15 research outputs found
Geospatial Analysis and Modeling of Textual Descriptions of Pre-modern Geography
Get PDFTextual descriptions of pre-modern geography offer a different view of classical geography. The descriptions have been produced when none of the modern geographical concepts and tools were available. In this dissertation, we study pre-modern geography by primarily finding the existing structures of the descriptions and different cases of geographical data. We first explain four major
geographical cases in pre-modern Arabic sources: gazetteer, administrative hierarchies, routes, and toponyms associated with people. Focusing on hierarchical divisions and routes, we offer approaches for manual annotation of administrative hierarchies and route sections as well as a semi-automated toponyms annotation. The latter starts with a fuzzy search of toponyms from an authority list and applies two different extrapolation models to infer true or false values, based on the context, for disambiguating the automatically annotated toponyms. Having the annotated data, we introduce mathematical models to shape and visualize regions based on the description of administrative hierarchies. Moreover, we offer models for comparing
hierarchical divisions and route networks from different sources. We also suggest approaches to approximate geographical coordinates for places that do not have geographical coordinates - we call them unknown places - which is a major issue in visualization of pre-modern places on map.
The final chapter of the dissertation introduces the new version of al-Ṯurayyā, a gazetteer and a spatial model of the classical Islamic world using georeferenced data of a pre-modern atlas with more than 2, 000 toponyms and routes. It offers search, path finding, and flood network functionalities as well as visualizations of regions using one of the models that we describe for regions. However the gazetteer is designed using the classical Islamic world data, the spatial model and features can be used for similarly prepared datasets.:1 Introduction 1
2 Related Work 8
2.1 GIS 8
2.2 NLP, Georeferencing, Geoparsing, Annotation 10
2.3 Gazetteer 15
2.4 Modeling 17
3 Classical Geographical Cases 20
3.1 Gazetteer 21
3.2 Routes and Travelogues 22
3.3 Administrative Hierarchy 24
3.4 Geographical Aspects of Biographical Data 25
4 Annotation and Extraction 27
4.1 Annotation 29
4.1.1 Manual Annotation of Geographical Texts 29
4.1.1.1 Administrative Hierarchy 30
4.1.1.2 Routes and Travelogues 32
4.1.2 Semi-Automatic Toponym Annotation 34
4.1.2.1 The Annotation Process 35
4.1.2.2 Extrapolation Models 37
4.1.2.2.1 Frequency of Toponymic N-grams 37
4.1.2.2.2 Co-occurrence Frequencies 38
4.1.2.2.3 A Supervised ML Approach 40
4.1.2.3 Summary 45
4.2 Data Extraction and Structures 45
4.2.1 Administrative Hierarchy 45
4.2.2 Routes and Distances 49
5 Modeling Geographical Data 51
5.1 Mathematical Models for Administrative Hierarchies 52
5.1.1 Sample Data 53
5.1.2 Quadtree 56
5.1.3 Voronoi Diagram 58
5.1.4 Voronoi Clippings 62
5.1.4.1 Convex Hull 62
5.1.4.2 Concave Hull 63
5.1.5 Convex Hulls 65
5.1.6 Concave Hulls 67
5.1.7 Route Network 69
5.1.8 Summary of Models for Administrative Hierarchy 69
5.2 Comparison Models 71
5.2.1 Hierarchical Data 71
5.2.1.1 Test Data 73
5.2.2 Route Networks 76
5.2.2.1 Post-processing 81
5.2.2.2 Applications 82
5.3 Unknown Places 84
6 Al-Ṯurayyā 89
6.1 Introducing al-Ṯurayyā 90
6.2 Gazetteer 90
6.3 Spatial Model 91
6.3.1 Provinces and Administrative Divisions 93
6.3.2 Pathfinding and Itineraries 93
6.3.3 Flood Network 96
6.3.4 Path Alignment Tool 97
6.3.5 Data Structure 99
6.3.5.1 Places 100
6.3.5.2 Routes and Distances 100
7 Conclusions and Further Work 10
Psychometric Properties and Correlates of Precarious Manhood Beliefs in 62 Nations
