NASA Open Data Public Data List. This machine readable file contains meta-records for NASA open data sets.

🇺🇸 미국 English NASA Open Data Public Data List. This machine readable file contains meta-records for NASA open data sets.

The NTRS is a valuable resource for researchers, students, educators, and the public to access NASA's current and historical technical literature and engineering results. Over 500,000 aerospace-related citations, over 200,000 full-text online documents, and over 500,000 images and videos are available. NTRS content continues to grow as new scientific and technical information (STI) is created or funded by NASA. The types of information found in the NTRS include: conference papers, journal articles, meeting papers, patents, research reports, images, movies, and technical videos. NTRS is Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) enabled

The Public Use Microdata Samples (PUMS) are computer-accessible files containing records for a sample of housing Units, with information on the characteristics of each housing Unit and the people in it for 1940-1990. Within the limits of sample size and geographical detail, these files allow users to prepare virtually any tabulations they require. Each datafile is documented in a codebook containing a data dictionary and supporting appendix information. Electronic versions for the codebooks are only available for the 1980 and 1990 datafiles. Identifying information has been removed to protect the confidentiality of the respondents. PUMS is produced by the United States Census Bureau (USCB) and is distributed by USCB, Inter-university Consortium for Political and Social Research (ICPSR), and Columbia University Center for International Earth Science Information Network (CIESIN).

GRIN is a collection of over a thousand images of significant historical interest scanned at high-resolution in several sizes. This collection is intended for the media, publishers, and the general public looking for high-quality photographs.

NASA's goal in Earth science is to observe, understand, and model the Earth system to discover how it is changing, to better predict change, and to understand the consequences for life on Earth. The Applied Sciences Program, within the Earth Science Division of the NASA Science Mission Directorate, serves individuals and organizations around the globe by expanding and accelerating societal and economic benefits derived from Earth science, information, and technology research and development.

The Prediction Of Worldwide Energy Resources (POWER) Project, funded through the Applied Sciences Program at NASA Langley Research Center, gathers NASA Earth observation data and parameters related to the fields of surface solar irradiance and meteorology to serve the public in several free, easy-to-access and easy-to-use methods. POWER helps communities become resilient amid observed climate variability by improving data accessibility, aiding research in energy development, building energy efficiency, and supporting agriculture projects.

The POWER project contains over 380 satellite-derived meteorology and solar energy Analysis Ready Data (ARD) at four temporal levels: hourly, daily, monthly, and climatology. The POWER data archive provides data at the native resolution of the source products. The data is updated nightly to maintain near real time availability (2-3 days for meteorological parameters and 5-7 days for solar). The POWER services catalog consists of a series of RESTful Application Programming Interfaces, geospatial enabled image services, and web mapping Data Access Viewer. These three service offerings support data discovery, access, and distribution to the project’s user base as ARD and as direct application inputs to decision support tools.

The latest data version update includes hourly-based source ARD, in addition to enhanced daily, monthly, annual, and climatology data. The daily time series for meteorology is available from 1981, while solar-based parameters start in 1984. The hourly source data are from Clouds and the Earth's Radiant Energy System (CERES) and Global Modeling and Assimilation Office (GMAO), spanning from 1984 for meteorology and from 2001 for solar-based parameters. The hourly data equips users with the ARD needed to model building system energy performance, providing information directly amenable to decision support tools introducing the industry standard EnergyPlus Weather file format.

Overview

This dataset encompasses over 500 user comments collected from high-performing posts on NASA's Facebook page dedicated to climate change (https://web.facebook.com/NASAClimateChange/). The comments, gathered from various posts between 2020 and 2023, offer a diverse range of public opinions and sentiments about climate change and NASA's related activities.

Data Science Applications

Despite not being a large dataset, it offers valuable opportunities for analysis and Natural Language Processing (NLP). Potential applications include:

• Sentiment Analysis: Gauge public opinion on climate change and NASA's communication strategies.
• Trend Analysis: Identify shifts in public sentiment over the specified period.
• Engagement Analysis: Understand the correlation between the content of a post and user engagement.
• Topic Modeling: Discover prevalent themes in public discourse about climate change.

Column Descriptors

1. Date: The date and time when the comment was posted.
2. LikesCount: The number of likes each comment received.
3. ProfileName: The anonymized name of the user who posted the comment.
4. CommentsCount: The number of responses each comment received.
5. Text: The actual text content of the comment.

Ethical Considerations and Data Privacy

All profile names in this dataset have been hashed using SHA-256 to ensure privacy while maintaining data usability. This approach aligns with ethical data mining practices, ensuring that individual privacy is respected without compromising the dataset's analytical value.

