Publications with Fulltext

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6

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Open Access
1899 yılı Osmanlı İmparatorluğu için jeomekansal ve çok modlu bir ulaşım ağı oluşturma denemesi
(Koç University Research Center for Anatolian Civilizations (ANAMED) / Koç Üniversitesi Anadolu Medeniyetleri Araştırma Merkezi (ANAMED), 2020) Gerrits, Piet; Department of History; Kabadayı, Mustafa Erdem; Özkan, Osman; Koçak, Turgay; Faculty Member; Teaching Faculty; Department of History; College of Social Sciences and Humanities; 33267; N/A; N/A
Open Access
A preliminary attempt to construct a geospatial, multimodal Ottoman transport network for 1899
(Koç University Press (KUP) / Koç Üniversitesi Yayınları (KÜY), 2021) Gerrits, Piet; Department of History; Kabadayı, Mustafa Erdem; Özkan, Osman; Koçak, Turgay; Faculty Member; Teaching Faculty; Department of History; College of Social Sciences and Humanities; 33267; N/A; N/A
Open Access
A tribe as an economic actor: the Cihanbeyli tribe and the meat provisioning of İstanbul in the early Tanzimat era
(Cambridge University Press (CUP), 2019) Polatel, Mehmet; Department of History; Köksal, Yonca; Faculty Member; Department of History; College of Social Sciences and Humanities; 53333
This article studies how the Cihanbeyli tribe became a crucial economic actor for the meat supply of Istanbul, by focusing on a conflict between the tribe's leader, Alişan Bey, and the Russian trader David Savalan, which lasted from the 1840s to the 1850s in and around the province of Ankara. Two important processes of the early Tanzimat era had an impact on the Cihanbeyli's role in animal trade. First, as part of the centralization project of the Tanzimat, the Cihanbeyli tribe was sedentarized in the 1840s and 1850s. Second, although the Ottoman state adopted liberal economic policies during the Tanzimat, the provisioning of meat to the imperial capital continued until 1857. Therefore, the article examines the Cihanbeyli's role in the animal trade in the light of these administrative and economic changes. Our findings support the argument that tribes were an integral part of the imperial economy, politics, and society. The dependence of the Ottoman state on the supply of meat by the Cihanbeyli increased significantly from the seventeenth to the mid-nineteenth century. This opposes the conventional view that posits tribes as primordial forms hindering economic and social development in the modernization processes of the nineteenth and twentieth centuries.
Open Access
Agricultural land abandonment in Bulgaria: a long-term remote sensing perspective, 1950–1980
(Multidisciplinary Digital Publishing Institute (MDPI), 2022) Department of History; Kabadayı, Mustafa Erdem; Osgouei, Paria Ettehadi; Sertel, Elif; Faculty Member; Researcher; Researcher; Department of History; College of Social Sciences and Humanities; 33267; N/A; N/A
Agricultural land abandonment is a globally significant threat to the sustenance of economic, ecological, and social balance. Although the driving forces behind it can be multifold and versatile, rural depopulation and urbanization are significant contributors to agricultural land abandonment. In our chosen case study, focusing on two locations, Ruen and Stamboliyski, within the Plovdiv region of Bulgaria, we use aerial photographs and satellite imagery dating from the 1950s until 1980, in connection with official population census data, to assess the magnitude of agricultural abandonment for the first time from a remote sensing perspective. We use multi-modal data obtained from historical aerial and satellite images to accurately identify Land Use Land Cover changes. We suggest using the rubber sheeting method for the geometric correction of multi-modal data obtained from aerial photos and Key Hole missions. Our approach helps with precise sub-pixel alignment of related datasets. We implemented an iterative object-based classification approach to accurately map LULC distribution and quantify spatio-temporal changes from historical panchromatic images, which could be applied to similar images of different geographical regions.
Open Access
An historical geographic information system for Ottoman Studies. The c. 1907 Ottoman Census and Armenian Settlement in Istanbul
(Peeters Online Journals, 2020) Ohanian, Daniel; Başkurt, Z. Mehmet; Department of History; Kabadayı, Mustafa Erdem; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267
The purpose of this article is to announce the publication of a partial transcription of the c. 1907 Ottoman census that relates to 24,000 Apostolic Armenian Istanbulites and of a historical geographic information system (HGIS), or interactive map, that shows where these individuals lived. Within this framework, the authors first present their argument that an unidentified, microfilmed population register housed in New York is the most substantial portion of this census currently available to researchers. In the second part of their article, they introduce HGISes as tools for the digital humanities and describe the process of creating one.
