Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “open data format”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Coastal On-line Assessment and Synthesis Tool 2.0

COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest.

Brown, Richard↗
NASA NTRS2013

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four‐dimensional numerical model simulations is propelling the wider adoption of ultra‐resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well‐integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display‐to‐dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data‐intensive information. This information can be digital‐cinema animations, high‐resolution images, high‐definition video‐teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross‐platform, community‐driven, open‐source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.

Jedlovec, Gary↗
DOE OSTI2025

CoCoMET v1.0: a unified open-source toolkit for atmospheric object tracking and analysis

Advances in performance and analysis capabilities have accelerated the development of object tracking algorithms for atmospheric research. This has resulted in a growing number of studies using Lagrangian tracking techniques to analyze the evolution of atmospheric phenomena and the underlying processes. However, the increasing complexity and variety of tracking algorithms present a steep learning curve for new users and make it difficult for existing users to compare algorithm performance. We introduce CoCoMET (Community Cloud Model Evaluation Toolkit), an open-source toolkit that addresses these issues. CoCoMET simplifies the process of running multiple tracking algorithms simultaneously and analyzing objects in both model and observational datasets by specifying parameters in a single configuration file. It standardizes input data from different sources into a consistent format and unifies the tracking output across algorithms. CoCoMET enhances the functionality of existing tracking methods by calculating additional properties such as cell growth and dissipation rates, perimeter, surface area, convexity, and irregularity. In addition, CoCoMET includes a novel method for identifying mergers and splits in 2D and 3D tracks and supports the integration of Eulerian/stationary datasets external to the tracking data for process studies. Its potential utility is demonstrated through examples of model intercomparison, model evaluation against observations, and comparisons between tracking algorithms. Designed for open-source environments, CoCoMET will continue to expand with future releases, incorporating more input data types and tracking algorithms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Catalytic hydrogenation of HMF to BHMF over copper catalysts

2,5-Bis(hydroxymethyl)furan (BHMF) is a bio-derived building block for polyester production, obtained via the hydrogenation of 5-hydroxymethylfurfural (HMF). First-principles thermodynamic equilibrium calculations indicate that this reaction is not thermodynamically limited under relevant conditions (e.g., 100 °C and high H 2 partial pressure). In this work, crude HMF was employed as the feedstock for BHMF synthesis. Initially, acidic impurities and humins were removed from unrefined HMF through filtration using a packed bed of γ-alumina. A comprehensive study of the filtration process is presented, including filtration kinetics, breakthrough curve analysis, and mathematical modeling. The purified HMF was subsequently hydrogenated over a 10 wt% CuZrO 2 catalyst, using ethanol as the reaction solvent. Batch reactions were first performed for collection of kinetic data to guide the transition to continuous flow operation. Kinetic data was collected in a fixed bed reactor at varying contact time, time on stream, temperature, and HMF concentration. This data was used to develop a kinetic model for HMF hydrogenation. Maximum BHMF production rates were achieved at 130 °C, accompanied by minor formation of byproducts from BHMF ring-opening reactions. The BHMF selectivity was 100 % at 100 °C although with lower reaction rates. Furthermore, catalyst stability tests revealed a loss of up to 50 % in catalytic activity within the first 24 h, likely due to the adsorption of HMF-derived oligomers that are not easily removed by filtration.

Crude HMF filtration↗
DOE OSTI2021

Data from: "Colonisation of the alpine tundra by trees: alpine neighbours assist late-seral but not early-seral conifer seedlings"

