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

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

Introduction by OpenMethods Editor: 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.

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.

Approaching Linked Data

Approaching Linked Data

Introduction: Linked Data and Linked Open Data are gaining an increasing interest and application in many fields. A recent experiment conducted in 2018 at Furman University illustrates and discusses some of the challenges from a pedagogical perspective posed by Linked Open Data applied to research in the historical domain.

“Linked Open Data to navigate the Past: using Peripleo in class” by Chiara Palladino describes the exploitation of the search-engine Peripleo in order to reconstruct the past of four archeologically-relevant cities. Many databases, comprising various types of information, have been consulted, and the results, as highlighted in the contribution by Palladino, show both advantages and limitations of a Linked Open Data-oriented approach to historical investigations.

Do humanists need BERT?

Do humanists need BERT?

Introduction: Ted Underwood tests a new language representation model called “Bidirectional Encoder Representations from Transformers” (BERT) and asks if humanists should use it. Due to its high degree of difficulty and its limited success (e.g. in questions of genre detection) he concludes, that this approach will be important in the future but it’s nothing to deal with for humanists at the moment. An important caveat worth reading.

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.

Little package, big dependency

Little package, big dependency

Introduction: The world of R consists of innumerous packages. Most of them have very little download rates because they are limited to certain functions as part of a larger argument. Based on a surprising experience with the small package clipr Matthew Lincoln shares his thoughts about this reception phenomenon especially in the digital humanities.

The Research Software Directory and how it promotes software citation

The Research Software Directory and how it promotes software citation

Introduction: The Research Software Directory of the Netherlands eScience Institute provides easy access to software, source code and its documentation. More importantly, it makes it easy to cite software, which is highly advisable when using software to derive research results. The Research Software Directory positions itself as a platform that eases scientific referencing and reproducibility of software based research—good peer praxis that is still underdeveloped in the humanities. 

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.

Towards Scientific Workflows and Computer Simulation as a Method in Digital Humanities – Digitale Bibliothek – Gesellschaft für Informatik e.V.

Introduction: The explore! project tests computer stimulation and text mining on autobiographic texts as well as the reusability of the approach in literary studies. To facilitate the application of the proposed method in broader context and to new research questions, the text analysis is performed by means of scientific workflows that allow for the documentation, automation, and modularization of the processing steps. By enabling the reuse of proven workflows, the goal of the project is to enhance the efficiency of data analysis in similar projects and further advance collaboration between computer scientists and digital humanists.