- Data Categories
Agriculture Data 
B2B Data 
Biometric Data 
Company Data 
Conservation Data 
Demographic Data 
Economic Data 
Environmental Data 
Geospatial Data 
Healthcare Data 
Individual Data 
Industry-Specific Data 
Internet of Things (IoT) Data 
Legal and IP Data 
People and Employment Data 
Political Data 
Psychology Data 
Real Estate Data 
Retail & Commerce Data 
Social Data 
Space Exploration Data 
Sports & Entertainment Data 
Web Data
- Data Categories
- Agriculture Data
- B2B Data
- Biometric Data
- Company Data
- Conservation Data
- Demographic Data
- Economic Data
- Environmental Data
- Geospatial Data
- Healthcare Data
- Individual Data
- Industry-Specific Data
- Internet of Things (IoT) Data
- Legal and IP Data
- People and Employment Data
- Political Data
- Psychology Data
- Real Estate Data
- Retail & Commerce Data
- Social Data
- Space Exploration Data
- Sports & Entertainment Data
- Web Data
What Is Energy Data?
Energy data provides information about energy generation, distribution, and consumption. It encompasses oil, gas, electrical, nuclear, and renewable sources of energy.
Domestic meter readings, satellite imagery of power grids, and more provide energy data. You can buy data to track trends in the industry. Such trends include the increased use of bio-fuels and green vehicles, or forecasts of power outages and surges.
Where Does Energy Data Come From?
The answer to this question depends entirely on what information the data provides. Solar farm data, for example, comes from solar radiation measurements and histories of photovoltaic output statistics. Domestic energy data can be collected by recording household meter readings and supplier bills.
Governments and intergovernmental agencies may also restrict the collection of certain types of this data.
What Types of Columns/Attributes Should I Expect When Working With This Data?
Attributes of this data category include:
- Source of energy (e.g. electrical, gas, oil, nuclear, renewable)
- Solar potential
- Building efficiency
- Electricity transmission
- Frequency of power outages
- Payments taken for mineral resources
What is Energy Data Used For?
Both private and public organizations use this data to ensure their consumption is as efficient as possible. Governments also use it to incentivize responsible energy usage by bench-marking one organization’s consumption against another. They may also use it to digitize a country’s electric grid.
Energy data is crucial in planning the construction of power stations and of wind and solar farms where land and climate conditions must be carefully considered.
Private renewable energy companies also use oil and gas company data to ensure that their sustainable alternatives can meet public demand.
How Should I Test the Quality of This Data?
First, you should ascertain where the data vendor got the data from. For example, only companies working in EU countries, the UK, Canada, and Norway are legally required to disclose all extractive industry payments, so their data is more complete.
Even data collected from public records is subject to the data vendor’s analysis, so the reliability of the vendor should also be assessed. To best determine this, consider how many external factors the vendors take into account in their analyses and how long ago the data was updated.
It should be noted that energy data from developing countries which undergo rapid changes in this sector more likely to be inaccurate than data from developed countries—unless the information was collected very recently.
What Are the Most Important Factors I Should Vet When Selecting This Data?
You must first check the sources of energy your data covers and its latest update. Ideally, you would also clarify the levels of subdivision within the data set. Secondly, you need to know aspects of law related to energy data collection: The disclosure laws in the country where the data has come from and the level of subscription or license type needed to implement the data into your own business. In addition, you should make sure you have the technology required to collect the data you are looking for. You can learn more from organizations and businesses that use this data.
Interesting Case Studies and Blogs to Look Into
US Department of Energy: Data Blog
Our World in Data: Renewable Energy
Tangible Examples of Impact
The Godia Museum in Barcelona needs large amounts of power to “maintain optimal conditions for conserving its works of art.” With an annual consumption rate of 589.999 kWh, costs were about €85.000. By investing in energy efficiency, the museum was able to reduce consumption by 35%—and costs by €25.000 annually.
Dexma: 2 Successful Case Studies in the Energy Management industry
Connected Datasets
Consumer-oriented phosphorus and nitrogen footprints for the U.S.
The P footprint approach described here emulates the N footprint approach described by Leach et al (2012), with updated (circa 2013-2015 ) values for N from Leach et al (submitted). The N footprint is defined as the N release associated with food and energy consumption, where food consumption is comprised of emissions associated with the food production chain and the treatment of human excreta after consumption. Here we focus both N and P footprints only on agricultural production, food processing, food waste, and sewage components (herein collectively the ‘food footprint’) .Leach A M, Galloway J N, Bleeker A, Erisman J W, Kohn R and Kitzes J 2012 A nitrogen footprint model to help consumers understand their role in nitrogen losses to the environment Environmental Development
Tropospheric Emission Spectrometer (TES) Satellite Validations of Ammonia, Methanol, Formic Acid, and Carbon Monoxide over the Canadian Oil Sands
The URLs link to the data archive of the Troposphere Emission Spectrometer (TES) retrievals. These include the transects included in the Canadian Tar Sands study. A brief description of TES is listed below.TES is a spectrometer that measures the infrared-light energy (radiance) emitted by Earth’s surface and by gases and particles in Earth’s atmosphere. Every substance warmer than absolute zero emits infrared radiation at certain signature wavelengths. Spectrometers measure this radiation as a means of identifying the substances.TES has very high spectral resolution, which gives it the ability to pinpoint the wavelengths at which the substances are emitting. This enables precise identification of the substances, and also provides information about their location in the atmosphere. Emission wavelengths can vary with temperature and pressure, so seeing
Data for Martin et al_Zebrafish irritant responses to wildland fire-related biomass smoke are influenced by fuel type, combustion phase, and byproduct chemistry
This data set contains the values used to generate the tables and figures in the manuscript.This dataset is associated with the following publication: Martin, W.K., S. Padilla, Y. Kim, M. Hays, D. Hunter, M. Hazari, D. DeMarini, I. Gilmour, and A. Farraj. Zebrafish irritant responses to wildland fire-related biomass smoke are influenced by fuel type, combustion phase, and byproduct chemistry. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH – PART A: CURRENT ISSUES. Taylor & Francis, Inc., Philadelphia, PA, USA, 84(16): 674-688, (2021).