GIST

The Greek Inscriptions in Space and Time (GIST) dataset represents a comprehensive collection of ancient Greek inscriptions, enriched by temporal and spatial metadata. The dataset was created by the Social Dynamics in the Ancient Mediterranean Project (SDAM), 2019-2023, funded by the Aarhus University Forskningsfond Starting grant no. AUFF-E-2018-7-2. The GIST dataset is mainly based on Greek inscriptions from the dataset of Searchable Greek Inscriptions [PHI](https://inscriptions.packhum.org/) and I.PHI dataset published by the Pythia Project (Sommerschield, T. et al. 2021). Furthermore, the attributes were enriched by LOD from the Trismegistos Project, Hansen and Nielsen's (2004) Inventory of Archaic and Classical Greek City-States and Hanson's (2016) Cities Database. The text of the inscriptions was lemmatised using the AGILe lemmatiser (de Graaf et al. 2022). The rights to these data are held by the respective original projects. The GIST dataset consists of 217,863 inscriptions, enriched by 36 attributes. The individual inscriptions have been cleaned, preprocessed and enriched with additional data, such as date in a numeric format and geolocation. The origin of existing attributes is further described in columns 'dataset_source', 'attribute_source', 'created_by_script' and 'description' in the attached Metadata.csv or available via GitHub. 180,061 inscriptions have valid geospatial coordinates (the `geometry` attribute). This information is also used to determine the Roman urban context of each inscription (i.e. whether it is in the neighbourhood (i.e. within a 5000m buffer) of a large city, medium city, or small city or rural (>5000m to any type of city; see the attributes `urban_context`, `urban_context_city`, and `urban_context_pop`) and for their mapping on an ancient Greek polis (if there is any within the 5000m buffer; see the attributes `polis_context_name`, `polis_context_size`, and `polis_context_fame`). 131,677 inscriptions have a numerical date of origin expressed by means of an interval or singular year using the attributes `not_before` and `not_after`. The scripts used to generate the dataset and their metadata are available via GitHub. Formats We publish the dataset in Parquet and GeoJSON file formats. A description of individual attributes is available in the Metadata.csv. Using `geopandas` library, you can load the data directly from Zenodo into your Python environment using the following command: `GIST = gpd.read_file("https://zenodo.org/records/10127597/files/GIST_v1-0.geojson?download=1", driver="GeoJSON")`. In R, the sfarrow and sf libraries hold tools, i.e., st_read_parquet(), read_sf(), to load a parquet and geojson, respectively, after you have downloaded the datasets locally. Further reading: de Graaf, E., Stopponi, S., Bos, J., Peels-Matthey, S. & Nissim, M. (2022). AGILe: The First Lemmatizer for Ancient Greek Inscriptions. Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022), Marseille, 20-25 June 2022. pp. 5334–5344. http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.571.pdf Nielsen, T. H., & Hansen, M. H. (Eds.) (2004). An Inventory of Archaic and Classical Poleis. Oxford University Press. Digitised data available through https://polis.stanford.edu Hanson, J. W. (2016). Cities Database (OXREP databases). Version 1.0. http://oxrep.classics.ox.ac.uk/databases/cities/. DOI: https://doi.org/10.5287/bodleian:eqapevAn8 Kaše, V. & Glomb, T. (2022). The History of Graeco-Roman Religions in the Light of Cultural Evolution: A computational text analysis of ancient Greek inscriptions (submitted). [pdf] Kaše, V. & Glomb, T. (2023). Affluence, Agricultural Productivity and the Rise of Moralizing Religion in the Ancient Mediterranean. Religion, Brain & Behavior 13/2, 202-206. https://doi.org/10.1080/2153599X.2022.2065350 [link] Sommerschield, T., Assael, Y., Shillingford, B., Bordbar, M., Pavlopoulos, J., Chatzipanagiotou, M., Androutsopoulos, I., Prag, J., & de