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Madoc as a tool to enrich and analyse sources

Madoc is an open-source tool developed by Digirati for the enrichment of digital objects. The primary building block for content enrichment is the International Image Interoperability Framework (IIIF), an open set of standards for sharing images and their metadata. IIIF is used by over 130 research institutions worldwide, mostly in image repositories, cultural heritage institutions, and research libraries. Participatory enrichment possibilities include annotations, translations, transcriptions, and metadata entry. In Madoc users can assemble digital collections with IIIF objects from multiple archives, libraries and museums and build an interpretative website around them. Another possibility is to run a crowdsourcing project and invite the public, researchers or students to contribute.

Madoc allows users to import IIIF objects, including metadata and the result of Optical Character Recognition (OCR). After data import, enrichment projects can be configured in the backend using a capture model or customizable template to describe entry fields. Capture models can consist of annotations to gather transcriptions, translations, entities, tags, commentaries, or metadata curation. Internal projects can be kept private, while public crowdsourcing projects allow users to participate and contribute after signing in.  Submissions made by the public can easily be reviewed and validated through a user-friendly dashboard. Madoc provides a public digital exhibition space to showcase the enriched collection along with the annotations. The results of a project can also be exported using the Madoc API.

The Ghent Centre for Digital Humanities has invested in Madoc since 2019 through the Flemish consortium CLARIAH-VL. Other investors include the National Library of Wales and the Indigenous Digital Archive. We have been actively involved since the development stage and have ample experience setting up projects.

Documentation

Madoc combines a multitude of functionalities and components, both in the front-end and in the back-end. Therefore, a clear documentation page is indispensable. During CLARIAH-VL, the documentation page was significantly expanded to support developers, project managers and users. The page provides explanations, examples and screenshots, and is linked to the source code on GitHub. There is also a subpage documenting the releases of new features. 

Although the documentation page is not complete, it is a tool to facilitate a wider use of the platform and strengthen the open-source character of Madoc.

Feature development

To make Madoc more user-friendly for both project managers and project participants, a range of functionalities was developed, resulting in the release of Madoc version 2.2 in October 2023. These functionalities were chosen based on comparative research and a user survey, performed in collaboration with Flemish Art Collection, meemoo and Meise Botanic Garden.

  • Polygon selectors

Up until now, the Capture Model Service in Madoc only supported rectangular box selectors to define regions on the image (i.e. IIIF canvas) as the target of an annotation. Because rectangular boxes make certain projects impossible, we added the possibility to draw non-rectangular polygonal regions on the image. Digirati used Scalable Vector Graphics (SVG), following the SVG-standards defined by the World Wide Web Consortium (W3C). This selector enables more detailed annotations in Madoc.

Project participants can add an image to the viewer via a split view. This enables a comparison of different images. The dimensions of the viewer can also be adjusted to make the form more visible.

Project managers can add structured vocabularies themselves, or link to existing vocabularies. By using an auto-complete field, project participants can easily create a connection to vocabularies such as Wikidata.

Instructions for the tasks can be linked to a help button. This allows extensive instructions to be given to the project participant without overloading the form with text.

In addition to a progress bar and an overview of the collections and manifests, every project participant can access an overview of their own contributions, statistics of the other participants and updates from the project team for each project. The project landing page also allows every participant to provide feedback to the project manager(s). To enable quick and efficiënt communication, managers can send an email to all participants of the project with one click.

  • Auto-save

In addition to a ‘save for later’ button, an auto-save can be enabled. In this way, a copy of the contribution is saved to the browser’s local storage every 10 seconds. If desired, the participant can restore the previous version.

The user profile provides an overview of a user’s personal information (name, e-mail address, setting, …) and the tasks they performed. The profile page also allows users to indicate for whom their personal information should be visible.

Project managers can add a page with terms of use to the project site. Each new participant is prompted upon registration to read the terms of use and agree to them. When the terms of use change, every user will be notified. Data on whether or not the terms of use are agreed to are stored and can be used to deny access to certain functionalities.

