Conservation implications of omitting historical data sources: response to Baisre

2015 ◽  
Vol 30 (1) ◽  
pp. 226-227 ◽  
Author(s):  
Loren McClenachan ◽  
Andrew B. Cooper ◽  
Marah Hardt ◽  
Matthew McKenzie ◽  
Joshua A. Drew
Keyword(s):  
Historical Data ◽  
Data Sources ◽  
Conservation Implications

scholarly journals Global Cycles: Capital Flows, Commodities, and Sovereign Defaults, 1815–2015

2016 ◽  
Vol 106 (5) ◽  
pp. 574-580 ◽  
Author(s):  
Carmen M. Reinhart ◽  
Vincent Reinhart ◽  
Christoph Trebesch
Keyword(s):  
Capital Flows ◽  
Historical Data ◽  
Commodity Prices ◽  
Commodity Price ◽  
Capital Inflows ◽  
Data Sources ◽  
Financial Capital ◽  
Global Capital ◽  
Sovereign Defaults ◽  
Global Cycles

Capital flow and commodity cycles have long been connected with economic crises. Sparse historical data, however, has made it difficult to connect their timing. We date turning points in global capital flows and commodity prices across two centuries and provide estimates from alternative data sources. We then document a strong overlap between the ebb and flow of financial capital, the commodity price super-cycle, and sovereign defaults since 1815. The results have implications for today, as many emerging markets are facing a double bust in capital inflows and commodity prices, making them vulnerable to crises.

scholarly journals System approach for Digital History

2020 ◽  
Vol 33 ◽  
pp. 03002
Author(s):  
Nikolay Bystritskiy
Keyword(s):  
System Approach ◽  
Historical Data ◽  
Information Storage ◽  
Data Sources ◽  
Practical Implementation ◽  
Digital Form ◽  
Historical Knowledge ◽  
Digital History ◽  
Theoretical Foundations ◽  
Clear Presentation

Present advanced capabilities for information storage and a clear presentation, uncover the possibility of accumulation in digital form large volumes of historical data. For this purpose, it is necessary to establish the theoretical foundations and principles of formalization and presentation of historical knowledge. This paper presents the description and experience of practical implementation of the developed methods for formalization and analysis of historical data sources.

A mixture-of-modelers approach to forecasting NCAA tournament outcomes

2015 ◽  
Vol 11 (1) ◽  
Author(s):  
Lo-Hua Yuan ◽  
Anthony Liu ◽  
Alec Yeh ◽  
Aaron Kaufman ◽  
Andrew Reece ◽  
...  
Keyword(s):  
Information Sources ◽  
Historical Data ◽  
Data Sources ◽  
Statistical Prediction ◽  
Post Processing ◽  
Men's Basketball ◽  
Sporting Event ◽  
Working Together ◽  
Performance Variations

AbstractPredicting the outcome of a single sporting event is difficult; predicting all of the outcomes for an entire tournament is a monumental challenge. Despite the difficulties, millions of people compete each year to forecast the outcome of the NCAA men’s basketball tournament, which spans 63 games over 3 weeks. Statistical prediction of game outcomes involves a multitude of possible covariates and information sources, large performance variations from game to game, and a scarcity of detailed historical data. In this paper, we present the results of a team of modelers working together to forecast the 2014 NCAA men’s basketball tournament. We present not only the methods and data used, but also several novel ideas for post-processing statistical forecasts and decontaminating data sources. In particular, we highlight the difficulties in using publicly available data and suggest techniques for improving their relevance.

scholarly journals The PRIMAP-hist national historical emissions time series

2016 ◽  
Vol 8 (2) ◽  
pp. 571-603 ◽  
Author(s):  
Johannes Gütschow ◽  
M. Louise Jeffery ◽  
Robert Gieseke ◽  
Ronja Gebel ◽  
David Stevens ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Growth Rates ◽  
Agricultural Land ◽  
Historical Data ◽  
Data Sources ◽  
Additional Time ◽  
Country Level ◽  
History Of ◽  
Different Sources

Abstract. To assess the history of greenhouse gas emissions and individual countries' contributions to emissions and climate change, detailed historical data are needed. We combine several published datasets to create a comprehensive set of emissions pathways for each country and Kyoto gas, covering the years 1850 to 2014 with yearly values, for all UNFCCC member states and most non-UNFCCC territories. The sectoral resolution is that of the main IPCC 1996 categories. Additional time series of CO2 are available for energy and industry subsectors. Country-resolved data are combined from different sources and supplemented using year-to-year growth rates from regionally resolved sources and numerical extrapolations to complete the dataset. Regional deforestation emissions are downscaled to country level using estimates of the deforested area obtained from potential vegetation and simulations of agricultural land. In this paper, we discuss the data sources and methods used and present the resulting dataset, including its limitations and uncertainties. The dataset is available from doi:10.5880/PIK.2016.003 and can be viewed on the website accompanying this paper (http://www.pik-potsdam.de/primap-live/primap-hist/).

