Using Historical Maps in Scientific Studies
Applications, Challenges, and Best Practices
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Chapter and Conference Paper
SAND : A Tool for Creating Semantic Descriptions of Tabular Sources
Building semantic descriptions of tables is a vital step in data integration. However, this task is expensive and time-consuming as users often need to examine the table data, its metadata, and ontologies to f...
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Chapter and Conference Paper
A Graph-Based Approach for Inferring Semantic Descriptions of Wikipedia Tables
There are millions of high-quality tables available in Wikipedia. These tables cover many domains and contain useful information. To make use of these tables for data discovery or data integration, we need pre...
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Book
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Chapter
Introduction
Historical maps are fascinating to look at and contain valuable retrospective place information difficult to find elsewhere. However, the full potential of historical maps has not been realized because the use...
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Chapter
Summary and Discussion
This chapter summarizes the book and provides a brief outlook.
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Chapter
Creating Structured, Linked Geographic Data from Historical Maps: Challenges and Trends
Historical geographic data are essential for a variety of studies of cancer and environmental epidemiology, urbanization, and landscape ecology. However, existing data sources typically contain only contempora...
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Chapter and Conference Paper
Building Linked Spatio-Temporal Data from Vectorized Historical Maps
Historical maps provide a rich source of information for researchers in the social and natural sciences. These maps contain detailed documentation of a wide variety of natural and human-made features and their...
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Chapter
Historical Map Applications and Processing Technologies
Digital map processing has been an interest in the computer science and geographic information science communities since the early 1980s. With the increase of available map scans, a variety of researchers in t...
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Chapter
Training Deep Learning Models for Geographic Feature Recognition from Historical Maps
Historical map scans contain valuable information (e.g., historical locations of roads, buildings) enabling the analyses that require long-term historical data of the natural and built environment. Many online...
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Reference Work Entry In depth
Wrapper Maintenance
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Reference Work Entry In depth
Conflation of Geospatial Data
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Chapter and Conference Paper
Lessons Learned in Building Linked Data for the American Art Collaborative
Linked Data has emerged as the preferred method for publishing and sharing cultural heritage data. One of the main challenges for museums is that the defacto standard ontology (CIDOC CRM) is complex and museum...
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Chapter and Conference Paper
A Scalable Approach to Incrementally Building Knowledge Graphs
We work on converting the metadata of 13 American art museums and archives into Linked Data, to be able to integrate and query the resulting data. While there are many good sources of artist data, no single so...
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Living Reference Work Entry In depth
Wrapper Maintenance
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Chapter and Conference Paper
Unsupervised Entity Resolution on Multi-type Graphs
Entity resolution is the task of identifying all mentions that represent the same real-world entity within a knowledge base or across multiple knowledge bases. We address the problem of performing entity resol...
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Chapter and Conference Paper
Efficient Graph-Based Document Similarity
Assessing the relatedness of documents is at the core of many applications such as document retrieval and recommendation. Most similarity approaches operate on word-distribution-based document representations ...
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Chapter and Conference Paper
Semantic Labeling: A Domain-Independent Approach
Semantic labeling is the process of map** attributes in data sources to classes in an ontology and is a necessary step in heterogeneous data integration. Variations in data formats, attribute names and even ...
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Chapter and Conference Paper
Leveraging Linked Data to Discover Semantic Relations Within Data Sources
Map** data to a shared domain ontology is a key step in publishing semantic content on the Web. Most of the work on automatically map** structured and semi-structured sources to ontologies focuses on seman...
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Chapter and Conference Paper
Finding Concept Coverings in Aligning Ontologies of Linked Data
Despite the recent growth in the size of the Linked Data Cloud, the absence of links between the vocabularies of the sources has resulted in heterogenous schemas. Our previous work tried to find conceptual map...
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Chapter and Conference Paper
Karma: A System for Map** Structured Sources into the Semantic Web
The Linked Data cloud contains large amounts of RDF data generated from databases.