Ghent Enriched – platform for customized participation

To test and improve the technology, methodology and user experience of Madoc as a participative tool we learned a lot from the project Ghent Enriched (Gent Verrijkt), a spin-off of the cultural heritage project Ghent Mapped (Gent Gemapt) (2020-2023). Through Ghent Enriched, museums and archives offer parts of their collections and ask the public or experts to help transcribe, date, describe and identify them. Heritage partners used Madoc as a customized toolbox for digital and hybrid volunteer work. Moreover, the platform made it possible to set up shared projects with similar collections, and to learn from each other’s capture models.

We first tested the approach and technology in pilot projects. Huis van Alijn, Amsab-ISG and Archief Gent, formulated problem statements around specific collection registration cases. We then translated and implemented these cases via IIIF manifests in a capture model, and embedded the Madoc projects in existing public and volunteer operations. Students worked on the Belgian-Dutch feminist-socialist periodical De Vrouw (Woman; 1893‒1900) from the digital collections of the Belgian Amsab-Institute of Social History. They collaborated to identify all poems (over 200 in total), developed a distinct data model to describe the poems, and each conducted their own case study. An important condition of collection registration cases was to shield copyrighted collections, an advantage of Madoc.

Archief Gent made an open call for volunteers to help date the collection of 3,000 postcards of the Municipal Commission for Monuments and Townscapes (SCMS). These unique pieces contain a lot of interesting information for researchers and folklorists but have yet to be dated. Aside from historical purposes, dating is crucial for clearing copyright and thus making the postcards more accessible. The dating methodology was translated to a capture model taking into account postage and publisher stamps, writing, colours, and lay-out. After a training session on dating methodology in the archive, five volunteers individually worked on the task in Madoc. They could come back two-weekly for feedback from the archivist. 

The Industry Museum uses Madoc to present and describe historical photographs of metalworking at the ACEC-site. (Former) metal workers were asked to identify machines and measuring instruments on photographs from several different companies. During a workshop with seventeen volunteers, three groups worked together with curators to complete the description of this collection and share their expertise.

Erfgoedcel Gent set up a community project to identify people and places on photographs and slides made by amateur photographer Lucien Bogaert between 1960 and 2010. People from neighbourhood de Muide are asked to further describe the collection.

Research Scenario CLARIAH-VL: Mapping flood damages in the past (part I)

Introducing the case of the Belgian Historical Gazetteer

The aim of the CLARIAH-VL Open Humanities Service Infrastructure is to advance digitally-enabled research in Humanities and the Arts by, among other things, providing data-level access to digitized and born-digital resources. In this blogpost series, we will communicate on research scenarios leading to and building upon the datasets made available through CLARIAH-VL. This blogpost introduces the research scenario “Mapping flood damages in the past using the Belgian Historical Gazetteer”. The two following ones will introduce the methodology and the results.

Introduction

Our societies are facing major meteorological disasters because climate changes greatly and because societies are no longer prepared to face them: many people live in risky areas when the risk itself is culturally no longer accepted. Recent research has shown that past societies used to be more resilient towards meteorological bad events (Soens 2018, De Keyzer et al. 2024), at least to the non-exceptional ones. Thinking about the daily resilience of societies to such events in the past means taking stock of past bad weather events: how frequent were they? What were the causes? Which places were the most impacted? This can be difficult because these events have whether not always left much trace in the documentation (because they were common), whether so much trace (because they were numerous) that they are difficult to manage. However, digital tools can help researchers in both cases. They can for instance greatly facilitate the visualization of specific natural disasters by automatizing the mapping of (forgotten) affected places. This research scenario aims at showing how it can be done.

Dataset

For this research scenario, we will focus on one specific source, namely the “Gazet van Antwerpen” which is a daily newspaper published in Flanders since 1891. Among other subjects, this newspaper mentions the occurrences and consequences of bad weather in all Belgium, in other countries but especially in Flanders.  This document had been digitized and is available online from 1911 on BelgicaPress, the online newspaper database of the Royal Library of Belgium (KBR).