Enhancing COVID-19 Epidemics Forecasting Accuracy by Combining Real-time and Historical Data from Social Media, Online News Articles, and Search Queries (Preprint)

2021 ◽  
Author(s):  
Jingwei Li ◽  
Wei Huang ◽  
Choon Ling Sia ◽  
Zhuo Chen ◽  
Tailai Wu ◽  
...  
Keyword(s):  
Public Health ◽  
Real Time ◽  
Historical Data ◽  
Mainland China ◽  
Hubei Province ◽  
Online News ◽  
Data Sources ◽  
Resources Allocation ◽  
Forecasting Accuracy ◽  
Proposed Model

BACKGROUND The SARS-COV-2 virus and its variants are posing extraordinary challenges for public health worldwide. More timely and accurate forecasting of COVID-19 epidemics is the key to maintaining timely interventions and policies and efficient resources allocation. Internet-based data sources have shown great potential to supplement traditional infectious disease surveillance, and the combination of different Internet-based data sources has shown greater power to enhance epidemic forecasting accuracy than using a single Internet-based data source. However, existing methods incorporating multiple Internet-based data sources only used real-time data from these sources as exogenous inputs, but didn’t take all the historical data into account. Moreover, the predictive power of different Internet-based data sources in providing early warning for COVID-19 outbreaks has not been fully explored. OBJECTIVE The main aim of our study is to explore whether combining real-time and historical data from multiple Internet-based sources could improve the COVID-19 forecasting accuracy over the existing baseline models. A secondary aim is to explore the COVID-19 forecasting timeliness based on different Internet-based data sources. METHODS We first used core terms and symptoms related keywords-based methods to extract COVID-19 related Internet-based data from December 21, 2019, to February 29, 2020. The Internet-based data we explored included 90,493,912 online news articles, 37,401,900 microblogs, and all the Baidu search query data during that period. We then proposed an autoregressive model with exogenous inputs, incorporating the real-time and historical data from multiple Internet-based sources. Our proposed model was compared with baseline models, and all the models were tested during the first wave of COVID-19 epidemics in Hubei province and the rest of mainland China separately. We also used the lagged Pearson correlations for the COVID-19 forecasting timeliness analysis. RESULTS Our proposed model achieved the highest accuracy in all the five accuracy measures, compared with all the baseline models in both Hubei province and the rest of mainland China. In mainland China except Hubei, the COVID-19 epidemics forecasting accuracy differences between our proposed model (model i) and all the other baseline models were statistically significant (model 1, t=–8.722, P<.001; model 2, t=–5.000, P<.001, model 3, t=–1.882, P =0.063, model 4, t=–4.644, P<.001; model 5, t=–4.488, P<.001). In Hubei province, our proposed model's forecasting accuracy improved significantly compared with the baseline model using historical COVID-19 new confirmed case counts only (model 1, t=–1.732, P=0.086). Our results also showed that Internet-based sources could provide a 2-6 days earlier warning for COVID-19 outbreaks. CONCLUSIONS Our approach incorporating real-time and historical data from multiple Internet-based sources could improve forecasting accuracy for COVID-19 epidemics and its variants, which may help improve public health agencies' interventions and resources allocation in mitigating and controlling new waves of COVID-19 or other epidemics.

scholarly journals Six decades of changes in the riparian corridor of a Mediterranean river: a synthetic analysis based on historical data sources

Ecohydrology ◽  
2012 ◽  
Vol 6 (4) ◽  
pp. 536-553 ◽  
Author(s):  
V. Garófano-Gómez ◽  
F. Martínez-Capel ◽  
W. Bertoldi ◽  
A. Gurnell ◽  
J. Estornell ◽  
...  
Keyword(s):  
Historical Data ◽  
Data Sources ◽  
Mediterranean River ◽  
Riparian Corridor

Words from the Past

2020 ◽  
pp. 101-126
Author(s):  
C. Riley Augé
Keyword(s):  
Historical Data ◽  
Crisis Response ◽  
Data Sources ◽  
Documentary Evidence ◽  
Historical Sources ◽  
The Past ◽  
Salem Witch Trials ◽  
Witch Trials ◽  
Court Proceedings

The process of locating and evaluating historical data sources is presented here as a prelude to the analysis of the detailed magical references abstracted from historic archives. The sources are divided into primary and secondary general historical sources including letters, diaries, magical treatises and compilations, sermons, magical symbolism, and herbal collections and the documentary evidence from the Salem witch trials and other court proceedings. These sources provide the first glimpse into concerns over threshold permeability and the use of gender related magic as a crisis response to protect those domestic boundaries.

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