Open Access
Automatic CNN-based Arabic numeral spotting and handwritten digit recognition by using deep transfer learning in Ottoman population registers
(Multidisciplinary Digital Publishing Institute (MDPI), 2020) Department of History; Kabadayı, Mustafa Erdem; Can, Yekta Said; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267; N/A
Historical manuscripts and archival documentation are handwritten texts which are the backbone sources for historical inquiry. Recent developments in the digital humanities field and the need for extracting information from the historical documents have fastened the digitization processes. Cutting edge machine learning methods are applied to extract meaning from these documents. Page segmentation (layout analysis), keyword, number and symbol spotting, handwritten text recognition algorithms are tested on historical documents. For most of the languages, these techniques are widely studied and high performance techniques are developed. However, the properties of Arabic scripts (i.e., diacritics, varying script styles, diacritics, and ligatures) create additional problems for these algorithms and, therefore, the number of research is limited. In this research, we first automatically spotted the Arabic numerals from the very first series of population registers of the Ottoman Empire conducted in the mid-nineteenth century and recognized these numbers. They are important because they held information about the number of households, registered individuals and ages of individuals. We applied a red color filter to separate numerals from the document by taking advantage of the structure of the studied registers (numerals are written in red). We first used a CNN-based segmentation method for spotting these numerals. In the second part, we annotated a local Arabic handwritten digit dataset from the spotted numerals by selecting uni-digit ones and tested the Deep Transfer Learning method from large open Arabic handwritten digit datasets for digit recognition. We achieved promising results for recognizing digits in these historical documents.
Open Access
Automatic detection of road types from the third military mapping survey of Austria-Hungary historical map series with deep convolutional neural networks
(Institute of Electrical and Electronics Engineers (IEEE), 2021) Department of History; Kabadayı, Mustafa Erdem; Can, Yekta Said; Gerrits, Petrus Johannes; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267; N/A; N/A
With the increased amount of digitized historical documents, information extraction from them gains pace. Historical maps contain valuable information about historical, geographical and economic aspects of an era. Retrieving information from historical maps is more challenging than processing modern maps due to lower image quality, degradation of documents and the massive amount of non-annotated digital map archives. Convolutional Neural Networks (CNN) solved many image processing challenges with great success, but they require a vast amount of annotated data. For historical maps, this means an unprecedented scale of manual data entry and annotation. In this study, we first manually annotated the Third Military Mapping Survey of Austria-Hungary historical map series conducted between 1884 and 1918 and made them publicly accessible. We recognized different road types and their pixel-wise positions automatically by using a CNN architecture and achieved promising results.
Open Access
Automatic estimation of age distributions from the first Ottoman Empire population register series by using deep learning
(Multidisciplinary Digital Publishing Institute (MDPI), 2021) Department of History; Kabadayı, Mustafa Erdem; Can, Yekta Said; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267; N/A
Recently, an increasing number of studies have applied deep learning algorithms for extracting information from handwritten historical documents. In order to accomplish that, documents must be divided into smaller parts. Page and line segmentation are vital stages in the Handwritten Text Recognition systems; it directly affects the character segmentation stage, which in turn deter-mines the recognition success. In this study, we first applied deep learning-based layout analysis techniques to detect individuals in the first Ottoman population register series collected between the 1840s and the 1860s. Then, we employed horizontal projection profile-based line segmentation to the demographic information of these detected individuals in these registers. We further trained a CNN model to recognize automatically detected ages of individuals and estimated age distributions of people from these historical documents. Extracting age information from these historical registers is significant because it has enormous potential to revolutionize historical demography of around 20 successor states of the Ottoman Empire or countries of today. We achieved approximately 60% digit accuracy for recognizing the numbers in these registers and estimated the age distribution with Root Mean Square Error 23.61.
