Funded by a grant from the Sloan Foundation, and with support from Massachusetts Open Cloud, the Center for Geographic Analysis(CGA) at Harvard developed a “big geodata”, remotely hosted, real-time-updated dataset which is a prototype for a new data type hosted outside Dataverse which supports streaming updates, and is accessed via an API. The CGA developed 1) the software and hardware platform to support interactive exploration of a billion spatio-temporal objects, nicknamed the "BOP" (billion object platform) 2) an API to provide query access to the archive from Dataverse 3) client-side tools for querying/visualizing the contents of the archive and extracting data subsets. This project is currently no longer active. For more information please see: http://gis.harvard.edu/services/project-consultation/project-resume/billion-object-platform-bop. “Geotweets” are tweets containing a GPS coordinate from the originating device. Currently 1-2% of tweets are geotweets, about 8 million per day. The CGA has been harvesting geotweets since 2012.

Harvard CGA Geotweet Geography Archive is a subset of Harvard CGA Geotweet Archive v2.0 enriched with boundaries at the ADMIN-2 level. It contains the tweet identification records and ADMIN 2 variables for more than 4.3 billion geo-tagged tweets since 2019. This dataset has been used to calculate the geographic variables of our Twitter Sentiment Geographical Index dataset and is available to the academic community at large, unlike the Harvard CGA Geotweet Archive v2.0 which is under Twitter's redistribution policy restriction for public sharing. It could serve as cross-validation data for publications that used data from Harvard CGA Geotweet Archive v2.0 . If you are interested in accessing this archive, please fill out our Geotweet Request Form. Before requesting or receiving Tweet IDs, requestors must agree to Twitter's Terms of Service, Twitter's Privacy Policy, and Twitter's Developer Policy . Geotweets IDs data provided by CGA can only be used for not-for-profit research and academic purposes. Recipients may not share CGA provided Tweet IDs or content derived from them without written permission from the CGA. Citations: If you use the Geotweet Archive in your research please reference it: "Harvard CGA Geotweet IDs Archive". ======================================================== Schema of Geotweet Census Archive Field name_TYPE_Description message_id----TEXT----Tweet ID OBJECTID ----INT----Object ID ID_0 ----INT----Country/Region ID NAME_0 ----TEXT----Country/Region Name ISO ----TEXT----Country/Region Abbreviation ID_1 ----INT----State/Province ID NAME_1 ----TEXT----State/Province Name ID_2 ----INT----County/City ID NAME_2 ----TEXT----County/City Name

Harvard CGA Geotweet Sentiment Archive is a subset of Harvard CGA Geotweet Archive v2.0 enriched with a sentiment score. It contains the tweet identification records along with a sentiment score based on tweet text for about 4.3 billion geo-tagged tweets since 2019. This sentiment score was calculated using Bidirectional Encoder Representations from Transformers. More information about this methodology can be found in our Nature Paper on Twitter Sentiment Geographical Index. This dataset is available to the academic community at large, unlike the Harvard CGA Geotweet Archive v2.0 which is under Twitter's redistribution policy restriction for public sharing. It could serve as cross-validation data for publications that used data from Harvard CGA Geotweet Archive v2.0 . If you are interested in accessing this archive, please fill out our Geotweet Request Form. Before requesting or receiving Tweet IDs, requestors must agree to Twitter's Terms of Service, Twitter's Privacy Policy, and Twitter's Developer Policy . Geotweets IDs data provided by CGA can only be used for not-for-profit research and academic purposes. Recipients may not share CGA provided Tweet IDs or content derived from them without written permission from the CGA. Citations: If you use the Geotweet Archive in your research please reference it: "Harvard CGA Geotweet IDs Archive". ======================================================== Schema of Geotweet Census Archive Field name_TYPE_Description message_id----TEXT----Tweet ID score ----FLOAT----BERT sentiment score

Click to add a brief description of the dataset (Markdown and LaTeX enabled).

Provide:

a high-level explanation of the dataset characteristics explain motivations and summary of its content potential use cases of the dataset

Harvard CGA Geotweet IDs Archive is a subset of Harvard CGA Geotweet Archive v2.0 . It contains the user and message identification records of individual tweets for approximately 10 billion geo-tagged tweets from January 2010 to July 2023. This dataset is available to the academic community at large, unlike the Harvard CGA Geotweet Archive v2.0 which is under Twitter's redistribution policy restriction for public sharing. It could serve as cross-validation data for publications that used data from Harvard CGA Geotweet Archive v2.0 . If you are interested in accessing this archive, please fill out our Geotweet Request Form. Before requesting or receiving Tweet IDs, requestors must agree to Twitter's Terms of Service, Twitter's Privacy Policy, and Twitter's Developer Policy . Geotweets IDs data provided by CGA can only be used for not-for-profit research and academic purposes. Recipients may not share CGA provided Tweet IDs or content derived from them without written permission from the CGA. Citations: If you use the Geotweet Archive in your research please reference it: "Harvard CGA Geotweet IDs Archive". ======================================================== Schema of Geotweet IDs Archive Field name_TYPE_Description message_id----BIGINT----Tweet ID user_id ----BIGINT----User ID number