Figure 1 – First page of the Gazet van Antwerpen (BelgicaPress)

For this case study, we will look for every mention of the words “onder water” (“under water” in English. Ex: “this hamlet was under water because of the storm”) used in this newspaper from 1911 to 1921. We will select the articles that use this expression in the framework of storms or floods that took place in provinces Antwerp and East-Flanders.

Research Question

For this research scenario, we would like to obtain a visualisation of the damage caused by (non-exceptional) storms and floods in the provinces of Antwerp and East Flanders in order to take measure of these (non-exceptional) events each year between 1911 and 1921. The first step is of course to be able to map places mentioned in those articles. Our research question is therefore: where are the places that were impacted by storms and floods in provinces Antwerp and East-Flanders between 1911 and 1921? and To what extent were they affected ? 

Challenges

The challenges are numerous if one wants to automatize, at least a bit, the working process. The bigger are 1) that information on storms and floods needs to be aggregated into locations, which 2) need to be disambiguated and linked to an existing spatial database for subsequent mapping within a Geographic Information System.

Solutions

This research scenario will make use of the tools provided by SIC 4 (Aggregate) to (semi)automatically map the locations mentioned in the selected newspaper articles.

This includes specifically the Belgian Historical Gazetteer, which is an historical gazetteer of toponyms. Its main goals is to provide researchers with a collection of data that 1) does not stop at Belgian provincial borders, which 2) goes beyond the level of municipalities and 3) that does not stop to the 19th century but go deeper in the past.

Next Steps (and next blogposts)

  • Building the dataset and identifying locations (blogpost part II)
  • Visualizing floods damages (blogpost part III)

References

Tim Soens, 2018. “Resilient Societies, Vulnerable People: Coping with North Sea Floods Before 1800”, Past & Present, 241 (1), 2018 : 143–177, https://doi.org/10.1093/pastj/gty018

Maïka De Keyzer, Tim Soens and Christophe Verbruggen, 2024. Mens en natuur : een geschiedenis, (Gent: Academia Press), 2014, 313p.

Diff Annotator: An Annotation Tool for Text Comparisons

Diff Annotator

Diff Annotator, developed at the University of Antwerp as part of eXtant, a toolkit for digital scholarly editing, is a lightweight tool for annotating text-comparisons of two plain text files. It was initially created for a specific use case, a research project that included a comparative close reading of two versions of Stephen King’s novel IT. It was programmed to facilitate an analysis of the mechanics of suspense throughout King’s revision campaigns during the novel’s composition process.

How Does Diff Annotator Work?

The tool provides a reading environment that presents the variation in a pleasing way and enables users to take notes and attach annotations to variants. As the name suggests, the Diff Annotator uses the ‘git diff’ command from git (an open-source distributed version control system) for the collation process itself. It visualizes invariant text in black and the variants from the first version in red and the second version in green. The collation is accurate, and the output is clear. Equally important to the collation itself, however, is Diff Annotator’s mechanism to note down what one notices in the variants: to make general notes about revision patterns that one might discover along the way and to attach annotations to particular variants, flagging and tallying those patterns.

Technical Specifications and Installation

Diff Annotator’s simple web-based content management system is a lightweight node js application. To add a new text comparison, users can click on the ‘+ NEW DIFF’ button, supply a name for the comparison and then select two plain text files from their computer (other file formats than .txt are not supported, only two versions can be compared). The output generated by git diff is transformed to HTML by a python script that adds unique identifiers to all variants. The adding of notes and annotations is handled by a combination of python scripts (which make the changes to the HTML files) and client-side javascript functions (which update the visualisation in the browser as the user is working).

The automatic collation output can be corrected in three ways:

1) by clicking on a variant and making changes in the text fields marked ‘f1’ (the first text file) and ‘f2’ (the second text file)

2) by clicking the ‘Normalize to f2’ button to remove a variant and insert the variant from f2 as normal text

3) editing the source code by calling up the source HTML of a selection of paragraphs (all variants are contained in a <span class=”app”>, for instance: <span class=”app” id=”app-652″><span class=”f1″>Hello</span><span class=”f2″>Hi</span></span>).