Open Access
Automatic road extraction from historical maps using deep learning techniques: a regional case study of Turkey in a German World War II map
(Multidisciplinary Digital Publishing Institute (MDPI), 2021) Sertel, Elif; Department of History; Kabadayı, Mustafa Erdem; Ekim, Burak; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267; N/A
Scanned historical maps are available from different sources in various scales and contents. Automatic geographical feature extraction from these historical maps is an essential task to derive valuable spatial information on the characteristics and distribution of transportation infrastructures and settlements and to conduct quantitative and geometrical analysis. In this research, we used the Deutsche Heereskarte 1:200,000 Türkei (DHK 200 Turkey) maps as the base geoinformation source to construct the past transportation networks using the deep learning approach. Five different road types were digitized and labeled to be used as inputs for the proposed deep learning-based segmentation approach. We adapted U-Net++ and ResneXt50_32×4d architectures to produce multi-class segmentation masks and perform feature extraction to determine various road types accurately. We achieved remarkable results, with 98.73% overall accuracy, 41.99% intersection of union, and 46.61% F1 score values. The proposed method can be implemented in DHK maps of different countries to automatically extract different road types and used for transfer learning of different historical maps.
Open Access
Book review: Kein Griff nach der Weltmacht: Geheime Dienste und Propaganda im deutsch-österreichisch-türkischen Bündnis 1914–1918
(University of Chicago Press, 2014) Department of History; McMeekin, Sean; Faculty Member; Department of History; College of Social Sciences and Humanities
Open Access
Bridging the gap between pre-census and census-era historical data: devising a geo-sampling model to analyse agricultural production in the long run for Southeast Europe, 1840–1897
(Edinburgh University Press, 2020) Gerrits, Piet; Department of History; Kabadayı, Mustafa Erdem; Boykov, Grigor; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267; N/A
This research introduces a novel geo-spatial sampling model to overcome a major difficulty in historical economic geography of Bulgarian lands during a crucial period: immediately before and after the de facto independence of the territory from the Ottoman Empire in the second half of the nineteenth century. At its core it seeks to investigate the research question how the Bulgarian independence affected agricultural production in two regions (centered around the cities of Plovdiv and Ruse) of today's Bulgaria, for which there are conflicting yet empirically unsubstantiated claims concerning the economic impact of the political independence. Using our be-spoke geo-sampling strategy we believe, we have sampled regionally representative commensurable agricultural data from the 1840s Ottoman archival documentation, in accord with agricultural censuses conducted by the nascent nation state of Bulgaria in the 1890s.
Open Access
British workers and Ottoman modernity in nineteenth-century Istanbul
(Cambridge University Press (CUP), 2021) Department of History; Sefer, Akın; Researcher; Department of History; College of Social Sciences and Humanities
In the mid-nineteenth century, when the Ottoman state launched an industrialization campaign within the context of increasing contacts between the Ottoman and British governments, hundreds of British industrial workers migrated to Istanbul to work in Ottoman military factories, along with technology transfer from Britain. This article narrates the history of these workers and of the community they established in Istanbul in a period spanning four decades, from the beginning of the mechanization efforts in the 1830s until the economic crisis in the mid-1870s. Drawing on archival evidence from Ottoman and British sources, it analyzes the larger context of British workers' migration from Britain, their relations with the Ottoman state officials and local workers, and their experiences and struggles in the workplace and the city. Although both British and Ottoman historians have largely ignored their experiences due to their marginal numbers and distinct statuses, these workers actively took part in the Ottoman industrialization process, in the development of capitalist class relations, and in the social, cultural, and spatial transformation of the capital city in the Ottoman age of reforms. By means of this analysis, the article aims to highlight the significance of immigrant workers as actors of the history of large-scale transformations in the late Ottoman Empire as well as underlining the role of trans-imperial labor migration in the history of modernity.
Open Access
CNN-based page segmentation and object classification for counting population in Ottoman archival documentation
(Multidisciplinary Digital Publishing Institute (MDPI), 2020) Department of History; Kabadayı, Mustafa Erdem; Can, Yekta Said; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267; N/A
Historical document analysis systems gain importance with the increasing efforts in the digitalization of archives. Page segmentation and layout analysis are crucial steps for such systems. Errors in these steps will affect the outcome of handwritten text recognition and Optical Character Recognition (OCR) methods, which increase the importance of the page segmentation and layout analysis. Degradation of documents, digitization errors, and varying layout styles are the issues that complicate the segmentation of historical documents. The properties of Arabic scripts such as connected letters, ligatures, diacritics, and different writing styles make it even more challenging to process Arabic script historical documents. In this study, we developed an automatic system for counting registered individuals and assigning them to populated places by using a CNN-based architecture. To evaluate the performance of our system, we created a labeled dataset of registers obtained from the first wave of population registers of the Ottoman Empire held between the 1840s and 1860s. We achieved promising results for classifying different types of objects and counting the individuals and assigning them to populated places.