Acknowledgements

We extend our gratitude to NASA and their Facebook platform for facilitating open discussions on climate change. Their commitment to fostering public engagement and awareness on this critical global issue is deeply appreciated.

Note to Data Scientists

As data scientists analyzing this dataset, it is crucial to approach the data impartially. Climate change is a subject with diverse viewpoints, and it is important to handle the data and any derived insights in a manner that respects these different perspectives.

Image Credits

The dataset's thumbnail was generated by Dall-E 3.

The NASA Lessons Learned system provides access to official, reviewed lessons learned from NASA programs and projects. These lessons have been made available to the public by the NASA Office of the Chief Engineer and the NASA Engineering Network. Each lesson describes the original driving event and provides recommendations that feed into NASA’s continual improvement via training, best practices, policies, and procedures.

Metadata relating to the FAO / NASA Harvest Public Cropland Maps dataset.

DescriptionPrognostics and health management is an important topic in industry for predicting state of assets to avoid downtime and failures. This data set is the Kaggle version of the very well known public data set for asset degradation modeling from NASA. It includes Run-to-Failure simulated data from turbo fan jet engines.

NASA's Physical Sciences Research Program, along with its predecessors, has conducted significant fundamental and applied research in the physical sciences. The International Space Station (ISS) is an orbiting laboratory that provides an ideal facility to conduct long-duration experiments in the near absence of gravity and allows continuous and interactive research similar to Earth-based laboratories. This enables scientists to pursue innovations and discoveries not currently achievable by other means. NASA's Physical Sciences Research Program also benefits from collaborations with several of the ISS international partners—Europe, Russia, Japan, and Canada—and foreign governments with space programs, such as France, Germany and Italy.

In fulfillment of the Open Science model, NASA's Physical Sciences Research Program is pleased to offer the PSI data repository for physical science experiments performed in reduced-gravity environments such as the ISS, Space Shuttle flights, and Free-flyers. PSI also includes data from some related ground-based studies. The PSI system is accessible and open to the public. This provides the opportunity for researchers to data mine results from prior flight investigations, expanding on the research performed. This approach will allow numerous ground-based investigations to be conducted from one flight experiment’s data, exponentially increasing our body of knowledge. PSI is an Open Data initiative.

This database table is a catalog of all the RXTE slew observations and is based on information culled from the RXTE Data Archive's latest top-level FMI (FITS Master Index) file that is created when data products are made publicly available each week. ObsIDs listed in this table are available for download from https://heasarc.gsfc.nasa.gov/FTP/xte/data/archive/. See the parameter 'data_loc' for the relative location of specific ObsIDs. The XTESLEW database table is updated automatically, usually on a weekly basis whenever the RXTE GOF updates the top-level FMI for the public data archive and notifies the HEASARC. This is a service provided by NASA HEASARC .

Public data set for NASA Agency Intellectual Property (IP). The distribution contains both Patent information as well as General Release of Open Source Software.

The purpose of the Aerospace Technical Facility Inventory is to facilitate the sharing of specialized capabilities within the aerospace research/engineering community primarily within NASA, but also throughout the nation and the entire world. A second use is to assist in answering questions regarding NASA capabilities for future missions or various alternative scenarios regarding mission support to help the Agency maintain the right set of assets.

The INTEGRAL Public Data Results Catalog is based on publicly available data from the two main instruments (IBIS and SPI) on board INTEGRAL (see Winkler et al. 2003, A&A, 411, L1 for a description of the INTEGRAL spacecraft and instrument packages). INTEGRAL began collecting data in October 2002. This catalog will be regularly updated as data become public (~14 months after they are obtained). This catalog is a collaborative effort between the INTEGRAL Science Data Center (ISDC) in Switzerland and the NASA Goddard Space Flight Center (GSFC) INTEGRAL Guest Observer Facility (GOF). The results presented here are a result of a semi-automated analysis and they should be considered as approximate: they are intended to serve as a guideline to those interested in pursuing more detailed follow-up analyses. The data from the imager ISGRI (Lebrun et al. 2003, A&A, 411, L141) have been analyzed at the INTEGRAL Science Data Centre (ISDC), while the SPI (Vedrenne et al. 2003, A&A, 411, L63) data analysis was performed at GSFC as a service of the INTEGRAL GOF. Note: For cases where two or more proposals have been amalgamated (entries with pi_lname = 'Amalgamated') for a given observation, the same observation is listed for each of the amalgamated proposal numbers. This database table was first created in September 2004. It is based on the online web page maintained by the INTEGRAL GOF at the URL http://heasarc.gsfc.nasa.gov/docs/integral/obslist.html and was updated on a weekly basis whenever that web page was updated. Automatic updates were discontinued in June 2019. Duplicate entries were removed in June 2019, also. This is a service provided by NASA HEASARC .