Diff Annotator supplies statistics for every paragraph on the increase or decrease in words between the versions. ‘[inv.:19 — f1:14 — f2:12 (-6.06%)]’, for instance, describes the collation of a paragraph with 19 invariant words, 14 variant words in the first text file, compared to only 12 variant words in the second text file, which comes down to a decrease of 6% in word count between the versions.

Usage and Customization

The intended audience of the Diff Annotator will need moderate technical skills to install it since it has a moderate number of dependencies that must be installed first (git diff, node.js and python). Text comparisons can be easily transported from one installation of the Diff Annotator to another: simply copy the relevant folder from the ‘Diff-Annotator/public/data’ directory to the same directory in another installation.

The tool does not come with a user management system; it is intended to be used as local software on an individual’s computer. But since the application is open source, users are free to add such a feature to it or set it up in such a way that it can be used safely from a shared server. If so desired, a user with a technical background could remove the interactive functionality (adding new text comparisons, adding or changing annotations and notes) and publish the collection of annotated text comparisons on the web.

The source code of this application can be downloaded from:

https://github.com/eXtant-CMG/Diff-Annotator

Bibundina: a Writer’s Library app

The Writer’s Library application “Bibundina”, developed at the University of Antwerp as part of eXtant, a toolkit for digital scholarly editing, aims to provide an environment both to create and to publish an edition of a collection of books and the reading traces in them. In origin, it was created to publish an edition of a writer’s library. It could for instance be used to make an edition of Virginia Woolf’s personal library, or Toni Morrison’s, or James Joyce’s—a digital reconstruction of the books that occupied their shelves. Such an edition can contain not just the bibliographic details of those books, but also focus on the marginalia left in them by the writers, as well as include information about the books’ provenance and when they were read.

Target audience

The project’s target audience consists of people who have an interest in creating such an edition of a library and are looking for a publication environment. The only technical skill users will need is an understanding of XML: to fill up an XML document following a well-documented schema. Bibundina was written as an application in eXist-db, an open-source NoSQL XML database and application platform. Bibundina can be easily installed via eXist’s “package manager” by dropping a compressed version of the app into the dropzone. Included with the eXist installation is eXide, eXist-db’s code editor. Users can edit the Writer’s Library app’s XML files in eXide and immediately see their work visualized in the publication environment. There are just two XML files to edit: a config file in which users can give their edition a name and select which sorting and browsing categories to use, and a file called “library.xml”, the main data file in which to encode the books.

Images

Images of the books can be added. The app accommodates three different ways of incorporating images, including IIIF, which will allow scholars to create editions based on their own research data or on collections of images that have been made available via IIIF at institutions all around the world. In the book view, users can browse through the images of the pages the editor wishes to include, cover and title page, for instance, and all pages with reading traces.

Reading traces

For pages with reading traces, zone numbers appear in the left margin of the image, at the same level as their corresponding trace. Clicking on a zone number will activate two pop-up windows on the right: a cropped picture of the reading trace in question and a text box with a transcription of the reading trace, the marked passage and an extract of the passage in context.

Some admin tools have been embedded into the interface to facilitate the data input. There is a tool to help editors create a new book entry, to extract image links from a IIIF manifest and formats them into the required XML schema, and a tool that assists admins with drawing rectangular zones around reading traces on IIIF images.

Available on GitHub: the source code, the current binary release, the documentation, and the user manual.

https://github.com/eXtant-CMG/writerslibrary

The Belgian Historical Gazetteer: an index of Belgian historical place names to link archival collections and explore landscapes histories

Legend: extracts from various sheets of the ‘reduced cadastre’ (©IGN/NGI)

Gazetteers can help historians with mapping toponyms that appear in the sources they analyse by providing them with lists of historical place names and extra information which can be used to disambiguate the latter, if it happens that several different places share a same name. This is the aim of initiatives such as the World Historical Gazetteer or Pleiades. However, despite their merits, the international scope of these tools impedes the use for regional and local historical research. Historians thus need more suitable gazetteers if they want to work at a more local scale.