Open Access
Computerized counting of individuals in Ottoman population registers with deep learning
(Springer, 2020) Department of History; Can, Yekta Said; Kabadayı, Mustafa Erdem; Faculty Member; Department of History; College of Social Sciences and Humanities; N/A; 33267
The digitalization of historical documents continues to gain pace for further processing and extract meanings from these documents. Page segmentation and layout analysis are crucial for historical document analysis systems. Errors in these steps will create difficulties in the information retrieval processes. Degradation of documents, digitization errors and varying layout styles complicate the segmentation of historical documents. The properties of Arabic scripts such as connected letters, ligatures, diacritics and different writing styles make it even more challenging to process Arabic historical documents. In this study, we developed an automatic system for counting registered individuals and assigning them to populated places by using a CNN-based architecture. To evaluate the performance of our system, we created a labeled dataset of registers obtained from the first wave of population registers of the Ottoman Empire held between the 1840s–1860s. We achieved promising results for classifying different types of objects and counting the individuals and assigning them to populated places.
Open Access
Developing an automatic layout analysis system for Ottoman population registers
(Institute of Electrical and Electronics Engineers (IEEE), 2021) Department of History; Can, Yekta Said; Kabadayı, Mustafa Erdem; Faculty Member; Department of History; College of Social Sciences and Humanities; N/A; 33267
For extracting information from the historical documents, digitization efforts have increased dramatically in the recent decades. Accurate layout analysis will help researchers for developing more robust HTR and OCR techniques which will extract meaningful information from these documents. Variable layouts, low quality and distorted images of historical documents create different problems to deal with when compared to modern document processing. Arabic script features have even more problems for these automatic processing systems. In this study, we have developed a tool for automatically analyzing the layouts of the first Ottoman population registers which are written in Arabic script form. We built a dataset for testing the performance of our system which are chosen from the first population records of the Ottoman Empire between the 1840s and 1860s. We successfully classified two different object types in those documents. / Tarihsel belgelerden bilgi çıkarmak için sayısallaştırma çabaları son yıllarda önemli ölçüde artmı ştır. Doğru yerleşim analizi, araştırmacıların bu belgelerden anlamlı bilgiler elde edecek daha sağlam HTR ve OCR teknikleri geliştirmelerine yardımcı olacaktır. Değişken yerleşimler, düşük kaliteli ve bozuk tarihi belgeler, modern belge işlemeye kıyasla farklı sorunlar yaratmaktadır. Arapça yazılar kendine has bazı özelliklerinden dolayı otomatik işlem sistemleri için daha da fazla sorun yaratmaktadır. Bu çalışmada, ilk Osmanlı nüfus kayıtlarının Arap harfleriyle yazılmış yerleşimlerini otomatik olarak analiz etmek için bir araç geliştirdik. 1840’lar ve 1860’lar arasında Osmanlı İmparatorluğu’nun ilk nüfus kayıtlarından seçilen sistemimizin performansını test etmek için bir veri seti oluşturduk. Bu belgelerde iki farklı nesne türünü başarıyla sınıflandırdık.
Open Access
European imperial rule through Ottoman land law: British Cyprus, the Italian Dodecanese and French Mandatory Syria
(Cambridge University Press (CUP), 2022) Department of History; Rappas, Alexis; Faculty Member; Department of History; College of Social Sciences and Humanities; 50773
This paper focuses on the articulation between property, sovereignty, and the construction of new political subjectivities in post-Ottoman provinces. Drawing on the cases of British Cyprus, the Italian Dodecanese, and French Mandatory Syria, it shows that European sovereign claims on these territories were pursued through the perpetuation of Ottoman land laws and the reorganisation of the judicial system responsible for implementing them. Dictated by the enduring legal uncertainty regarding the international status of these three provinces, this peculiar path to imperium did not deter European officials from working towards the ambitious goal of creating a class of individual peasant-proprietors, protected in their rights by colonial courts. Acknowledging the differences between these projects, their mutual influences, as well as their relative failure, the article contends that they nonetheless impel us to envision the transition from “Ottoman” to “European” rule as a gradual, multilayered process, instead of a sudden break.