Meteorite Landings DatasetThe Meteoritical Society collects data on meteorites landings. This dataset, taken from public available NASA datasets, includes the location, mass, composition, and fall year for over 45,000 meteorites that have struck our planet.Dataset Variables:name: name given to meteoriteid: unique identifier given to meteoritenametype: Valid (typical meteorite) or Relict (meteorite that has been highly degraded by weather on Earth)recclass: classification given to meteoritemass (g): mass of meteorite, in gramsfall: Fall (meteorite's fall was observed) or Found (meteorite's fall was not observed)year: the year the meteorite fell or year it was foundreclat: latitude of meteorite's landingreclong: longitude of the meteorite's landingGeoLocation: a parentheses-enclose, comma-separated tuple that combines reclat and reclong

This dataset contains raw messages received from the Time Based Flow Management (TBFM) System Wide Information System (SWIM) public data feed. This feed requires each consumer develop their own source code to store the data. TBFM is one of the large decision support tools used by the Federal Aviation Administration to meter the rate of traffic into airports and over busy airspace resources.

This data set has been collected from a custom built battery prognostics testbed at the NASA Ames Prognostics Center of Excellence (PCoE). Li-ion batteries were run through 3 different operational profiles (charge, discharge and Electrochemical Impedance Spectroscopy) at different temperatures. Discharges were carried out at different current load levels until the battery voltage fell to preset voltage thresholds. Some of these thresholds were lower than that recommended by the OEM (2.7 V) in order to induce deep discharge aging effects. Repeated charge and discharge cycles result in accelerated aging of the batteries. The experiments were stopped when the batteries reached the end-of-life (EOL) criteria of 30% fade in rated capacity (from 2 Ah to 1.4 Ah). Data Acquisition: The testbed comprises: * Commercially available Li-ion 18650 sized rechargeable batteries, * Programmable 4-channel DC electronic load, * Programmable 4-channel DC power supply, * Voltmeter, ammeter and thermocouple sensor suite, * Custom EIS equipment, * Environmental chamber to impose various operational conditions, * PXI chassis based DAQ and experiment control, and MATLAB based experiment control, data acquisition and prognostics algorithm evaluation setup (appx. data acquisition rate is 10Hz). Parameter Description: Data Structure: cycle: top level structure array containing the charge, discharge and impedance operations type: operation type, can be charge, discharge or impedance ambient_temperature: ambient temperature (degree C) time: the date and time of the start of the cycle, in MATLAB date vector format data: data structure containing the measurements for charge the fields are: Voltage_measured: Battery terminal voltage (Volts) Current_measured: Battery output current (Amps) Temperature_measured: Battery temperature (degree C) Current_charge: Current measured at charger (Amps) Voltage_charge: Voltage measured at charger (Volts) Time: Time vector for the cycle (secs) for discharge the fields are: Voltage_measured: Battery terminal voltage (Volts) Current_measured: Battery output current (Amps) Temperature_measured: Battery temperature (degree C) Current_charge: Current measured at load (Amps) Voltage_charge: Voltage measured at load (Volts) Time: Time vector for the cycle (secs) Capacity: Battery capacity (Ahr) for discharge till 2.7V for impedance the fields are: Sense_current: Current in sense branch (Amps) Battery_current: Current in battery branch (Amps) Current_ratio: Ratio of the above currents Battery_impedance: Battery impedance (Ohms) computed from raw data Rectified_impedance: Calibrated and smoothed battery impedance (Ohms) Re: Estimated electrolyte resistance (Ohms) Rct: Estimated charge transfer resistance (Ohms) Intended Use: The data sets can serve for a variety of purposes. Because these are essentially a large number of Run-to-Failure time series, the data can be set for development of prognostic algorithms. In particular, due to the differences in depth-of-discharge (DOD), the duration of rest periods and intrinsic variability, no two cells have the same state-of-life (SOL) at the same cycle index. The aim is to be able to manage this uncertainty, which is representative of actual usage, and make reliable predictions of Remaining Useful Life (RUL) in both the End-of-Discharge (EOD) and End-of-Life (EOL) contexts.

This file contains the public MISR Level 3 FIRSTLOOK Global Cloud public Product in netCDF format covering a day

The NASA Exoplanet Archive is an online astronomical exoplanet and stellar catalog and data service that collates and cross-correlates astronomical data and information on exoplanets and their host stars, and provides tools to work with these data. The archive is dedicated to collecting and serving important public data sets involved in the search for and characterization of extrasolar planets and their host stars. These data include stellar parameters (such as positions, magnitudes, and temperatures), exoplanet parameters (such as masses and orbital parameters) and discovery/characterization data (such as published radial velocity curves, photometric light curves, images, and spectra).