CLARIAH-VL aims to fill in this gap for Belgium by launching the project “Belgian Historical Gazetteer” in the framework of its SIC “Enrich”. Started in November 2022, the pilot of this project will last two years, and eventually aims to cover the whole country in the coming years. It is hosted at the University of Antwerp and undertaken in liaison with the Belgian National Geographical Institute (IGN/NGI). The aim of this project is to set up a historical gazetteer of toponyms for the whole present-day territory of Belgium, in order to provide researchers with a collection of data that 1) does not stop at Belgian provincial borders 2) goes beyond the level of municipalities and 3) goes back in time as much as possible.

Pilot test

The first phase of the project (pilot 2022/2024) consists in the gathering of an ancient and geographically homogeneous set of toponyms for provinces Antwerp, East Flanders and Liège. This is done by collecting all the toponyms mentioned on the ‘reduced cadastre’, a reduced version of the primitive cadastre drawn between 1847 and 1855 to prepare the creation of the first topographical map of Belgium in the second half of the 19th century.

Workflow of the ‘reduced cadastre’ (©IGN/NGI)
Workflow of the ‘reduced cadastre’ (©IGN/NGI)

From QGis to Linked Open Data

These toponyms are located by using points in QGis and described via the PostGis extension in a PostgreSQL database whose structure is highly adaptable to every source and compatible with Linked Open Data principles. For each toponym we record not only its name, location, type (as described in the source, and a standardized version of it), but also if applicable its matching number in databases of other projects (for instance the “placename” project of the State Archives, the “Dorpskernen” project for Flemish toponyms), its corresponding Wikidata page if it already exists and its corresponding notice in the book Gemeenten van Belgïe[1], where Hervé Hasquin and his team summarized historical information (notably administrative and ecclesiastical belonging during the Ancien Régime) about municipalities.

The ultimate aim of drawing those links with the existing (notably historical) resources is to provide researchers with sufficient information on each toponyms to facilitate the disambiguation of place names. For instance, if one historian wants to locate a place called “heikant” in the primary source and if it appears that there are several “heikant” in Belgium, it may help him/her to identify the correct one among the latter if he knows in which bishopric each of them belongs in the seventeenth century. Finally, thanks to another table of the database (table “relations”), we also describe elementary relations between the toponyms like the administrative ones (“this hamlet belongs to this town” / “this isolated chapel belongs to this town”).

Future integration and accessibility

At the end of the project, this gazetteer will be published on the World Historical Gazetteer, and will progressively be loaded on Druid (a LOD platform), in order to make it easily reachable for everyone as well as potentially extendable. This gazetteer will enable researchers to easily identify place names they find in their sources, and could be used in the future to automatically ‘map’ (e.g. annotated) written sources to a great extent.

Beyond these very practical benefits, we think that this Belgian gazetteer can also be used to open new perspectives in landscape history by making it possible to follow the evolution of the Belgian landscape through the evolution of toponyms (name and location) on the long-term. This is why, in a second phase (which in practice is ran parallel to the first), we compare the nineteenth century toponyms with present-day ones using the database of the IGN/NGI. By establishing links between ancient and actual toponyms, we can explore how a toponym evolved during the nineteenth and the twentieth century in order to research variations of place names through time. In a third phase, toponyms extracted from older material will be added to the database and the same sort of links will be described, in order to make it possible to follow the evolution of place name on a longer term.


[1] Duvosquel, Jean-Marie, Hervé Hasquin, and Raymond Van Uytven. Gemeenten Van België: Geschiedkundig En Administratief-Geografisch Woordenboek. Bruxelles: La Renaissance du Livre, 1980.