Open Access
Examining age structure and estimating mortality rates in Ottoman Bursa using Mid-Nineteenth-Century population registers
(Taylor _ Francis, 2021) Department of History; Erünal, Efe; PhD Student; Department of History; Graduate School of Social Sciences and Humanities
This study aims to document the age structure and mortality by age in the Ottoman city of Bursa that served as a politically and commercially significant urban center over centuries. It uses a set of hitherto unexamined Ottoman population registers kept in 1839 and updated until 1842 that provide detailed self-reported data on all male inhabitants regardless of age, including deaths, births, and migration. The study tests the quality of age and mortality data in conjunction with the Coale and Demeny regional model life tables and compares the results to historical demographic studies conducted for European regions. The results point to a demographic structure marked by high birth and death rates and prove promising for extending back the study of Ottoman demographic transition and establishing historical comparison points with the global experience.
Open Access
Feature and information extraction for regions of Southeast Europe from Corona satellite images acquired in 1968
(Society of Photo-optical Instrumentation Engineers (SPIE), 2020) Stratoulias, Dimitris; Department of History; Kabadayı, Mustafa Erdem; Faculty Member; Department of History; College of Social Sciences and Humanities; 33267
The Corona spy programme was a series of reconnaissance satellites which delivered more than 860000 images between 1960 and 1972. Since 1995, the data are declassified and a large historic earth observation archive is made accessible to the scientific community. Despite the large volume of information and the high spatial resolution of the satellite imagery, little has been done in the last 25 years in the context of image processing of this data source, a fact which perhaps can be attributed to the technical difficulties of these primitive images such as the lack of metadata, intense spatial and radiometric distortions, low Signal-to-Noise Ratio (SNR) and a single panchromatic band. Hence, the photogrammetric challenges to extract useful information are paramount. In this study, we present recent developments arising from our efforts to map settlements and agricultural parcels over the Plovdiv region, Bulgaria from a Corona image acquired in 1968. We, overall, present initial findings from the integration of earth observation into the ERC-StG project UrbanOccupationsOETR and evaluate the usability of such primitive images in feature extraction. We compare the areas corresponding to settlements and correlate them with concurrent population census. Based on the findings, we suggest that settlements and agricultural parcels can be mapped from a Corona KH-4B image with fine radiometric quality.
Open Access
Jewish refugees in cyprus and british imperial sovereignty in the eastern mediterranean, 1933–1949
(Taylor _ Francis, 2018) Department of History; Rappas, Alexis; Faculty Member; Department of History; College of Social Sciences and Humanities; 50773
This paper focuses on the use of the British Colony of Cyprus as a clearing ground for Jewish refugees on route to Palestine before, during, and after the Second World War. While acknowledging the historiographical consensus underscoring Cyprus’ renewed strategic importance in the context of British post-Second World War imperial retreat in the East, the article argues that Jewish transmigration revealed new potential uses for the island which in turn contributed to confirm British sovereignty in that possession. Drawing on British and Cypriot sources, the article further shows the transformative impact of Jewish transmigration for Cyprus politics as it induced British authorities, who had established an authoritarian regime in the island in the 1930s, to invoke Cypriot reactions in order to stem the flow of refugees to the island. This paved the way for future policies meant to redefine the relations between rulers and ruled. As the management of refugees coming to Cyprus during the period under scrutiny relied on ever more refined instruments of classification, the paper finally highlights the contribution of Empire to the crafting of official categories to designate people on the move—‘refugees’, ‘illegal immigrants’—which still inform European migration policies.
Open Access
Koyunun olmadığı yerde keçiye Abdurrahman Çelebi derler: Ankara Eyaleti’nde Tiftik Keçisi ekonomisinin zaman-uzamsal analiz denemesi (1889-1905)
(Vehbi Koç Ankara Studies Research Center (VEKAM) / Vehbi Koç Ankara Araştırmaları Uygulama ve Araştırma Merkezi (VEKAM), 2018) Department of History; Çelik, Semih; Department of History; College of Social Sciences and Humanities