EIA launched a new liquids pipeline projects database that tracks more than 200 pipeline projects for crude oil, hydrocarbon gas liquids (HGL), and other petroleum products. The database contains project information such as project type, start date, capacity, mileage, and geographic information for historical (completed since 2010) and future pipeline projects. The information in the database is based on the latest public information from company documents, government filings, and trade press, but it does not reflect any assumptions on the likelihood or timing of project completion. The liquids pipeline projects database complements EIA’s natural gas pipeline projects table.

The Oil and Gas Pipelines Database contains known spatial locations of onshore and offshore pipelines or pipeline corridors used to transport natural gas, oil and other liquids within Australia’s mainland and territorial waters.

This database contains data, as received, from GP INFO, Petrosys. Minimal effort was made to revise, value add and/or spatially improve the datasets.

AbstractThe Oil and Gas Pipelines Database contains known spatial locations of onshore and offshore pipelines or pipeline corridors used to transport natural gas, oil and other liquids within Australia’s mainland and territorial waters. Onshore pipelines are represented as polylines for Qld, NSW, Vic, Tas, and SA, and polygons/corridors for WA and NT. Offshore pipelines are represented as polylines for WA, NT and Vic. Pipeline data has been provided by Petrosys GPinfo as of 24 August 2022. More information available at www.gpinfo.com.au. No effort was made to revise, value add and/or spatially improve the datasets.For the purposes of this dataset a Pipeline is defined as: A linked series of pipes, with pumps and valves, used for the conveyance of gas, oil and liquids.For the purposes of this dataset a Corridor is defined as: A passage of land in which a pipeline and the facilities of a pipeline operator have the potential to transverse, including rights-of-way and easements over and through public or private propertyCurrencyDate modified: 12 December 2022Modification frequency: As neededThe next revision of this database will be determined by Geoscience Australia’s work program. This timeframe will range between 3 and 5 years; this is also dependent upon available resources and other priorities.Data extentSpatial extentNorth: -17.5°South: -38.5°East: 153.2°West: 113.8°Temporal extentFrom 1 January 1970 to PresentSource informationThe primary sources of information/data used to construct and validate entries within the Version 3 database were:Direct data download was captured on the 24 of August 2022 under the licencing agreement between Geoscience Australia (GA) and Petrosys GPinfoCatalog entry: Oil and Gas PipelinesLineage statementUsing pipeline datasets acquired from the States, Territories and NOPTA, the data was uploaded into an ArcSDE environment using Feature Manipulation Engine (FME). The process included the extraction of the themed (gas pipeline and oil pipeline) features, and the translation of the data into a schema created by, National Location Information Branch, Geoscience Australia (GA).Data download:Mar 2015:- Public release of GA's Onshore Gas Pipelines Database Version 1- Public release of GA's Onshore Oil Pipelines Database Version 1Mar 2017:- Public release of GA's Gas and Oil Pipelines Database Version 2Aug 2022:- Public release of GA’s Oil and Gas Pipelines Database – Version 3Web Service:Feb 2015:- Public release of GA’s Onshore Gas Pipelines web service – Version 1- Public release of GA’s Onshore Oil Pipelines web service – Version 1Feb 2016:- Public release of GA’s National Oil and Gas Infrastructure web service – Version 1Dec 2022:- Public release of GA’s Onshore Oil Pipelines web service – Version 3Data dictionaryAll layersAttribute nameDescriptionNAMEThe name of each individual featureDATE_DOWNLOADEDThe date when the data was downloaded as part of the licencing agreementFEATURE_TYPEA description of this feature’s type (Pipeline, Corridor)LENGTHTotal length of pipeline - kilometresLICENSEThe licence type in which data can be usedOPERATIONAL_STATUSThe operational status as define by GP INFOSOURCEThe source of the data of whom the licencing agreement is withSPATIAL_CONFIDENCEA confidence value (5 = high to 0 = low) of the feature’s spatial location as assigned by the spatial professionalSTATEState or Territory where pipeline segment is locatedContactGeoscience Australia, clientservices@ga.gov.au

The Advanced Infrastructure Integrity Modeling (AIIM) Onshore Pipeline Database is an interoperable spatial resource containing critical environmental, operational, and reported stressors tied to publicly available oil and gas pipeline locations across the contiguous U.S. and Alaska. This database contains two layers: 1. Pipeline point locations (‘pipeline_points’) – More than 500,000 points (at every kilometer along pipelines, and end points) to which more than 350 stress-related variables have been appended. 2. Merged pipelines (‘merged_pipelines’) – The original, publicly available pipeline data (see table below) merged together into one feature class.