Styloscope and Toposcope: Towards User-Friendly Digital Text Analysis

Natural Language Processing (NLP) has been one of the fastest-growing research fields in the last decade. Innovations such as pre-trained large language models based on transformer neural networks have not only led to the popularization of AI and NLP in the general public, but also to interdisciplinary research projects in the humanities and social sciences facilitated by the scalability of these methods. In this post, we present two tools that aim to facilitate said interdisciplinary research: Styloscope and Toposcope.  The tools were developed in Python and can be used from the command line or from a user interface. The code, detailed installation instructions, and user guidelines can be found on GitHub:

Styloscope

Styloscope is a tool for automatic writing style analysis. It can be used to test hypotheses about large-scale corpora, parse documents, or detect outliers. Users can provide data by either uploading a local file or by using a publicly available Huggingface dataset. When uploading a corpus, the tool accepts CSV files with one document per row, and ZIP folders in which documents are stored in individual text files. The output contains the parsed documents, raw statistics on various writing style features such as syntactic dependencies, lexical richness,  readability, etc., and visualizations of aggregated results. An example for syntactic dependencies is provided below:

Toposcope

Toposcope can be used to detect topics in unstructured text data. It provides annotations and visualizations of the detected topics, including (changes in) topic frequency over time. The tool features four algorithms: BERTopic (Grootendorst, 2022), Top2Vec (Angelov, 2020), Non-negative Matrix Factorization (Choo et al., 2013), and Latent Dirichlet Allocation (Blei et al., 2003). Users can modify a selection of topic model parameters, and apply a number of built-in preprocessing steps, such as lemmatization and stopword removal. The input format is identical to the Styloscope format: users can upload a local corpus (CSV/ZIP), or use a Huggingface dataset. The output includes visualizations of the topic-document clusters (as shown below) and the most important keywords per topic. The raw results, among other things, consist of annotations, a topic-document matrix, and a topic-term matrix. Topic diversity and topic coherence are also computed in order to support the user during the evaluation of the tool.

How to cite

Jens Lemmens and Walter Daelemans. 2024. Styloscope and Toposcope: Towards user-friendly digital text analysis. CLiPS Technical Report Series (CTRS): 10. https://www.uantwerpen.be/en/research-groups/clips/research/computational-linguistics/compling-resources/clips-technical-repo/

References

  • Dimo Angelov. 2020. Top2Vec: Distributed representation of topics. arXiv:2008.09470.
  • David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent dirichlet allocation. Journal of Machine Learning Research, vol. 3, pp. 993—1022.
  • Jaegul Choo, Changhyun Lee, Chandan K. Reddy and Haesun Park. 2013. Utopian: User-driven topic modeling based on interactive nonnegative matrix factorization. IEEE Transactions on Visualization and Computer Graphics, vol. 19 (12), pp. 1992—2001. Institute of Electrical and Electronics Engineers (IEEE).
  • Maarten Grootendorst. 2022. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv:2203.05794.

CLARIAH-VL SIC 5 tool descriptions

A CLARIAH-VL supported data management system: nodegoat

Information on people, places, and things are related to each other in different ways. There are countless ways we can infer these relations which are research question and source dependent. There are also many ways to store this information as data. The nodegoat platform is an object oriented relational web-based data management system which also provides network and geospatial visualizations in one platform. It has the availability to develop custom data models, and then collaborate on this data and later generate visualizations and export data. Within CLARIAH-VL nodegoat is used to store, organize, maintain and analyze relational data. Below you can find the cases where the platform is currently or has been used.

To support researchers in their use of such data, CLARIAH-VL & GhentCDH are hosting 2 nodegoat workshops. In the workshop you will learn how to use this platform for your research. The workshops will be held in two parts on the same day:

1) beginners

2) advanced users (users that already are using nodegoat or have setup an instance).

The workshops, given by the developers of the platform – Lab1100, will be held on 16 November from 10 – 12h & 14 – 16h respectively at Ghent University. Both workshops will be given in English, but questions may be asked in Dutch. The exact location will be confirmed two weeks before the location to registered participants. Please register here: https://event.ugent.be/registration/nodegoat.

An example of the nodegoat instance, as used in the TIC Collaborative project. This network represents a social visualisation of people and conferences.