Get PDFPrecarious manhood beliefs portray manhood, relative to womanhood, as a social status that is hard to earn, easy to lose, and proven via public action. Here, we present cross-cultural data on a brief measure of precarious manhood beliefs (the Precarious Manhood Beliefs scale [PMB]) that covaries meaningfully with other cross-culturally validated gender ideologies and with country-level indices of gender equality and human development. Using data from university samples in 62 countries across 13 world regions (N = 33,417), we demonstrate: (1) the psychometric isomorphism of the PMB (i.e., its comparability in meaning and statistical properties across the individual and country levels); (2) the PMB’s distinctness from, and associations with, ambivalent sexism and ambivalence toward men; and (3) associations of the PMB with nation-level gender equality and human development. Findings are discussed in terms of their statistical and theoretical implications for understanding widely-held beliefs about the precariousness of the male gender role
Geospatial Analysis and Modeling of Textual Descriptions of Pre-modern Geography
No full textTextual descriptions of pre-modern geography offer a different view of classical geography. The descriptions have been produced when none of the modern geographical concepts and tools were available. In this dissertation, we study pre-modern geography by primarily finding the existing structures of the descriptions and different cases of geographical data. We first explain four major
geographical cases in pre-modern Arabic sources: gazetteer, administrative hierarchies, routes, and toponyms associated with people. Focusing on hierarchical divisions and routes, we offer approaches for manual annotation of administrative hierarchies and route sections as well as a semi-automated toponyms annotation. The latter starts with a fuzzy search of toponyms from an authority list and applies two different extrapolation models to infer true or false values, based on the context, for disambiguating the automatically annotated toponyms. Having the annotated data, we introduce mathematical models to shape and visualize regions based on the description of administrative hierarchies. Moreover, we offer models for comparing
hierarchical divisions and route networks from different sources. We also suggest approaches to approximate geographical coordinates for places that do not have geographical coordinates - we call them unknown places - which is a major issue in visualization of pre-modern places on map.
The final chapter of the dissertation introduces the new version of al-Ṯurayyā, a gazetteer and a spatial model of the classical Islamic world using georeferenced data of a pre-modern atlas with more than 2, 000 toponyms and routes. It offers search, path finding, and flood network functionalities as well as visualizations of regions using one of the models that we describe for regions. However the gazetteer is designed using the classical Islamic world data, the spatial model and features can be used for similarly prepared datasets.:1 Introduction 1
2 Related Work 8
2.1 GIS 8
2.2 NLP, Georeferencing, Geoparsing, Annotation 10
2.3 Gazetteer 15
2.4 Modeling 17
3 Classical Geographical Cases 20
3.1 Gazetteer 21
3.2 Routes and Travelogues 22
3.3 Administrative Hierarchy 24
3.4 Geographical Aspects of Biographical Data 25
4 Annotation and Extraction 27
4.1 Annotation 29
4.1.1 Manual Annotation of Geographical Texts 29
4.1.1.1 Administrative Hierarchy 30
4.1.1.2 Routes and Travelogues 32
4.1.2 Semi-Automatic Toponym Annotation 34
4.1.2.1 The Annotation Process 35
4.1.2.2 Extrapolation Models 37
4.1.2.2.1 Frequency of Toponymic N-grams 37
4.1.2.2.2 Co-occurrence Frequencies 38
4.1.2.2.3 A Supervised ML Approach 40
4.1.2.3 Summary 45
4.2 Data Extraction and Structures 45
4.2.1 Administrative Hierarchy 45
4.2.2 Routes and Distances 49
5 Modeling Geographical Data 51
5.1 Mathematical Models for Administrative Hierarchies 52
5.1.1 Sample Data 53
5.1.2 Quadtree 56
5.1.3 Voronoi Diagram 58
5.1.4 Voronoi Clippings 62
5.1.4.1 Convex Hull 62
5.1.4.2 Concave Hull 63
5.1.5 Convex Hulls 65
5.1.6 Concave Hulls 67
5.1.7 Route Network 69
5.1.8 Summary of Models for Administrative Hierarchy 69
5.2 Comparison Models 71
5.2.1 Hierarchical Data 71
5.2.1.1 Test Data 73
5.2.2 Route Networks 76
