Category: Capture

Capture generally refers to the activity of creating digital surrogates of existing cultural artefacts, or expressing existing artifacts in a digital representation (digitization). This could be a manual process (as in Transcribing) or an automated procedure (as in Imaging or DataRecognition). Such capture precedes Enrichment and Analysis, at least from a systematic point of view, if not in practice.

RAWGraphs: A Visualization Platform to Create Open Outputs

RAWGraphs: A Visualization Platform to Create Open Outputs

The paper illustrates the features of the innovative tool in the field of data visualization: it is the framework RAW Graphs, available in an open access format at the website https://rawgraphs.io/. The framework permits to establish a connection between data coming from various applications (from Microsoft Excel to Google Spreadsheets) and their visualization in several layouts.

As detailed in the video guide available in the ‘Learning section’ (https://rawgraphs.io/learning), it is possible to load own data through a simple ‘copy and past’ command, and then select a chart-based layout among those provided: contour plot, beeswarm plot, hexagonal binnings, scatterplot, treemap, bump chart, Gantt chart, multiple pie charts, alluvial diagram and barchart. The platform permits also to unstack data according to a wide and a narrow format.

RAWGraphs, ideal for those working in the field of design but not only, is kept as an open-source resource thanks to an Indiegogo crowdfunding campaign (https://rawgraphs.io/blog).
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Mining ethnicity: Discourse-driven topic modelling of immigrant discourses in the USA, 1898–1920

Mining ethnicity: Discourse-driven topic modelling of immigrant discourses in the USA, 1898–1920

Introduction: The article illustrates the application of a ‘discourse-driven topic modeling’ (DDTM) to the analysis of the corpus ChronicItaly comprising several newspapers in Italian language, appeared in the USA during the time of massive migration towards America between the end of the XIX century and the first two decades of the XX (1898-1920).

The method combines both Text Modelling (™) and the discourse-historical approach (DHA) in order to get a more comprehensive representation of the ethnocultural and linguistic identity of the Italian group of migrants in the historical American context in crucial periods of time like that immediately preceding the eruption and that of the unfolding of World War I.

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Web Scraping with Python for Beginners | The Digital Orientalist

Web Scraping with Python for Beginners | The Digital Orientalist

Introduction: In this blog post, James Harry Morris introduces the method of web scraping. Step by step from the installation of the packages, readers are explained how they can extract relevant data from websites using only the Python programming language and convert it into a plain text file. Each step is presented transparently and comprehensibly, so that this article is a prime example of OpenMethods and gives readers the equipment they need to work with huge amounts of data that would no longer be possible manually.

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Diseño de corpus literario para análisis cuantitativos

Diseño de corpus literario para análisis cuantitativos

Introduction: In this article, José Calvo Tello offers a methodological guide on data curation for creating literary corpus for quantitative analysis. This brief tutorial covers all stages of the curation and creation process and guides the reader towards practical cases from Hispanic literature. The author deals with every single step in the creation of a literary corpus for quantitative analysis: from digitization, metadata, automatic processes for cleaning and mining the texts, to licenses, publishing and achiving/long term preservation.

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Document ALL the things!| The Center for Digital Humanities at Princeton

Document ALL the things!| The Center for Digital Humanities at Princeton

Introduction: Sustainability questions such as how to maintain digital project outputs after the funding period, or how to keep aging code and infrastructure that are important for our research up-to-date are among the major challenges DH projects are facing today. This post gives us a sneak peek into the solutions and working practices from the Center for Digital Humanities at Princeton. In their approach to build capacity for sustaining DH projects and preserve access to data and software, they view projects as collaborative and process-based scholarship. Therefore, their focus is on implementing project management workflows and documentation tools that can be flexibly applied to projects of different scopes and sizes and also allow for further refinement in due case. By sharing these resources together with their real-life use cases in DH projects, their aim is to benefit other scholarly communities and sustain a broader conversation about these tricky issues.

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Exploring internet with Hyphe

Exploring internet with Hyphe

Introduction: Given in French by Mathieu Jacomy – also known for his work on Gephi, this seminar presentation gives a substantial introduction to Hyphe, an open-source web crawler designed by a team of the Sciences Po Medialab in Paris. Specifically devised for the researchers’ use, Hyphe helps collecting and curating a corpus of web pages, through an easy to handle interface. 

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Analyzing Documents with TF-IDF | Programming Historian

Analyzing Documents with TF-IDF | Programming Historian

Introduction: The indispensable Programming Historian comes with an introduction to Term Frequency – Inverse Document Frequency (tf-idf) provided by Matthew J. Lavin. The procedure, concerned with specificity of terms in a document, has its origins in information retrieval, but can be applied as an exploratory tool, finding textual similarity, or as a pre-processing tool for machine learning. It is therefore not only useful for textual scholars, but also for historians working with large collections of text.

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Evaluating named entity recognition tools for extracting social networks from novels

Evaluating named entity recognition tools for extracting social networks from novels

Introduction: Named Entity Recognition (NER) is used to identify textual elements that gives things a name. In this study, four different NER tools are evaluated using a corpus of modern and classic fantasy or science fiction novels. Since NER tools have been created for the news domain, it is interesting to see how they perform in a totally different domain. The article comes with a very detailed methodological part and the accompanying dataset is also made available.

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The Uncanny Valley and the Ghost in the Machine

The Uncanny Valley and the Ghost in the Machine

Introduction: There is a postulated level of anthropomorphism where people feel uncanny about the appearance of a robot. But what happens if digital facsimiles and online editions become nigh indistinguishable from the real, yet materially remaining so vastly different? How do we ethically provide access to the digital object without creating a blindspot and neglect for the real thing. A question that keeps digital librarian Dot Porter awake and which she ponders in this thoughtful contribution.

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From Hermeneutics to Data to Networks: Data Extraction and Network Visualization of Historical Sources

From Hermeneutics to Data to Networks: Data Extraction and Network Visualization of Historical Sources

Introduction: This lesson by Marten Düring from the “Programming Historian-Website” gently introduces novices to the topic to Network Visualisation of Historical Sources. As a case study it covers not only the general advantages of network visualisation for humanists but also a step-by-step explanation of the process from extraction of the data until the visualization (using the Palladio-tool). This lesson has also been translated into Spanish and includes many useful references for further reading.

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