This archive contains data used to support conclusions made in “Colonisation of the alpine tundra by trees: alpine neighbours assist late-seral but not early-seral conifer seedlings”, by Jabis et al., 2020. Data were collected in the alpine field location of the Alpine Treeline Warming Experiment (ATWE), on Niwot Ridge, in the Front Range of the Colorado Rocky Mountains, USA.This package includes survivorship and physiology data for limber pine (Pinus flexilis), Engelmann spruce (Picea engelmannii), and Rocky Mountain snowlover (Chionophila jamesii). Site climate data such as soil moisture and temperature are also included. This data package contains ten comma-separated-values (.csv) files, and two rich-text-format (.rtf) files all compressed within one folder named “Neighbor_data_repository.zip”. Both file types can be opened by text-edit softwares such as TextEdit (Mac) and Notepad (Windows). The files are also compatible with analyses softwares such as R. .csv files can also be opened by Microsoft Excel. Two geospatial datasets are also included in this archive: one keyhole markup language (.kml) file with four points marking the corners of the study site, and a compressed file containing two ESRI shapefiles (.shp). The .kml files can be opened with Google Earth or Google Maps, and the shapefiles can be opened using any geographic information system applications, including the entire ArcGIS suite, and QGIS. -------------------------------------------------------------------------------------------------------------------------------------------------------The elevation mountain treeline is expected to shift upward with climate warming, and seed germination and seedling survival are critical local controls on treeline expansion. Neighboring alpine plants, either through competition for resources or through altering the microclimate, can also affect seedling emergence and survival. We asked whether establishing tree seedlings and an alpine herb are similarly sensitive to alpine plant neighbours under ambient and altered climate. We imposed active heating, watering, and neighbor removal experiments for emerging conifer seedlings and an alpine herb.We compared target plant survival, photosynthetic efficiency, and water use efficiency under ambient and experimental conditions. Picea engelmannii seedlings showed lower survival compared with Pinus flexilis three weeks following neighbour removal, and after 1 year only survived in watered plots. Pinus seedlings responded to neighbour removal by lowering the quantum yield of photosynthesis (ϕPSII). Contrary to expectations from the stress gradient hypothesis, survival was reduced without neighbours near the low-elevation range limit of Chionophila jamesii.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1988

An operational open-end file transfer protocol for mobile satellite communications

This paper describes an operational open-end file transfer protocol which includes the connecting procedure, data transfer, and relinquishment procedure for mobile satellite communications. The protocol makes use of the frame level and packet level formats of the X.25 standard for the data link layer and network layer, respectively. The structure of a testbed for experimental simulation of this protocol over a mobile fading channel is also introduced.

Wang, Charles↗
DOE OSTI2021

ESS-DIVE Reporting Format for File-level Metadata

The ESS-DIVE reporting format for file-level metadata (FLMD) provides granular information at the data file level to describe the contents, scope, and structure of the data file to enable comparison of data files within a data package. The FLMD are fully consistent with and augment the metadata collected at the data package level. We developed the FLMD template based on a review of a small number of existing FLMD in use at other agencies and repositories with valuable input from the Environmental Systems Science (ESS) Community. Also included is a template for a CSV Data Dictionary where users can provide file-level information about the contents of a CSV data file (e.g., define column names, provide units). Files are in .csv, .xlsx, and .md. Templates are in both .csv and .xlsx (open with e.g. Microsoft Excel, LibreOffice, or Google Sheets). Open the .md files by downloading and using a text editor (e.g. Notepad or TextEdit). Though we provide Excel templates for the file-level metadata reporting format, our instructions encourage users to 'Save the FLMD template as a CSV following the CSV Reporting Format guidance'. In addition, we developed the ESS-DIVE File Level Metadata Extractor which is a lightweight python script that can extract some FLMD fields following the recommended FLMD format and structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 2 Sensor Data v2-1

This is the version v2-1 Level 2 (L2) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. Level 2 (L2) data consist of sensor observations from the COMPASS-FME synoptic sites, TEMPEST, and DELUGE. Compared to the L1 data, these are more consistent (always 15-minute timestamps for the entire year); better QA/QC’d (out of bounds, out of service, and extreme outlier values are removed); and more complete, with a gap-filled time series available alongside the main observations, and additional derived (calculated) variables. L2 data are intended to be rapidly and easily usable in analyses and simulations. However, algorithmic outlier identification always carries the risk of removing valid data, and Level 1 data may be more suitable for analyses that focus on variability or extreme events. This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific Parquet (a high performance, space efficient format; see https://parquet.apache.org) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are reported every 15 minutes. Please see v2-1 TEMPEST L2 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. Data files are in Apache Parquet, a high performance, space efficient format for tabular data. These files can be read using R's `arrow` package (https://arrow.apache.org/docs/r/), with similar tools available in other languages. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
DOE OSTI2025

2025 TEM Workshop

The TEM Data Management Workshop will take place on August 26 from 9 a.m. to 12 p.m. MT, and will be held virtually on TEAMS. The primary goal of this workshop is to engage NSUF users and stakeholders in discussions about the data needs for the utilization of AI and ML in the analysis of TEM data. Key topics to be covered include data storage, data sharing, data tagging, metadata inclusion, standardized data formats, data augmentation, and annotated training datasets. Additionally, the workshop will provide valuable insights into resources such as the Nuclear Research Data System (NRDS) for data storage and sharing, as well as open-source codes for data analysis.

