Photograph of the staff of the International Institute of Bibliography, writing and classifying records

One of the most obvious questions to start with when working with structured data in the humanities is: what is data? Miriam Posner has captured this challenge in the title of her talk on this topic: 'Humanities Data: A Necessary Contradiction'. Oftentimes, scholars think about their research material in terms of nuances, vagueness, uniqueness, whereas data is perceived as binary, strict and repetitive. The realisation that nuances, vagueness, and uniqueness can also be captured by data in a database is something that has to grow over time.

As soon as we start talk about 'data' it is important to keep two things in mind. First, we should be ready to reflect on the fact that data oriented processes can dehumanise data. This process has been described by Scott Weingart in his essay on digitising and storing holocaust survivor stories. Even though we can efficiently organise large collections of data, the implications of this process have to be taken into account.[....]

Manuscripts and Archives Division, The New York Public Library. Room 100, including card catalogs

At a certain moment in your research process, you might decide that you need to order your material in a structured format. A reason could be that there are too many different people in your body of research and it's becoming hard to keep track of them, let alone their different attributes. Another reason could be that you have repetitive sources, like letters or books, that you want to store and include in your analysis.

In the old days, you would get yourself a card catalogue and start reworking your notes onto these little handy cards.[....]

Every bit of information that is entered into nodegoat can immediately be published through a public user interface. This allows the Encyclopedia of Romantic Nationalism in Europe to instantly publish articles and a wide range of research data. This data also includes a set of over 38.000 letters that can be queried through the public user interface. In this blogpost we discuss the steps we took to allow visitors to dynamically explore this dataset.

The Study Platform on Interlocking Nationalisms (SPIN) at the University of Amsterdam has created a dataset of metadata of over 38.000 letters of nineteenth century intellectuals. This data has been manually entered and imported semi-automatically (geo-referencing and disambiguating people was largely done by hand). Sources include a range of publications of letters, like Breve fra og til Carl Christian Rafn, med en biographi, plus two existing datasets: (1) the metadata of over 18.000 letters of Jacob and Wilhelm Grimm were provided by the Arbeitsstelle Grimm-Briefwechsel Berlin, and (2) the metadata of over 14.000 letters of Sir Walter Scott were provided by the Millgate Union Catalogue of W. Scott Correspondence; courtesy prof. Millgate & National Library of Scotland. The remaining 6.000 letters were entered by hand by SPIN, based on publications of letters of various other intellectuals throughout Europe. This means that the dataset is a combination of a number of personal networks and that we have an overrepresentation of letters sent by the people at the center of these personal networks.

This dataset is part of the Encyclopedia of Romantic Nationalism in Europe (ERNiE). ERNiE will include over 1.500 articles on topics and people associated with the era of romantic nationalism (e.g. Dress, design : Romanian, Karadžić, Vuk Stefanović, Felicia Hemans). ERNiE also includes other materials like monuments, architecture, art, and currency. ERNiE is coordinated by SPIN. The editor of ERNiE is Joep Leerssen.[....]

Next week there will be a nodegoat workshop at the 'DARIAH-EU Annual Meeting' in Gent. This event will take place on 10-13 October. The nodegoat workshop will be on Tuesday 11 October from 14:00 to 15:30. You can find the full program here.

There will also be a nodegoat workshop at the conference 'Creating Spatial Historical Knowledge. New Approaches, Opportunities and Epistemological Implications of Mapping History Digitally'. This conference is organised by the German Historical Institute in Washington DC. The conference takes place on 20-22 October. The nodegoat workshop will be on Thursday 20 October from 14.15 to 16.00. This workshop requires individual registration. The full program of the conference can be found here.

We have proposed a session at the THATCamp Amsterdam on Linked Data challenges. Together with Ingeborg van Vugt we plan to discuss the benefits and difficulties of Linked Data in the humanities.

After a stimulating Virtual Heritage Network conference last year in Maynooth, we look forward to this year's conference in Cork. The conference will take place on 8-10 December.[....]

There will be a nodegoat community meeting at the Mundaneum (Paul Otlet ftw) in Mons (Belgium) on July 1. This meeting is an initiative of the TIC project at the University of Ghent in cooperation with DARIAH-BE. The meeting follows on the doctoral workshop 'Tracing Mobilities & Socio-political Activism. 19th-20th centuries' that takes place at the Mundaneum between June 29 and July 1.

The nodegoat community meeting will start with a general introduction on the current status of nodegoat and upcoming new features. Next, we will have four presentations of projects that make use of nodegoat:

• Wechanged: Agents of change: women editors and socio-cultural transformation in Europe, 1710-1920
• SPIN: Study platform on interlocking nationalisms
• NISE: National movements & intermediary: structures in Europe
• TIC Collaborative: The transnational dynamics of social reform, 1840-1940

See the full program here (the nodegoat meeting is on the last page of the PDF).

The following interactive visualisation explores the movements of 10.896 Representatives of the United States Congress, from Roger Sherman's birth in 1721 up until all its members in 2015. The Representatives move from their place of birth to their place of education and finally to their possible place of death. Click here to open the interactive visualisation.

Last April, we gave a talk at the tenth Historical Network Research workshop in Düsseldorf about the 'Reversed Classification' functionality in nodegoat. To illustrate what you can accomplish with this functionality, we queried Wikidata to get a dataset of all the members of the US House of Representatives, including their date and place of birth and death, their professions, and the institutes where they took their education. We used this data to perform a reversed classification process that groups the representatives into career politicians or politicians with a heterogeneous career. From there, you could start looking at geographical patterns or educational backgrounds of these groups. See a graph of this network with these two 'career' nodes included here (canvas).

The diachronic geographical visualisation of all this data in nodegoat turns out to be a nice bonus.

Düsseldorf, Assumulator / CC BY-SA 3.0

The tenth Historical Network Research workshop will be in Düsseldorf from 28-04-2016 to 30-04-2016. They have set up an exciting programme on the theme 'Fakten verknüpfen, Erkenntnisse gewinnnen? Wissenschaftsgeschichte in Historischer Netzwerkanalyse'.

On the first day, we will host a nodegoat workshop. This workshop will last half a day and is titled 'Advanced HNR' (it will run in parallel with an introductory historical network research workshop by Martin Stark). Since we only have half a day, we encourage participants who have not used nodegoat before to watch our three tutorials that cover basic functionalities of nodegoat.[....]

We have taken data available in Wikidata and DBpedia on 'Military Conflicts' to create this interactive visualisation in nodegoat:

Wikidata

From the outside, it can be a challenge to keep up with all the developments within the ever expanding universe of wiki*/*pedia. So it's good to be reminded now and then of all the structured data that has become available thanks to their efforts:

This looks pretty neat, especially since Wikidata currently has over 947 million triples in their data store. Since battles usually have a place and a date, it would be nice to import this data into a data design in nodegoat and visualise these battles through time and space (diachronic geospatiality ftw).[....]