Take a looks at the Harvard Map Collection's interactive exhibit 'Embellishing the Map,' which explores the myriad varieties and uses of embellishments found on the library's extraordinary collection of maps.This exhibition presents maps chosen from the Harvard Map Collection that display how European cartographers, mainly from the Low Countries of the 16th and 17th centuries, embellished maps with a variety of illustrative, non-cartographic elements. With echoes of the classical world’s anxiety of the “horror vacuii” (fear of empty spaces), the uncharted and unknown spaces are populated with sea creatures and animals, from the mythic and fantastic to the zoologically accurate, and many varieties of ships plying the open seas. All in their natural habitat, which is to say located on the land and seas of the map, not as artistic embellishments in cartouches or title panels (something for another exhibition, perhaps). The sources for the cartographic fauna run the gamut from classical sources (the histories of Herodotus and Pliny the Elder), Medieval bestiaries and compendiums of the natural world (Hortus Sanitatis), to accounts from the ever peripatetic explorers. The maps are presented in loosely geographic order, beginning (where everything begins) with the heavens, then, after a medieval view of the known world, moves from the Western Hemisphere eastward to the Pacific Ocean. Besides the few modern, more thematic maps that have been included for contrast, chronologically this exhibition effectively ends before the ascendancy of the Royally sponsored French cartographers of the 18th century. The maps of Delisle, Bellin, d’Anville and the distinguished Cassini dynasty migrate the sea creatures, animals and ships to the pages and articles of Diederot’s grand Encyclopedia. What now is presented on the map reflects the science of cartography and measurement reigning supreme, not alas (as seen in the 1541 map “Tabula noua partis Africae”), a King riding a bridled Sea Carp!

Harvard CGA 2018 Datafest Presentation on Dataverse and WorldMap

Take a looks at the Harvard Map Collection's interactive exhibit 'Manuscript Maps,' which explores the library's extraordinary collection of hand-drawn manuscript maps.Behind every manuscript map lies an individual’s hand. Unlike printed maps, where a combination of drafting, engraving, and printing distances particular sheets from the people who produced them, manuscript maps carry the pressure and movement of individual bodies. The weight of these individual bodies interweave the stories of individuals with the material lives of the maps themselves. In a nautical chart made of the Fiji islands, we can follow the path of the ship Sally to see the human cost of a short boom in the Sandalwood trade; in a draft of a map of US railroad systems, we can imagine a cartographer’s frustrations when we see the demands a never-satisfied author has made in the margins; in a survey of the property of the late Philip Wheeler in Rehoboth, Massachusetts, we can feel the cold of a New England day in late December on the surveyor’s hands as he divided the land for Wheeler’s wife and heirs. Each map invites you into the world—as big as the earth or as small as a backyard—that someone laid out by hand.These stories often begin before ink was put to paper and have continued long after that ink has dried. Most of these maps rely on previous models, whether someone has traced, copied, transferred, or improved that original map. As individuals trace, copy, and amend the maps in front of them, they graft their own lives into stories of their maps. As murky as their origins can be, their futures are no clearer. When, after all, is a manuscript finished? We would struggle to distinguish a line or a legend added a day, a week, a month, maybe even a year after the initial marks on a map from two hundred years ago. These manuscripts point to a moment in a story that radiates into both past and future.These hazy beginnings and endings invite us into the ongoing life stories of these manuscripts as we discover the many lives that touch them.

Harvard CGA Geotweet Census Archive is a subset of Harvard CGA Geotweet Archive v2.0 enriched with nationwide census data. It contains the tweet and user identification records along with census variables and sentiment scores for more than 2 billion geo-tagged tweets from January 2012 to July 2023. The sentiment scores are derived from the BERT sentiment scores from the Harvard CGA Geotweet Sentiment Archive. This dataset is available to the academic community at large, unlike the Harvard CGA Geotweet Archive v2.0 which is under Twitter's redistribution policy restriction for public sharing. It could serve as cross-validation data for publications that used data from Harvard CGA Geotweet Archive v2.0 . If you are interested in accessing this archive, please fill out our Geotweet Request Form. Before requesting or receiving Tweet IDs, requestors must agree to Twitter's Terms of Service, Twitter's Privacy Policy, and Twitter's Developer Policy . Geotweets IDs data provided by CGA can only be used for not-for-profit research and academic purposes. Recipients may not share CGA provided Tweet IDs or content derived from them without written permission from the CGA. Citations: If you use the Geotweet Archive in your research please reference it: "Harvard CGA Geotweet IDs Archive". ======================================================== Schema of Geotweet Census Archive Field name_TYPE_Description day----TEXT----The date of the tweet (YYYY-MM-DD) GEOID20----TEXT----Census block geoid tweet_count----INTEGER----Number of tweets in the census block user_count----INTEGER----Number of unique users in the census block avg_score----FLOAT----The average tweet sentiment score in the census block max_score----FLOAT----The maximum tweet sentiment score in the census block min_score----FLOAT----The minimum tweet sentiment score in the census block std_score----FLOAT----The standard deviation of tweet sentiment scores in the census block score_10q----FLOAT----The 10th quantile tweet sentiment score in the census block score_25q----FLOAT----The 25th quantile tweet sentiment score in the census block score_50q----FLOAT----The 50th quantile (median) tweet sentiment score in the census block score_75q----FLOAT----The 75th quantile tweet sentiment score in the census block score_90q----FLOAT----The 90th quantile tweet sentiment score in the census block

