Verified Burial Mounds in Yambol Province, SE Bulgaria

This release contains field observations collected at mound locations shown in 1:50,000-scale Soviet military topographic maps from 1980s, visited in years 2009-2022 by the Tundzha Regional Archaeologial Project within the Province of Yambol in SE Bulgaria. There are two main datasets: features ( ~1260) which include all kinds of surface phenomena teams encountered when visiting mound locations, such as settlement mounds, surface scatters, etc. Observations at 18 locations have been repeated, producing spatial duplicates with different attributes. A unique version can be generated by filter on one of the two columns Upto2010 and Post2010. mounds (~ 1095) which include only those rows in features dataset classified as extant or extinct burial mounds. Observations at 18 locations have been repeated, producing spatial duplicates with different attributes. A unique version can be generated by filter on one of the two columns Upto2010 and Post2010. These two datasets have been streamlined and clipped to the borders of the Yambol region. While spatial duplicates are identified in each dataset, for purpose of analysis the user can choose among the duplicates by selecting either 2010 or post-2010 version, by filtering on one or another column. Datasets are provided in output_data/ folder in .CSV, .RDS (native R format) and .GeoJSON (spatial format for Python). A number of accompanying datasets were generated for this release and placed in the interim/ folder, including a paired list of all spatial duplicates, an .rds/.geojson file with all verified map features from within and without Yambol Province (the largest dataset of ~ 1466 features) , as well as faims4326.rds fully digitally collected dataset between 2017-2022, containing over 40 attributes as opposed to the shared~27 from the whole span of work 2009-2022. Both the interim and the final datasets can be found in the output_data/ . Attributes in the final datasets are described in the Metadata.csv in the root folder. Broader description of the cleaning process and remaining uncertainties in the datasets can be found in the Readme.md file in the root folder. The scripts used for the processing and streamlining of the data sit in the scripts/ folder. Acknowledgements Collecting a large-scale landscape dataset would not be possible without the dedicated help of local and international colleagues. We owe massive thanks to Barbora Weissova for long-term collaboration on mound monitoring and subsequent assistance with data streamlining. We also thank Petra Heřmánková and Věra Doležálková for leading field teams and managing data collection. Last but not least, the data would not exist were it not for the students, colleagues, and volunteers from the Yambol History Museum, UNSW Australia, Macquarie University, New Bulgarian University, Charles University, Aarhus University and many other institutions. In rough chronological order of appearance these include Iliya Iliev, Georgi Iliev, Yavor Rusev, Stefan Bakardzhiev, Simon Connor, Shawn Ross, Petra Tušlová, Tereza Dobrovodská, Sona