in journals and presented at conferences. One important feature of the database tomography algorithm is that it can be used on a database of any size, and will facilitate the users ability to understand the volume of content therein. While employing the process to identify research opportunities it became obvious that this promising technology has potential applications for business, science, engineering, law, and academe. Examples include evaluating marketing trends, strategies, relationships and associations. Also, the database tomography process would be a powerful component in the area of competitive intelligence, national security intelligence and patent analysis. User interests and involvement cannot be overemphasized.

Kostoff, Ronald N.↗

NASA NTRS1993

VIEWCACHE: An incremental pointer-based access method for autonomous interoperable databases

One of the biggest problems facing NASA today is to provide scientists efficient access to a large number of distributed databases. Our pointer-based incremental data base access method, VIEWCACHE, provides such an interface for accessing distributed datasets and directories. VIEWCACHE allows database browsing and search performing inter-database cross-referencing with no actual data movement between database sites. This organization and processing is especially suitable for managing Astrophysics databases which are physically distributed all over the world. Once the search is complete, the set of collected pointers pointing to the desired data are cached. VIEWCACHE includes spatial access methods for accessing image datasets, which provide much easier query formulation by referring directly to the image and very efficient search for objects contained within a two-dimensional window. We will develop and optimize a VIEWCACHE External Gateway Access to database management systems to facilitate database search.

Roussopoulos, N.↗

NASA NTRS2003

ResPlan Database

The main project I was involved in was new application development for the existing CIS0 Database (ResPlan). This database application was developed in Microsoft Access. Initial meetings with Greg Follen, Linda McMillen, Griselle LaFontaine and others identified a few key weaknesses with the existing database. The weaknesses centered around that while the database correctly modeled the structure of Programs, Projects and Tasks, once the data was entered, the database did not capture any dynamic status information, and as such was of limited usefulness. After the initial meetings my goals were identified as follows: Enhance the ResPlan Database to include qualitative and quantitative status information about the Programs, Projects and Tasks Train staff members about the ResPlan database from both the user perspective and the developer perspective Give consideration to a Web Interface for reporting. Initially, the thought was that there would not be adequate time to actually develop the Web Interface, Greg wanted it understood that this was an eventual goal and as such should be a consideration throughout the development process.

Zellers, Michael L.↗

NASA NTRS2004

JDD, Inc. Database

JDD Inc, is a maintenance and custodial contracting company whose mission is to provide their clients in the private and government sectors "quality construction, construction management and cleaning services in the most efficient and cost effective manners, (JDD, Inc. Mission Statement)." This company provides facilities support for Fort Riley in Fo,rt Riley, Kansas and the NASA John H. Glenn Research Center at Lewis Field here in Cleveland, Ohio. JDD, Inc. is owned and operated by James Vaughn, who started as painter at NASA Glenn and has been working here for the past seventeen years. This summer I worked under Devan Anderson, who is the safety manager for JDD Inc. in the Logistics and Technical Information Division at Glenn Research Center The LTID provides all transportation, secretarial, security needs and contract management of these various services for the center. As a safety manager, my mentor provides Occupational Health and Safety Occupation (OSHA) compliance to all JDD, Inc. employees and handles all other issues (Environmental Protection Agency issues, workers compensation, safety and health training) involving to job safety. My summer assignment was not as considered "groundbreaking research" like many other summer interns have done in the past, but it is just as important and beneficial to JDD, Inc. I initially created a database using a Microsoft Excel program to classify and categorize data pertaining to numerous safety training certification courses instructed by our safety manager during the course of the fiscal year. This early portion of the database consisted of only data (training field index, employees who were present at these training courses and who was absent) from the training certification courses. Once I completed this phase of the database, I decided to expand the database and add as many dimensions to it as possible. Throughout the last seven weeks, I have been compiling more data from day to day operations and been adding the information to the database. It now consists of seven different categories of data (carpet cleaning, forms, NASA Event Schedules, training certifications, wall and vent cleaning, work schedules, and miscellaneous) . I also did some field inspecting with the supervisors around the site and was present at all of the training certification courses that have been scheduled since June 2004. My future outlook for the JDD, Inc. database is to have all of company s information from future contract proposals, weekly inventory, to employee timesheets all in this same database.

Miller, David A., Jr.↗