To get an idea of how nodegoat can be used in research, see this list of the use cases, all projects supported by GhentCDH (CLARIAH-VL):

Discover Ghent through historical maps: unveiling the past with Gent Gemapt

Our partners from the Ghent Centre for Digital Humanities are proud to present their newest project: Ghent Mapped. The digital city map ‘Gent Gemapt’ stacks 20 historical maps and connects them to 4,000 places and 10,000 pieces of heritage. Collections and history that over time have become dispersed among museums, libraries, archives, associations and living rooms, come together again virtually. Reunited, they offer a multifaceted view of the city and its past. Go explore for yourself via gentgemapt.be and discover Ghent layer by layer, from the Middle Ages to today.

The cultural heritage project Gent Gemapt is a collaboration of Ghent University LibrarySTAM – Stadsmuseum GentHuis van AlijnIndustriemuseumArchief GentAmsab-Institute for Social HistoryLiberas and Erfgoedcel Gent. It was developed and coordinated by the Ghent Centre for Digital Humanities at Ghent University, with support from CLARIAH-VL.

Example of the enriched map of Ghent Mapped

Want to know more?

  1. De Kaart” is the core of Ghent Gemapt. It is an innovative presentation platform that spatially unlocks the splendor of Ghent’s heritage collections. It allows you to search, zoom and scroll through time and space of the city.
  2. Gent Verrijkt” stands next to De Kaart and is the digital toolbox of Gent Gemapt. Here, museums and archives enlist the help of volunteers to help transcribe, date, describe and identify their collections.
  3. With the project, the heritage partners are innovating in digital technology. Gent Gemapt uses open source technology Omeka SMadocIIIF (International Image Interoperability Framework), Linked Open Data, and a new Ghent place register.
  4. Gent Gemapt is funded through a project grant from the Department of Culture, Youth and Media of the Flemish Government and through Clariah-Vlaanderen.
  5. After this launch, Gent Gemapt continues to grow and the partners continue to build on the heritage presentation and enrichment via GentGemapt.be.
  6. Read About Gent Gemapt and About the project.

Launch of DigHimapper, a platform to analyse historical maps via georeferencing and annotating

CLARIAH-VL is proud to announce the release of DigHimapper, a platform to analyse historical maps via georeferencing and annotating. It involves the public in two important steps in the processing of historical maps into analysable sources of information to make it possible to visualise landscape evolutions and search maps for place names.

  • In the Georeferencing portal, historical maps are placed as closely as possible to their current state. This is done by looking for points that can be found on both a historical map and in the current landscape. By repositioning the maps, it becomes possible to compare them directly with the present, as well as with other historical maps, thus visualising landscape evolutions.
  • In the Annotation portal, place names (toponyms) on historical maps are converted into text that can be read by computers. Combined with the repositioning of the map itself, these toponyms are given a place in space. Since toponyms often contain a wealth of information about past landscapes, this provides an indispensable resource for studying landscape evolution.

The collection

Central to a first phase of the development of this platform are the magnificent maps of the Arenberg family, which can be found in the General State Archives. The Arenberg family had possessions all over Europe, but mainly in the Low Countries. The collection has now been scanned at high quality and totals some 4,000 maps, ranging from parcel maps of villages to world maps.

An example of georeferencing in the Allmaps Editor

Contribute as a volunteer yourself!

Refine existing georeferences or get to work on toponyms. The results will be used for scientific research on past landscapes, making digital historical maps better available and as a test case to expand the platform with more functions and a multitude of historical maps. Go to the DigHimapper website and you can get started right away!

Contact: dighimaps@uantwerpen.be

DigHimapper is a collaboration between the University of Antwerp, the State Archives of Belgium, Webmapper and Bert Spaan. The project is funded by the Special Research Fund of the University of Antwerp and CLARIAH-VL. The original historical maps were transferred by the Arenberg Foundation to the State Archives of Belgium, which was responsible for scanning them. DigHimapper is also part of the FED-tWIN DigHimaps, a project collaboration between the University of Antwerp and the State Archives of Belgium, funded by BELSPO.