Holičková, Scott Jackson, Stanislav Marchovski, Jana Ryšavková, Radko Sedláček, Jarmila Švédová, Dragomir Garbov, Emma Jacobson, Royce Lawrence, Briana Barton, Stephanie Black, Lachlan Hanley, Samuel Riley, Isaac Roberts, Tiana Anderson, Amy Tanswell, Mikaila Walker, Bronwyn Schlamowitz, Elissa Sinclair, Angel Bogdanov Grigorov, Matilde Jensen, Sara Vejrup, Dorthe Pedersen, Julie Lund, Joel Sercombe, Mathias Kaas, and Mathias Johansen. Funding Information This work was supported by the Australian Research Council Linkage Projects Funding scheme LP0989901, University of Michigan International Grant, America for Bulgaria Foundation, Endeavour Short-Term Mobility Programme from the Australian Department of Education, grant 19686; National eResearch Collaboration Tools and Resources (NeCTAR) under eResearch Tools grant RT043; the Australian Research Council under Linkage, Infrastructure, Equipment and Facilities (LIEF) grant LE140100151; Macquarie University and UNSW Australia under internal infrastructure grant schemes; and Aarhus University Forskningsfond Starting grant no. AUFF-2018-7-22 awarded to the ‘Social Complexity in the Ancient Mediterranean’ (SDAM) project.本数据集收录了1980年代1:50000比例尺苏联军用地形图中标注的丘岗点位的野外调查观测数据，这些点位由保加利亚东南部扬博尔省的腾贾区域考古项目（Tundzha Regional Archaeological Project）于2009年至2022年间完成实地考察。 本数据集包含两大核心数据集： **要素数据集（features，约1260条）**：收录考察队在丘岗点位实地考察时记录的各类地表遗存现象，包括聚落丘岗、地表遗存散布区等。其中18个点位的观测数据存在重复采集，即空间位置一致但属性存在差异的副本。可通过筛选Upto2010与Post2010两个字段之一，生成唯一版本的数据集。 **丘岗数据集（mounds，约1095条）**：仅包含要素数据集中被归类为现存或已湮没的墓葬丘岗的记录。同样存在18个点位的重复观测数据，可通过筛选前述两个字段之一生成唯一版本的数据集。 两个数据集均已进行格式精简与空间裁剪，适配扬博尔省辖区范围。尽管各数据集内部存在空间重复记录，用户可根据分析需求，通过筛选对应字段选择2010年及以前或2010年之后的版本。数据集以CSV、.RDS（R原生格式）与.GeoJSON（适用于Python的空间数据格式）三种格式存储于output_data/目录下。 本发布还附带了interim/目录下的多项衍生数据集，包括所有空间重复记录的配对列表、覆盖扬博尔省内外的所有已验证地图要素的.rds/.geojson文件（为规模最大的数据集，包含约1466条要素），以及2017年至2022年间完整数字化采集的faims4326.rds数据集，该数据集包含超过40个属性字段，而2009年至2022年全周期采集的数据集仅共享约27个属性字段。 最终数据集与临时衍生数据集均可在output_data/目录下获取。最终数据集的属性说明详见根目录下的Metadata.csv文件。数据集的清洗流程概述与尚存的不确定性说明，可参阅根目录下的Readme.md文件。数据处理与精简所用的脚本存放于scripts/目录中。 ## 致谢 大规模景观考古数据集的采集离不开国内外同仁的鼎力支持。谨向长期合作开展丘岗监测并协助数据精简工作的巴尔博拉·魏索娃（Barbora Weissova）致以诚挚谢意。同时感谢佩特拉·赫尔曼科娃（Petra Heřmánková）与薇拉·多莱扎尔科娃（Věra Doležálková）带队开展野外调查并统筹数据采集工作。尤为重要的是，若无来自扬博尔历史博物馆（Yambol History Museum）、澳大利亚新南威尔士大学（UNSW Australia）、麦考瑞大学（Macquarie University）、新保加利亚大学（New Bulgarian University）、查理大学（Charles University）、奥胡斯大学（Aarhus University）等诸多机构的学生、同仁与志愿者的参与，本数据集无从诞生。按参与时间大致排序，他们包括：伊利娅·伊利耶夫、格奥尔基·伊利耶夫、亚沃·鲁塞夫、斯特凡·巴卡尔日耶夫、西蒙·康纳、肖恩·罗斯、佩特拉·图斯洛娃、特蕾扎·多布罗夫斯卡、索娜·霍利奇科娃、斯科特·杰克逊、斯坦尼斯拉夫·马尔乔夫斯基、亚娜·里萨夫科娃、拉德科·塞德莱切克、亚尔米拉·什韦多娃、德拉戈姆·加尔博夫、艾玛·雅各布森、罗伊斯·劳伦斯、布里安娜·巴顿、斯蒂芬妮·布莱克、拉克兰·汉利、塞缪尔·莱利、艾萨克·罗伯茨、蒂安娜·安德森、艾米·坦斯韦尔、米凯拉·沃克、布龙温·施拉莫维茨、埃莉萨·辛克莱、安杰尔·博格达诺夫·格里戈罗夫、玛蒂尔德·延森、萨拉·维鲁普、多特·佩德森、朱莉·伦德、乔尔·瑟康贝、马蒂亚斯·卡斯与马蒂亚斯·约翰森。 ## 资助说明 本研究得到澳大利亚研究委员会（Australian Research Council）联动项目资助方案LP0989901、密歇根大学国际合作基金、保加利亚美国基金会、澳大利亚教育部“奋进短期交流计划”（资助编号19686）、国家电子研究协作工具与资源计划（NeCTAR）下的电子研究工具资助RT043、澳大利亚研究委员会（Australian Research Council）联动、基础设施、设备与设施（LIEF）资助LE140100151、麦考瑞大学（Macquarie University）与澳大利亚新南威尔士大学（UNSW Australia）内部基础设施资助计划，以及奥胡斯大学（Aarhus University）研究基金启动项目（编号AUFF-2018-7-22，授予“古代地中海社会复杂性（SDAM）”项目）的支持。