Bachhav, Mukesh↗
NASA NTRS2009

MAGIC: Model and Graphic Information Converter

MAGIC is a software tool capable of converting highly detailed 3D models from an open, standard format, VRML 2.0/97, into the proprietary DTS file format used by the Torque Game Engine from GarageGames. MAGIC is used to convert 3D simulations from authoritative sources into the data needed to run the simulations in NASA's Distributed Observer Network. The Distributed Observer Network (DON) is a simulation presentation tool built by NASA to facilitate the simulation sharing requirements of the Data Presentation and Visualization effort within the Constellation Program. DON is built on top of the Torque Game Engine (TGE) and has chosen TGE's Dynamix Three Space (DTS) file format to represent 3D objects within simulations.

Herbert, W. C.↗
DOE OSTI2025

A DECADE of dwarfs: first detection of weak lensing around spectroscopically confirmed low-mass galaxies

We present the first detection of weak gravitational lensing around spectroscopically confirmed dwarf galaxies, using the large overlap between DESI DR1 spectroscopic data and DECADE/DES weak lensing catalogs. A clean dwarf galaxy sample with well-defined redshift and stellar mass cuts enables excess surface mass density measurements in two stellar mass bins ($\log \rm{M}_*=[8.2, 9.2]~M_\odot$ and $\log \rm{M}_*=[9.2, 10.2]~M_\odot$), with signal-to-noise ratios of $5.6$ and $12.4$ respectively. This signal-to-noise drops to $4.5$ and $9.2$ respectively for measurements without applying individual inverse probability (IIP) weights, which mitigates fiber incompleteness from DESI's targeting. The measurements are robust against variations in stellar mass estimates, photometric shredding, and lensing calibration systematics. Using a simulation-based modeling framework with stellar mass function priors, we constrain the stellar mass-halo mass relation and find a satellite fraction of $\simeq 0.3$, which is higher than previous photometric studies but $1.5σ$ lower than $Λ$CDM predictions. We find that IIP weights have a significant impact on lensing measurements and can change the inferred $f_{\rm{sat}}$ by a factor of two, highlighting the need for accurate fiber incompleteness corrections for dwarf galaxy samples. Our results open a new observational window into the galaxy-halo connection at low masses, showing that future massively multiplexed spectroscopic observations and weak lensing data will enable stringent tests of galaxy formation models and $Λ$CDM predictions.

To, Chun-Hao [Chicago U., Astron. Astrophys. Ctr.;↗
DOE OSTI2023

A novel approach for adaptive skeleton toolpath generation

Industry 4.0 is revolutionizing manufacturing through the integration of automation and real-time data sharing in cyber-physical systems. At the forefront of this revolution is large-format additive manufacturing. In large-format printing, parts are often designed to be an even number of beads wide to produce a completely dense part. However, voids can still arise. This is often due to the part not being an even number of bead widths wide in some areas, or in geometry containing acute angles, as the process of generating closed contours cannot completely fill the space. Voids can be tolerated in smaller models, but in large-format additive manufacturing they may cause mechanical defects. To fill these voids, open loop paths called skeletons are often used, but they are typically limited by the physical constraints defined in the slicing software. To address this, researchers at Oak Ridge National Laboratory have extended skeleton toolpaths via an adaptive methodology. These adaptive skeletons were found to better fill void spaces through manipulation of physical parameters of the build process and were calculated as part of the slicing process.

42 ENGINEERING↗
DOE OSTI2023

Utah FORGE: Powder X-ray Diffraction Data from Well 16A(78)-32 Core

This dataset from Lawrence Livermore National Laboratory (LLNL) consists of four raw X-ray diffraction (XRD) scans and preliminary results of quantitative XRD analysis. The scanned samples were prepared from four subcores, which came from various depths of the FORGE well 16A(78)-32 core. Desired core lengths were selected from available core photos (on GDR), provided by FORGE personnel, and subcored at LLNL. The XRD scans were collected in May 2023 at LLNL as pre-experimental characterization data for these subcores, which will be used in core-flooding experiments at LLNL and in triaxial direct shear experiments at Los Alamos National Laboratory as part of DOE Project 5-2428. XRD scans are in RAW file format (e.g., FORGE-5477-full.raw) and are suitable for viewing and analysis using open-source quantitative XRD software (e.g., Profex; www.profex-xrd.org ) and/or other proprietary instrument software.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Model Data for the Mesh Convergence Study Demonstrating Benefits of Mixed-polyhedral Mesh in Integrated Hydrology Simulations