5.2.2.1 Post-processing 81
5.2.2.2 Applications 82
5.3 Unknown Places 84
6 Al-Ṯurayyā 89
6.1 Introducing al-Ṯurayyā 90
6.2 Gazetteer 90
6.3 Spatial Model 91
6.3.1 Provinces and Administrative Divisions 93
6.3.2 Pathfinding and Itineraries 93
6.3.3 Flood Network 96
6.3.4 Path Alignment Tool 97
6.3.5 Data Structure 99
6.3.5.1 Places 100
6.3.5.2 Routes and Distances 100
7 Conclusions and Further Work 10
Geospatial Analysis and Modeling of Textual Descriptions of Pre-modern Geography
No full textTextual descriptions of pre-modern geography offer a different view of classical geography. The descriptions have been produced when none of the modern geographical concepts and tools were available. In this dissertation, we study pre-modern geography by primarily finding the existing structures of the descriptions and different cases of geographical data. We first explain four major
geographical cases in pre-modern Arabic sources: gazetteer, administrative hierarchies, routes, and toponyms associated with people. Focusing on hierarchical divisions and routes, we offer approaches for manual annotation of administrative hierarchies and route sections as well as a semi-automated toponyms annotation. The latter starts with a fuzzy search of toponyms from an authority list and applies two different extrapolation models to infer true or false values, based on the context, for disambiguating the automatically annotated toponyms. Having the annotated data, we introduce mathematical models to shape and visualize regions based on the description of administrative hierarchies. Moreover, we offer models for comparing
hierarchical divisions and route networks from different sources. We also suggest approaches to approximate geographical coordinates for places that do not have geographical coordinates - we call them unknown places - which is a major issue in visualization of pre-modern places on map.
The final chapter of the dissertation introduces the new version of al-Ṯurayyā, a gazetteer and a spatial model of the classical Islamic world using georeferenced data of a pre-modern atlas with more than 2, 000 toponyms and routes. It offers search, path finding, and flood network functionalities as well as visualizations of regions using one of the models that we describe for regions. However the gazetteer is designed using the classical Islamic world data, the spatial model and features can be used for similarly prepared datasets.:1 Introduction 1
2 Related Work 8
2.1 GIS 8
2.2 NLP, Georeferencing, Geoparsing, Annotation 10
2.3 Gazetteer 15
2.4 Modeling 17
3 Classical Geographical Cases 20
3.1 Gazetteer 21
3.2 Routes and Travelogues 22
3.3 Administrative Hierarchy 24
3.4 Geographical Aspects of Biographical Data 25
4 Annotation and Extraction 27
4.1 Annotation 29
4.1.1 Manual Annotation of Geographical Texts 29
4.1.1.1 Administrative Hierarchy 30
4.1.1.2 Routes and Travelogues 32
4.1.2 Semi-Automatic Toponym Annotation 34
4.1.2.1 The Annotation Process 35
4.1.2.2 Extrapolation Models 37
4.1.2.2.1 Frequency of Toponymic N-grams 37
4.1.2.2.2 Co-occurrence Frequencies 38
4.1.2.2.3 A Supervised ML Approach 40
4.1.2.3 Summary 45
4.2 Data Extraction and Structures 45
4.2.1 Administrative Hierarchy 45
4.2.2 Routes and Distances 49
5 Modeling Geographical Data 51
5.1 Mathematical Models for Administrative Hierarchies 52
5.1.1 Sample Data 53
5.1.2 Quadtree 56
5.1.3 Voronoi Diagram 58
5.1.4 Voronoi Clippings 62
5.1.4.1 Convex Hull 62
5.1.4.2 Concave Hull 63
5.1.5 Convex Hulls 65
5.1.6 Concave Hulls 67
5.1.7 Route Network 69
5.1.8 Summary of Models for Administrative Hierarchy 69
5.2 Comparison Models 71
5.2.1 Hierarchical Data 71
5.2.1.1 Test Data 73
5.2.2 Route Networks 76
5.2.2.1 Post-processing 81
5.2.2.2 Applications 82
5.3 Unknown Places 84
6 Al-Ṯurayyā 89
6.1 Introducing al-Ṯurayyā 90
6.2 Gazetteer 90
6.3 Spatial Model 91
6.3.1 Provinces and Administrative Divisions 93
6.3.2 Pathfinding and Itineraries 93
6.3.3 Flood Network 96
6.3.4 Path Alignment Tool 97
6.3.5 Data Structure 99
6.3.5.1 Places 100
6.3.5.2 Routes and Distances 100