This spreadsheet contains detailed information on liquids (crude oil, petroleum products, and hydrocarbon gas liquids) pipeline projects that have been completed (since 2010), announced, or canceled or are on hold or under construction. We do not collect the data on an EIA survey, but rather we compile the data from various sources including trade press, pipeline company websites, and government agencies. These data are not a forecast. They represent last-known public information on projects, as of December 17, 2021. The amount of capacity additions may be different from that reflected in accompanying data. Projects that are announced, but have no start date, capacity, or route information are not included. Projects that are under indefinite legal or regulatory holds are included, but without start dates. The file will be updated twice a year.

The Pipeline and Hazardous Materials Safety Administration (PHMSA) Pipeline Safety Regions dataset was compiled on October 04, 2022 from the Pipeline and Hazardous Materials Safety Administration (PHMSA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). PHMSA’s Office of Pipeline Safety (OPS) is responsible for protecting people and the environment from pipeline failures by analyzing pipeline safety and accident data; evaluating which safety standards need improvement and where new rulemakings are needed; setting and enforcing regulations and standards for the design, construction, operation, maintenance or abandonment of pipelines by pipeline companies; educating operators, states and communities on how to keep pipelines safe; facilitating research and development into better pipeline technologies; training state and federal pipeline inspectors; and administering grants to states and localities for pipeline inspections, damage prevention and emergency response. The PHMSA Pipeline Safety Regions layer contains polygon features representing each of the five regions, Central, Eastern, Southern, Southwest, and Western, that make up PHMSA’s Office of Pipeline Safety. Each region office is charged with ensuring the safe, reliable, and environmentally sound operation of the nation's pipeline infrastructure. Despite regional divisions the jurisdiction of PHMSA staff is nationwide and not limited to their regional area of responsibility. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1530287

A line file representing locations of the pipeline infrastructure in the Gulf of Mexico associated with the oil and gas industry is presented. These layers were modified from GIS data acquired from the U. S. Department of the Interior, Bureau of Ocean Energy Management (BOEM) website. We note that pipelines are being added or modified continuously, thus regular updates of this database are required to know the true distribution of pipelines. The current layers are non-projected with coordinates in decimal degrees.

Submarine Pipeline Locations in USACE Dataset

Locations and details of submarine pipelines for oil or gas transport

By Homeland Infrastructure Foundation [source]

About this dataset

The Submarine Pipeline Lines in the USACE IENC dataset provides comprehensive information about the locations and characteristics of submarine pipelines used for transporting oil or gas. These submarine or land pipelines are composed of interconnected pipes that are either laid on or buried beneath the seabed or land surfaces.

This dataset is a part of the Inland Electronic Navigational Charts (IENCs) and has been derived from reliable data sources utilized for maintaining navigation channels. It serves as a valuable resource for researchers, analysts, and policymakers interested in studying and monitoring the infrastructure related to oil and gas transportation.

For each submarine pipeline, this dataset includes various attributes such as its category type, product being transported (e.g., oil or gas), unique name or identifier, current status (active or decommissioned), additional information about its purpose or characteristics, minimum scale at which it can be visible on a map, length in meters, source of data used to create the dataset, and details regarding who provided the source data.

The Category_o column categorizes each pipeline based on its type, providing insights into different classifications within this infrastructure sector. Similarly,the Product column specifies whether it carries oil or gas through these pipelines.

Moreover,this dataset's Object_Nam field contains distinct names assigned to each submarine pipeline within the USACE IENC database. These names facilitate easy identification and reference when studying specific sections of this extensive network.

The Status attribute indicates whether a particular pipeline is currently active for transport purposes or has been decommissioned. This distinction holds significance for analyzing operational capacity and overall functionality.

Informatio presents additional details that further enhance our understanding of specific aspects related to these submarine pipelines such as their construction methods,purpose,functionality,and maintenance requirements.

Scale_Mini denotes the minimum scale at which each individual pipeline can be visualized accurately on a map,enabling users to effectively browse different levels of detail based on their requirements.