Freitas, N. (2021). I.PHI dataset: Ancient Greek inscriptions. https://github.com/sommerschield/iphi Notes on spatial attributes Machine-readable spatial point geometries are provided within the GeoJSON and parquet formats, as well as 'latitude' and 'longitude' columns, which contain geospatial decimal coordinates where these are known. Other attributes that contain spatial information have been generated from other sources. These include TMgeo_name, which provides the ID of the inscription location as presented in Trismegistos. Information on associated ancient cities within a 5 km buffer of inscription location is within the polis_ and urban_context_ attributes. 'polis-' attributes contain the name, identifier, and the rank of an associated polis from the Hansen/Nielsen's Inventory of Archaic and Classical Greek City-States (Oxford 2005), specifically a digital version of the inventory created by Joshua Ober and his team, hosted by the Stanford University library (https://polis.stanford.edu). Information on Roman-period urban contexts is present in the 'urban_context' attributes. These attributes, based on Hanson's 2016 list (http://oxrep.classics.ox.ac.uk/databases/cities/), include the rank of the associated city (the largest one within 5 km distance), ancient toponym, and population estimate. List of all spatial attributes: 'geometry' - contains spatial point coordinate pair, ready for use in R or Python 'latitude' and 'longitude' - contain angular coordinates in decimal numeric format (EPSG4326) 'TMgeo_name' - id of geographic location for inscription findspot from Trismegistos 'polis_context_name' - the textual component of the ancient polis identifier from the digital Greek polis inventory 'polis_context_size' - 1 to 5 ranking, 5 is largest, based on HN estimates. Range 0-5. 1= 0-25 km sq.; 2 = 25-100 km sq, 3 = 100-200 km sq; 4 = 200-500 km sq; 5 = 500 km sq or more. 0 = no evidence for size. HN Appendix 9, with additions from Hansen 2008 and from Emily Mackil (per litt). 'polis_context_fame' - Number of columns of text in the HN inventory (by 1/8 column), as proxy for prominence of a given place. The range is 0.12-20.87. For display, the range will be reduced to a 1-5 ranking: 0.12-.037 = 1, 0.5-0.87 = 2, 1.0-2.87 = 3, 3.0-5.87 = 4, 6.0-20.87 = 5. 'urban_context' - specifies the rank of a Roman city within 5 km distance of an inscription (if one exists) on the basis of population estimated by Hanson 2016. The scale is: small, medium, large. 'urban_context_city' - contains the name (ancient toponym) of a city within 5 km distance of an inscription (if one exists). The city dataset is based on Hanson 2016. If the inscription's findspot fell within 5 km distance of multiple Roman cities, the largest was selected. 'urban_context_popest' - estimated population of the associated city from Hanson 2016, 2019 Disclaimer Please be aware that the records in this dataset are aggregated from pre-existing sources, and additional attributes are generated on the basis of third-party data (see data provenance in the 'data_source' column in the Metadata.csv). SDAM did not create the original data, vouch for its accuracy, or guarantee that it is the most recent data available from the original data provider. Many variables contain values that are, by nature, approximate and may contain some inaccuracies or missing values. The data may also contain errors introduced by the data provider(s) and/or by SDAM. The openness of our processing scripts should facilitate the fast discovery of any such errors or discrepancies. We highly recommend checking attribute accuracy with the primary source, i.e. the *editio princeps* of the inscription in question. For derived data (e.g. urban_context), please review the associated scripts to understand their limitations. Please contact Petra Hermankova for questions or access (see the current contact address via ORCID).