7 Conclusions and Further Work 10
Premodern Geographical Description: Data Retrieval and Identification
No full textGeographical and spatial descriptions in the premodern world are structurally different from the modern era, where spatial understanding is based on cartographic navigation. This paper presents an experimental process to tag, retrieve, and identify geographical information as described in premodern primary sources, together with the issues and possible solutions. The proposed method defines specific categories of geographical information and a markdown system to mark these categories in the source. Having tagged the data, we extract it and geographical locations and their connections are identified through a heuristic approach: the extracted geographical entities are initially aligned with existing geographical references and secondary sources. String similarity approaches might provide fuzzy identifications which need to be verified and disambiguated. In this paper, we describe the process of annotation and extraction of geographical descriptions, experiment some toponyms matching metrics, report the results, and offer possible solutions to handle disambiguation through the existing contextual information in the source. The process is applied to two different datasets, proposed as test cases: a classical Arabic geographical text and a Roman itinerary
Open Islamicate Texts Initiative: a Machine-Readable Corpus of Texts Produced the Premodern Islamicate World
No full textAbstract and poster of paper 0838 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019
OpenITI: a Machine-Readable Corpus of Islamicate Texts
No full textCo-PIs: Matthew Thomas Miller (University of Maryland, College Park), Maxim G. Romanov (University of Vienna), Sarah Bowen Savant (Aga Khan University—ISMC, London).
Open Islamicate Texts Initiative (OpenITI, see https://iti-corpus.github.io/) is a multi-institutional effort to construct the first machine-actionable scholarly corpus of premodern Islamicate texts. Led by researchers at the Aga Khan University, Institute for the Study of Muslim Civilisations (AKU-ISMC), University of Vienna (UV), Leipzig University (LU), and the Roshan Institute for Persian Studies at the University of Maryland (College Park) and an interdisciplinary advisory board of leading digital humanists and Islamic, Persian, and Arabic studies scholars, OpenITI aims to provide the essential textual infrastructure in Arabic, Persian and other Islamicate languages for new forms of textual analysis and digital scholarship. In the process, OpenITI will enable new synergies between Digital Humanities and the inter-related Islamicate fields of Islamic, Persian, and Arabic Studies. In addition to support from the researchers’ home institutions, it is supported by funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme, awarded to the KITAB project (Grant Agreement No. 772989, PI Sarah Bowen Savant) and the Qatar National Library.
Currently, OpenITI contains almost exclusively Arabic texts, which were first assembled into a corpus within the OpenArabic project, developed first at Tufts University (at The Perseus Project, 2013–2015) and then at Leipzig University (at the Alexander von Humboldt Chair for Digital Humanities, 2015–2017)—in both cases with the support and under the patronage of Prof. Gregory Crane. The much more limited number of Persian texts were compiled during 2015–2016 in the Persian Digital Library (PDL) pilot (see Persian Digital Library by PersDigUMD) at Roshan Institute for Persian Studies at the University of Maryland. These texts have not been made fully compatible with OpenITI mARkdown yet and will be made fully available in next releases.
Note on Release Numbering: Version 2019.1.1—where 2019 is the year of the release, the first dotted number—.1—is the ordinal release number in 2019, and the second dotted number—.1—is the overall release number; the first dotted number will reset every year, while the second one will continue on increasing.
For more details: https://github.com/OpenITI/RELEAS