Finally,the Shape_Leng attribute provides the length of each submarine pipeline in meters, which is helpful for assessing distances, evaluating potential risks or vulnerabilities, and estimating transportation efficiency.

It is important to note that this dataset's information has been sourced from the USACE IENC dataset, ensuring its reliability and relevance to navigation channels. By leveraging this comprehensive collection of submarine pipeline data, stakeholders can gain valuable insights into the infrastructure supporting oil and gas transportation systems

How to use the dataset

Dataset Overview

The dataset contains several columns with information about each submarine pipeline. Here is an overview of each column:

• Category_o: The category or type of the submarine pipeline.
• Product: The product being transported through the submarine pipeline, such as oil or gas.
• Object_Nam: The name or identifier of the submarine pipeline.
• Status: The current status of the submarine pipeline, such as active or decommissioned.
• Informatio: Additional information or details about the submarine pipeline.
• Scale_Mini: The minimum scale at which the submarine pipeline is visible on a map.
• Source_Dat: The source of data used to create this dataset.
• Source_Ind: The individual or organization that provided the source data.
• Source_D_1: Additional source information or details about this specific data.
• Shape_Leng: The length of the submarine pipeline in meters.

Accessing and Analyzing Data

To access and start analyzing this dataset, you can follow these steps:

• Download: First, download the Submarine Pipeline Lines_USACE_IENC.csv file from its source.

• The downloaded file should be saved in your project directory.

• Open CSV File: Open your preferred programming environment (e.g., Python with Pandas) and read/load this CSV file into a dataframe.

• Data Exploration: Explore the dataset by examining its columns, rows, and general structure. Use pandas functions like head(), info(), or `descr...

The Oil and Gas Infrastructure Mapping (OGIM) database is a global, spatially explicit, and granular database of oil and gas infrastructure, developed at Environmental Defense Fund (EDF) (www.edf.org). The OGIM database is developed to support the quantification and source characterization of oil and gas methane emissions. The database development is based on the acquisition, analysis, curation, integration, and quality-assurance, performed at EDF, of public-domain datasets reported by official government sources, industry, academic, and other non-government entities.

The OGIM database includes locations and facility attributes of oil and gas infrastructure types that are important sources of methane emissions, including oil and gas production wells, offshore production platforms, natural gas compressor stations, processing facilities, liquefied natural gas facilities, crude oil refineries, pipelines, etc.

The OGIM_v1 database includes approximately six million features, including 2.6 million point locations of oil and gas facility types and over 2.6 million kilometers of oil and gas pipelines. This work and the OGIM database, which we anticipate updating on a regular cadence, helps fill a crucial oil and gas geospatial data need, in support of the quantification and attribution of global oil and gas methane emissions at high resolution.

Full details for database development and related analytics can be found in the following journal paper, which is under review at Earth System Science Data journal.

Please cite the paper when using the database:

Omara, M., Gautam, R., O'Brien, M., Himmelberger, A., Franco, A., Meisenhelder, K., Hauser, G., Lyon, D., Chulakadaba, A., Miller, C., Franklin, J., Wofsy, S., and Hamburg, S.: Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-452, 2023.

Important note: While we describe these datasets in detail in the manuscript above, and include maps for all acquired datasets, this open-access version of the OGIM database does not include the locations of about 300 natural gas compressor stations in Russia. Future updates may include these datasets when appropriate permissions to make them publicly accessible are obtained.

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OGIM_v1.1.gpkg. May-10-2023 update:

• This update includes the addition of natural gas flaring detections for the year 2021 based on the VIIRS dataset, available from the Earth Observation Group at Colorado School of Mines, as described in the manuscript text.
  
  
• The current version of the OGIM (OGIM_v1.1) is based on public-domain datasets reported on or prior to January 2023. Each record in OGIM includes a source date when the data was last updated. Some records may have out-of-date information, for example, if facility status has changed since we last acquired the data. We are continuing to update the OGIM database as new public-domain datasets become available.

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Point of Contact at Environmental Defense Fund: Ritesh Gautam (rgautam@edf.org).

kaiju database for MetaMeta pipeline version 1. The database was generated by the makeDB.sh script and it is based on the NCBI RefSeq Complete Genome sequences (protein sequences) of Archaea and Bacteria dating from 2016-11-07

Information layer of the Topographic Database of the Province of Lodi. L070701 - Section of oil pipeline line. It involves all systems for the distribution of liquids in pipelines except water.