时空希腊铭文（Greek Inscriptions in Space and Time, GIST）数据集是一套全面的古希腊铭文合集，辅以时空元数据进行增广。本数据集由古地中海社会动力学项目（Social Dynamics in the Ancient Mediterranean Project, SDAM）于2019-2023年间创建，受奥胡斯大学研究基金（Aarhus University Forskningsfond）启动资助项目编号AUFF-E-2018-7-2支持。 GIST数据集主要基于可检索希腊铭文数据集（Searchable Greek Inscriptions, PHI）以及皮提亚项目（Pythia Project）发布的I.PHI数据集（Sommerschield, T. 等, 2021）中的古希腊铭文数据。此外，本数据集的属性通过特里斯梅吉斯托斯项目（Trismegistos Project）、汉森与尼尔森（2004）《古风及古典希腊城邦名录》、汉森（2016）《城市数据库》的关联开放数据（Linked Open Data, LOD）进行了扩充。铭文文本通过AGILe词形还原器（AGILe lemmatiser, de Graaf等, 2022）完成词形还原。上述数据的版权归属于各自的原始项目方。 GIST数据集共包含217,863条铭文，辅以36项属性。所有单条铭文均经过清洗、预处理，并补充了数值格式日期与地理定位等额外数据。现有属性的来源可详见附件Metadata.csv中的'dataset_source'、'attribute_source'、'created_by_script'与'description'列，或通过GitHub获取相关信息。 其中180,061条铭文带有有效的地理空间坐标（`geometry`属性）。该信息可用于确定每条铭文所处的罗马城市语境：即铭文是否位于大城市、中等城市、小城市的周边（即距离城市5000米缓冲区范围内），或属于乡村区域（距任何类型城市超过5000米；详见`urban_context`、`urban_context_city`与`urban_context_pop`属性），同时可用于匹配铭文5000米缓冲范围内的古希腊城邦（若存在；详见`polis_context_name`、`polis_context_size`与`polis_context_fame`属性）。 131,677条铭文带有起源数值日期，通过`not_before`与`not_after`属性以时间区间或单一年份的形式表示。 本数据集及其元数据的生成脚本可通过GitHub获取。 ## 数据格式 我们以Parquet与GeoJSON文件格式发布本数据集。各属性的详细说明可在Metadata.csv中查阅。借助geopandas库，您可通过以下命令直接从Zenodo将数据加载至Python环境中： `GIST = gpd.read_file("https://zenodo.org/records/10127597/files/GIST_v1-0.geojson?download=1", driver="GeoJSON")`。 在R语言中，可分别使用sfarrow与sf库提供的`st_read_parquet()`与`read_sf()`工具，在本地下载数据集后加载Parquet与GeoJSON格式数据。 ## 拓展阅读 de Graaf, E., Stopponi, S., Bos, J., Peels-Matthey, S. & Nissim, M. (2022). AGILe: 首款古希腊铭文词形还原器. 第13届语言资源与评估会议（LREC 2022）论文集，马赛，2022年6月20-25日，第5334–5344页。http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.571.pdf Nielsen, T. H., & Hansen, M. H. (Eds.) (2004). 《古风及古典城邦名录》. 牛津大学出版社。数字化数据可通过https://polis.stanford.edu获取 Hanson, J. W. (2016). 城市数据库（OXREP数据库）1.0版. http://oxrep.classics.ox.ac.uk/databases/cities/. DOI: https://doi.org/10.5287/bodleian:eqapevAn8 Kaše, V. & Glomb, T. (2022). 从文化演化视角看希腊罗马宗教史：古希腊铭文的计算文本分析（已投稿）. [pdf] Kaše, V. & Glomb, T. (2023). 富裕程度、农业生产力与古地中海道德化宗教的兴起. 《宗教、大脑与行为》13/2, 202-206页. https://doi.org/10.1080/2153599X.2022.2065350 [链接] Sommerschield, T., Assael, Y., Shillingford, B., Bordbar, M., Pavlopoulos, J., Chatzipanagiotou, M., Androutsopoulos, I., Prag, J., & de Freitas, N. (2021). I.PHI数据集：古希腊铭文. https://github.com/sommerschield/iphi ## 空间属性说明 GeoJSON与Parquet格式中提供了可机器读取的空间点几何数据，同时附带`latitude`与`longitude`列，存储已知的地理空间十进制坐标。其他包含空间信息的属性均源自其他数据源，其中包括TMgeo_name，其存储了铭文出土地点在特里斯梅吉斯托斯中的位置ID。铭文出土地点5千米缓冲范围内的关联古代城市信息存储于polis_与urban_context_属性中。 `polis-`类属性包含源自汉森/尼尔森《古风及古典希腊城邦名录》（牛津大学出版社，2005）的关联城邦名称、标识符与等级，具体为Joshua Ober及其团队制作的数字化版本，由斯坦福大学图书馆托管（https://polis.stanford.edu）。罗马时期城市语境信息存储于`urban_context`类属性中，这些属性基于汉森2016年的列表（http://oxrep.classics.ox.ac.uk/databases/cities/），包含关联城市的等级（5千米范围内最大的城市）、古代地名与人口估算值。 ### 全部空间属性列表 'geometry' - 存储空间点坐标对，可直接在R或Python中使用 'latitude'与'longitude' - 存储十进制数值格式的角坐标（EPSG:4326） 'TMgeo_name' - 铭文出土地点在特里斯梅吉斯托斯中的地理位置ID 'polis_context_name' - 数字化希腊城邦名录中关联古代城邦标识符的文本部分 'polis_context_size' - 1至5级排名，5代表最大城邦，基于汉森与尼尔森的估算。取值范围为0-5：1=0-25平方千米；2=25-100平方千米；3=100-200平方千米；4=200-500平方千米；5=500平方千米及以上。0代表无尺寸相关证据。数据来自汉森与尼尔森附录9，并补充了汉森2008年与Emily Mackil（私人通信）的内容。 'polis_context_fame' - 汉森与尼尔森名录中的文本列数（以1/8列为单位），作为该地点知名度的代理指标。取值范围为0.12-20.87。为便于展示，该范围被映射为1-5级排名：0.12-0.37=1，0.5-0.87=2，1.0-2.87=3，3.0-5.87=4，6.0-20.87=5。 'urban_context' - 根据汉森2016年的人口估算结果，指定铭文5千米范围内存在的罗马城市等级，分为小型、中型、大型三类。 'urban_context_city' - 存储铭文5千米范围内（若存在）的城市名称（古代地名）。城市数据集基于汉森2016年的数据，若铭文出土地点5千米范围内存在多个罗马城市，则选取最大的城市。 'urban_context_popest' - 汉森2016、2019年估算的关联城市人口 ## 免责声明 请注意，本数据集的记录均汇总自现有数据源，额外属性基于第三方数据生成（详见Metadata.csv中'data_source'列的数据溯源信息）。古地中海社会动力学项目（SDAM）未创建原始数据，不对其准确性作出担保，亦不保证其为原始数据提供商提供的最新版本。许多变量的取值本质上为近似值，可能存在部分错误或缺失值。数据中亦可能包含原始数据提供商或SDAM引入的错误。本项目开源的处理脚本便于快速发现此类错误或不一致之处。我们强烈建议您通过原始来源，即相关铭文的首版校勘本（editio princeps），核对属性的准确性。对于衍生数据（如urban_context），请查阅相关脚本以了解其局限性。 如有疑问或获取数据权限，请联系Petra Hermankova（可通过ORCID查询当前联系方式）。