This archived model data is related to a study introducing a unique method that employs a stream-aligned mixed-polyhedral mesh to effectively and accurately represent river valleys, stream corridors, and narrow engineered channels in integrated hydrology simulations. The study finds that utilizing stream-aligned mixed-polyhedral meshes in integrated hydrology simulations achieves accuracy on par with a finely refined TIN-based mesh while markedly diminishing computational costs. This archive contains scripts and data files needed to generate the ATS model input, including mesh and ATS input files, for all mesh scenarios using the Watershed Workflow package. Additionally, this archive also provides key outputs from the model simulations that are used in the analysis and post-processing scripts to reproduce figures in the manuscript. The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling the Effects of Artificial Drainage on Agriculture-dominated Watersheds using a Fully Distributed Integrated Hydrology Model: Datasets, scripts, model files

This model-data archive supports the research paper that demonstrates the integration of agricultural drainage features—specifically, narrow engineered ditches and tile drains—into a fully distributed, basin-scale integrated surface-subsurface hydrology model (ISSHM), Amanzi-ATS. The model employs innovative computational meshes aligned with agricultural ditches and incorporates the physically based Hooghoudt's drainage equation to simulate tile drainage, offering a novel strategy that enhances the accuracy of hydrological simulations.The archived dataset includes input parameters, model configurations, and select simulation outputs for the Amanzi-ATS model that successfully captured the streamflow patterns in the Portage River Watershed as validated by USGS gauge readings. Jupyter notebook for the preparation of model inputs and post-processing of outputs are also included. The model's predictive performance achieved a normalized Kling-Gupta Efficiency (KGE) of 0.81, surpassing SWAT without the necessity for site-specific calibration.The Amanzi-ATS model presented in this modeL-data archive allows for numerical experiments to explore the shifts in the flow structure under different drainage scenarios. As a tool for advancing the understanding of distributed hydrological responses and nutrient cycling, this archived model provides valuable insights for researchers, modelers, and decision-makers involved in watershed management and environmental modeling.The Watershed Workflow package is implemented in Python3. The Jupyter notebooks can be executed through multiple open-source tools, for example, Anaconda Jupyter Lab, VS Studio Code, etc. Other data files include CSV and HDF5 files, which can be read through Python scripts. The input files for the ATS model, open-source integrated hydrology, and transport model, are in XML format and can be edited in any commonly used text editors.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Publications of the Jet Propulsion Laboratory, 1980

This bibliography cites by primary author the externally distributed technical reporting, released during calendar year 1980, that resulted from scientific and engineering work performed, or managed, by the Jet Propulsion Laboratory. Three classes of publications are included: (1) JPL Publications (77-, 78-, 79-series, etc.), in which the information is complete for a specific accomplishment and can e tailored to wide or limited audiences and be presented in an established standard format or special format to meet unique requirements; (2) articles published in the open literature; and (3) articles from the bimonthly Deep Space Network (DSN) Progress Repot (42-series) and its successor, the Telecommunications and Data Acquisition (TDA) Progress Report (also 42-series).

Source record↗
DOE OSTI2022

The Open Cluster Chemical Abundances and Mapping Survey. VII. APOGEE DR17 [C/N]–Age Calibration

Large-scale surveys open the possibility to investigate Galactic evolution both chemically and kinematically; however, reliable stellar ages remain a major challenge. Detailed chemical information provided by high-resolution spectroscopic surveys of the stars in clusters can be used as a means to calibrate recently developed chemical tools for age-dating field stars. Using data from the Open Cluster Abundances and Mapping survey, based on the Sloan Digital Sky Survey/Apache Point Observatory Galactic Evolution Experiment 2 survey, we derive a new empirical relationship between open cluster stellar ages and the carbon-to-nitrogen ([C/N]) abundance ratios for evolved stars, primarily those on the red giant branch. With this calibration, [C/N] can be used as a chemical clock for evolved field stars to investigate the formation and evolution of different parts of our Galaxy. We explore how mixing effects at different stellar evolutionary phases, like the red clump, affect the derived calibration. We have established the [C/N]–age calibration for APOGEE Data Release 17 (DR17) giant star abundances to be $\mathrm{log}{[\mathrm{Age}(\mathrm{yr})]}_{\mathrm{DR}17}=10.14\,(\pm 0.08)+2.23(\pm 0.19)\,[{\rm{C}}/{\rm{N}}]$, usable for $8.62\leqslant \mathrm{log}(\mathrm{Age}[\mathrm{yr}])\leqslant 9.82$, derived from a uniform sample of 49 clusters observed as part of APOGEE DR17 applicable primarily to metal-rich, thin- and thick-disk giant stars. This measured [C/N]–age APOGEE DR17 calibration is also shown to be consistent with asteroseismic ages derived from Kepler photometry.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Geospatial Data from the Alpine Treeline Warming Experiment (ATWE) on Niwot Ridge, Colorado, USA

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. –––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive.As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

54 ENVIRONMENTAL SCIENCES↗