This statistic shows the typical daily number of passenger entries at Oxford Circus Underground station (broken down into weekday entries, Saturday entries and Sunday entries) from 2007 to 2017. On a typical weekday in 2017 roughly 121,000 people entered Oxford Circus station.

(:unav)...........................................

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Harvard Forest (HFR) contains percent urban population measurements in percent units and were aggregated to a yearly timescale.

Electromagnetics : history, theory, and applications is a book. It was written by Robert Stratman Elliott and published by Oxford University Press in 1993.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Harvard Forest (HFR) contains human population (total) measurements in number units and were aggregated to a yearly timescale.

In Autumn 2024, among the students enrolled in the highest ranked university in the world, Oxford in the United Kingdom, 51 percent were female. See here for an overview of the highest-ranked universities in the world.

Asset-Level Compass is a comprehensive dataset cataloguing over 150 data sources across diverse sectors, including carbon emissions, financial markets, waste management, and environmental risk. Each entry provides critical information on global coverage, methodology, data format, and accessibility. It allows users to quickly identify and assess sources relevant to asset-level climate risk, financial performance, and sustainability.

The dataset is structured to provide an easy-to-navigate overview, supporting asset managers, financial institutions, and researchers in developing robust climate risk assessments and sustainability strategies. By offering insights into how various sectors collect, analyse, and share information on climate hazards, environmental exposures, and financial implications, this resource serves as a valuable tool for understanding the landscape of asset-level data sources.

Asset-Level Compass builds upon the foundational work titled Synthesis of Hazard, Vulnerability, and Asset-Level Data Sources for Physical Climate Risk Assessment and Adaptation.

Link: https://ora.ox.ac.uk/objects/uuid:3b05bf63-963c-4e7e-8218-2a6759f21ab5

In this dataset, I expanded the asset-level data sources catalogue by incorporating additional sources, refining methodologies, and improving its application for financial and environmental risk assessments.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

LON:OMG OXFORD METRICS PLC

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Battery degradation data for energy trading with physical models contains data collected from a year-long experiment where six lithium-ion cells were following current profiles corresponding to real-world usage profiles. The profiles were designed for grid-connected batteries trading power on the day-ahead wholesale market. The data set contains monthly capacity measurements as well as measurements of current, voltage and temperature while the cells were being cycled. See Readme.txt for a full description of the data and the licence under which it is made available.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Harvard Forest (HFR) contains population employed in service (percent of total) measurements in percent units and were aggregated to a yearly timescale.

In the 2022/23 academic year, 30 percent of undergraduate students obtaining their degree were awarded a degree with first-class honors, the highest possible grade for UK graduates. Almost half of all students achieved an upper second or 2.1, with 20 percent obtaining a lower second or 2.2, and just four percent of graduates obtained a third, the lowest possible pass grade. The share of UK students graduating with a first-class degree has increased significantly in this time period, while the share of students obtaining a 2.2 has fallen the most in the same time period. GCSE and A-Level grades also on the rise Higher grades for the UK's main qualification for high school students, the general certificate of secondary education (GCSE), have also increased in recent years. In 1988 for example, approximately 8.4 percent of GCSE entries received the highest grade, compared with 22 percent in 2023. This is also the case to a lesser-extent for advanced level GCSE results (A-Levels), with the share of entries being awarded an A or A* increasing from 17.8 percent in 2000 to 25.4 percent in 2023. There is no consensus on if these improvements are due to increased ability, or to grade inflation. During the COVID-19 pandemic, however, grades in the UK were a lot higher than in other years. This was due to teacher and tutor assessments being giving a higher weighting than normal, with exams being postponed or cancelled completely. The UK's top universities Britain's oldest and most famous universities, Cambridge and Oxford, remained the two highest-ranked universities in the UK in 2024, with the London School of Economics finishing third. According to the ranking, the University of St Andrews was the top university outside the south of England, with Durham University being the highest-ranked university in the north of England. The largest university in terms of enrolled students was the mainly remote focused Open University, which had 151,840 students in 2021/22. Among universities that mainly taught on-campus, University College London had the most students enrolled, at 46,830.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Harvard Forest (HFR) contains population employed at farms (percent of total) measurements in percent units and were aggregated to a yearly timescale.

As of 2020, Hult International Business School in London had an annual intake of 190 EMBA students, the highest among the provided business schools located in the United Kingdom. Oxford Saïd Business School had an annual intake of approximately 134 EMBA students in this year, the second-highest among the provided schools.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Harvard Forest (HFR) contains population employed in manufacturing (percent of total) measurements in percent units and were aggregated to a yearly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Harvard Forest (HFR) contains county area measurements in squareKilometers units and were aggregated to a yearly timescale.

The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities.

Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office.

The following dataset from Harvard Forest (HFR) contains population employed in commerce (percent of total) measurements in percent units and were aggregated to a yearly timescale.