Supplemental files to accompany the manuscript: Feshuk et al., "The ToxCast Pipeline: Updates to Curve-fitting Approaches and Database Structure", DOI https://doi.org/10.3389/ftox.2023.1275980, PMC10552852. This dataset is associated with the following publication: Feshuk, M., L. Kolaczkowski, K. Dunham, S. Davidson-Fritz, K. Carstens, J. Brown, R. Judson, and K. Friedman. The ToxCast Pipeline: Updates to Curve-fitting Approaches and Database Structure. Frontiers in Toxicology. Frontiers, Lausanne, SWITZERLAND, 5: 1275980, (2023).

Plant pathogen database for RAPiD pipline at https://github.com/SteveKnobloch/RAPiD_pipeline

Version 230309

Pathogen index for machines with < 8GB RAM

The National Pipeline Mapping System (NPMS) is a geographic information system (GIS) created by the U.S. Department of Transportation, Pipeline and Hazardous Materials Safety Administration (PHMSA), Office of Pipeline Safety (OPS) in cooperation with other federal and state governmental agencies and the pipeline industry. The NPMS consists of geospatial data, attribute data, public contact information, and metadata pertaining to the interstate and intrastate hazardous liquid trunklines and hazardous liquid low-stress lines as well as gas transmission pipelines, liquefied natural gas (LNG) plants, and hazardous liquid breakout tanks jurisdictional to PHMSA.

The Intermodal Freight Facilities - Pipeline Terminals dataset was compiled on February 02, 2021 and was updated on April 21, 2021 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Pipeline terminals interface between pipeline mode and other transportation modes. They have the ability to receive or deliver freight commodities via pipeline and truck/rail/water. The data consists of location information, truck/rail/water mode connections, storage capacity, and a list of commodities handled at the terminal. Geographical coverage includes the United States and U.S. territories. This dataset is one of several layers in the Bureau of Transportation Statistics (BTS) Intermodal Freight Facility Database.

The Natural Gas Interstate and Intrastate Pipelines dataset was updated on October 21, 2020 from the Energy Information Administration (EIA), with attribute data from the end of calendar year 2024 and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This is a polyline dataset representing the major natural gas transmission pipelines in the U.S. including interstate, intrastate, and gathering pipelines. These data were compiled by the U.S. Energy Information Administration from various sources including federal and state agencies, and other external sources such as company web pages and industry press. Updated January 2020. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529018

The Allan Lab has published a Fluidigm pipeline online. This is the url: https://github.com/HPCBio/allan-fluidigm-pipeline. This url includes a tutorial for running the pipeline. However it does not have test datasets yet. This tarball hosted at the Illinois Data Bank is the dataset that completes the github tutorial. It includes inputs (custom database of tick pathogens and fluidigm raw reads) and output files (tables of samples with taxonomic classifications).

The CO2 Transport Planning Database v3.0 is a geospatial resource, containing over 70 gigabytes of data representing critical considerations for the spatial routing of pipelines and transport of CO2, from source to sink. Considerations include state-specific legislation, land use requirements, existing infrastructure, and hazard prevention areas. Built to support strategic domestic energy transport planning and development, more than 60 layers of this database have been weighted (Weight fields) according to current legislation and pipeline construction recommendations. Weighted values range from zero to one, where zero represents potentially more acceptable areas for transport based on the various considerations, and a value of one represents areas that should be avoided. This geospatial database provides a baseline for the Smart CO2 Transport Planning Tool.

LncRNAs are RNA molecules longer than 200 nucleotides that do not encode proteins. Experimental studies have demonstrated the diversity and importance of lncRNA functions in plants: involvement in the regulation of gene expression, homeostasis of plant physiological parameters. However, structure and function features are known only for a small number of lncRNAs and were experimentally confirmed only for single cases. To expand knowledge about lncRNA in other species, computational pipelines that allow standardized data processing steps in a mode that does not require user control up to the final result have recently been actively developed. This makes it possible to implement wider functionality for lncRNA data identification and analysis. In the present work, we proposed a pipeline ICAnnoLncRNA for automatic prediction, classification, and annotation of plant lncRNAs. This pipeline was applied to analysis of 877 maize transcriptome libraries. More than 9 million lncRNAs were predicted and classified into 3 classes with respect to their localization in the genome, structural features of lncRNAs, tissue specificity, and homology with other organisms.