From a Boston Globe article, June 3, 1971 [georectified].

Net Migration (absolute value) per Province, and Bi-Directional Net Migration (absolute value) Between Provinces using the 2010 Census. Analysis and map by Fei Carnes. Webmap version of this data: http://worldmap.harvard.edu/maps/chinamap/coW See also the dynamic China Migration web map application for 1995, 2000, 2005, 2010 by Giovanni Zambotti. http://maps.cga.harvard.edu/crossroadsofmigration/china/

Massachusetts Dept. of Public Works, U.S. Bureau of Public Roads Archives.[Georectified]

Archive of VECTOR datasets collected in response to the Haiti Earthquake of 2010. These are the final archive of data that were previously available from the reitred website (cegrp.cga.harvard.edu/haiti) See also archives at: http://wiki.crisiscommons.eu/wiki/Haiti/2010_Earthquake http://www.gelib.com/haiti-earthquake.htm http://supersites.earthobservations.org/haiti.php (2015-09-02)Original Data from: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/BAGUVN

Archive of VECTOR datasets collected in response to the Haiti Earthquake of 2010. These are the final archive of data that were previously available from the reitred website (cegrp.cga.harvard.edu/haiti) See also archives at: http://wiki.crisiscommons.eu/wiki/Haiti/2010_Earthquake http://www.gelib.com/haiti-earthquake.htm http://supersites.earthobservations.org/haiti.php (2015-09-02)Original Data from: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/BAGUVN

Archive of VECTOR datasets collected in response to the Haiti Earthquake of 2010. These are the final archive of data that were previously available from the reitred website (cegrp.cga.harvard.edu/haiti) See also archives at: http://wiki.crisiscommons.eu/wiki/Haiti/2010_Earthquake http://www.gelib.com/haiti-earthquake.htm http://supersites.earthobservations.org/haiti.php (2015-09-02)Original Data from: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/BAGUVN

The Chinese Chronology Table was compiled primarily from the appendix 中国历史纪年表 found in the third volume of the 辞海 1979 edition. Disclaimer: users of the table should verify specific dates in your own best sources before relying on them in your work. See online service: http://maps.cga.harvard.edu/chgis/periods/ See also DDBC Time Authority: http://authority.dila.edu.tw/time/

Archive of RASTER datasets collected in response to the Haiti Earthquake of 2010. These are the final archive of data that were previously available from the reitred website (cegrp.cga.harvard.edu/haiti) See also archives at: http://wiki.crisiscommons.eu/wiki/Haiti/2010_Earthquake http://www.gelib.com/haiti-earthquake.htm http://supersites.earthobservations.org/haiti.php

Archive of VECTOR datasets collected in response to the Haiti Earthquake of 2010. These are the final archive of data that were previously available from the reitred website (cegrp.cga.harvard.edu/haiti) See also archives at: http://wiki.crisiscommons.eu/wiki/Haiti/2010_Earthquake http://www.gelib.com/haiti-earthquake.htm http://supersites.earthobservations.org/haiti.php (2015-09-02)Original Data from: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/BAGUVN

Many publicly-funded schools in Boston utilize exclusionary discipline practices, such as in-school and out-of-school suspensions. There has been a recent move towards strict discipline structures –such as “No Excuses” policies – with the aim of improving achievement. However, every time a student is disciplined they miss valuable learning time, which has a detrimental impact on learning outcomes. This is particularly concerning if students of color are being disproportionately impacted by school discipline.School administrators hold immense power when it comes to reforming discipline policies and eliminating exclusionary discipline in their schools. This report aims to inform administrators of the impact exclusionary discipline practices have on racial disparities and learning outcomes to position them to drive change in their schools.

From January 2019 to December 2021, 59 patients with Syn expression but no CgA expression were collected from 1298 patients with gastric cancer treated by operation in the General Hospital of the Chinese People's Liberation Army.