Paul Girard

Looking back at 4 years of Open research tools and technologies devroom, we propose an open discussion on what's been done and what's to do. The panel will be held by the devroom organisers and will present a brief wrap-up of the 2023 edition, before opening the floor to the attendance. We are looking for feedback regarding the event itself, and inputs about its part in the community. Where are we, and where should we go from here?

Other people: Matthieu Totet Mathieu Jacomy Diego Antolinos-Basso Maya Anderson-González Sara Petti

Driving research based on large collection of data often demands in the humanities a strong collaboration between researchers and data engineers. Data are the corner stone on which the research is based. Caring about our research data is not only a good practice to drive and open our research, it's also a good way to foster collaboration between researchers and engineers. In this talk we will present how, in a Digital Humanities research project, controlling the data quality and structure through a frictionless data package leverage the a great data productivity.

Please note that this talk replaces one entitled "Data flowing the right way" that was due to have been given by María Arias de Reyna, who has sent his apologies but is now unable to attend the conference.

Discussion between speakers of the Knowledge Management Communities panel.

Open source software can help in building communities around common practices. Damien Goutte-Gattat's talk shows how a piece of software (Ontology Development Kit) can help ontology editors to deploy their tools and at same time foster standardized ways to write and publish their work. A double benefit grounded in FOSS practices.

But Open source software also benefits in return of organized users communities. Lozana Rossenova and Dragan Espenschied present the Wikibase Stakeholder Group which gathers a community of wikibase server and its plugins users and developers. A detailed explanation of how to care a community around a FOSS.

Those two sides of community building around knowledge management will be discussed with the speakers in a live discussion panel. Questions from the audience will be collected from the textual chatroom and voiced by the session moderator.

Other people: Damien Goutte-Gattat Lozana Rossenova Dragan Espenschied

Discussion panel of three testimonies from academics developing software.

Developing software from academia is not easy. Scholars are meant to teach and write. Releasing a research software demands much more than writing code. In this panel discussion, the four speakers will share their thoughts on those challenges. The discussion will benefit from the variety of situations they all bring : a "scholar-analyst" collaborating with a tech team, a team of scholars/engineers and a sociologist who codes alone. Should scholars leave coding to the professional? What does open sourcing code brings to the game? What does maintaining a research software require? Is coding from academia actually fun or a burden?

Add your own questions to this list by participating to the live event. Questions from the audience (chatroom) will be asked to the panel by the moderator.

Other people: Ian Johnson Josquin Debaz John Boy Waldir Lisboa Rocha

The Open Research Tools and Technologies devroom managers welcome words announcing the schedule.

This years the Open Research devroom schedule has been organized in thematic panels:

• Academics developing software testimonies panel
• Visual inquiries panel
• Policies panel
• Artificial Intelligence Panel
• Open Hardware Panel
• Standards panel
• Knowledge management communities panel
• Open Data Panel

Other people: Matthieu Totet Mathieu Jacomy Célya Gruson-Daniel Yo Yehudi Maya Anderson-González Sara Petti

France started to compile statistics about its trade in 1716. The "Bureau de la Balance du Commerce" (Balance of Trade's Office) centralized local reports of imports/exports by commodities produced by french tax regions. Many statistical manuscript volumes produced by this process have been preserved in French archives. This communication will relate how and why we used network technologies to create a research instrument based on the transcriptions of those archives in the TOFLIT18 research project. Our corpus composed of more than 500k yearly trade transactions of one commodity between a French local tax region or a foreign country between 1718 and 1838. We used a graph database to modelize it as a trade network where trade flows are edges between trade partners. We will explain why we had to design a classification system to reduce the heterogeneity of the commodity names and how such a system introduce the need for hyperedges. Our research instruments aiming at providing exploratory data analysis means to researchers, we will present the web application we've built on top of the neo4j database using JavaScript technologies (Decypher, Express, React, Baobab, SigmaJS). We will finally show how graph model was not only a convenient way to store and query our data but also a poweful visual object to explore trade geographical structures and trade products' specialization patterns.

By Paul Girard and Guillaume Plique. Sciences Po, médialab, Paris, France

Project funded by the French Agence Nationale de la Recherche (TOFLIT18)

Khartis results from an observation: how can we create easily a statistical map, with a few clicks, without loosing the scientific accuracy and rigor while processing the data? Khartis is not the first mapping tool available online! It is, however, one of the few to propose different perspectives of the world representation among which the cartographer will choose. In order to feed the tool with data, you may want to retrieve from the Khartis website the data used to produce the maps given as examples or to import or copy / paste your own datasets. The base maps are geo-referenced and allow you to work on the proposed entities (countries, regions...) but also on objects identified by pairs of coordinates. You can choose between several projections (besides Mercator) and configure the visual appearance of your data.

Bruno Latour wrote a book about philosophy (an inquiry into modes of existence). He decided that the paper book was no place for the numerous footnotes, documentation or glossary, instead giving access to all this information surrounding the book through a web application which would present itself as a reading companion. He also offered to the community of readers to submit their contributions to his inquiry by writing new documents to be added to the platform. The first version of our web application was built on PHP Yiii and MySQL on the server side. This soon proved to be a nightmare to maintain because of the ultra-relational nature of our data. We refactored it completely to use node.js and Neo4J. We went from a tree system with internal links modelized inside a relational database to a graph of paragraphs included into documents, subchapters etc. all sharing links between them. On the way, we've learned Neo4J thoroughly, from graph data modeling to cypher tricks and developped our custom cypher query graphical monitor using sigma.js in order to check our data trans-modeling consistency.

During this journey, we've stumbled upon data model questions : ordered links, sub items grouping necessity, data output constraints from Neo4J, and finally the limitations of Neo4J community edition. Finally we feel much more confortable as developers in our new system. Reasoning about our data has become much easier and, moreover, our users are also happier since the platform's performance has never been better.

Our intention is, therefore, to share our experience with the community:

- our application's data needs
- our shift from a MySQL data model to a Neo4J graph model
- our feedbacks in using a graph database and more precisely Neo4J including our custom admin tool [Agent Smith](https://github.com/Yomguithereal/agent-smith)
- a very quick description of the admin tools we built to let the researchers write or modify contents (a markdown web editor)

The research has received funding from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / erc Grant ‘IDEAS’ 2010 n° 269567”

Authors :

Guillaume Plique A graduate student from Sciences-Po Lille and Waseda University, Guillaume Plique now offers the médialab his backend development skills as well as his profile in social sciences. He has been working since June 2013 on several projects such as IPCC mapping, AIME and develops scrapers aimed at social sciences researchers. https://github.com/Yomguithereal

Paul Girard Paul Girard is an Information Technology engineer specialized in driving collaborations between technology and non-technical domains. He graduated from the cultural industry engineering specialisation in Université de Technologie de Compiègne in 2004 where he studied the relationships between digital technologies and society and the mechanisms of collaborations. He worked in the research laboratories federation CITU (Paris 1 and Paris 8 universities) from 2005 to 2009 where he participated in research and creation projects, collaborations between artists and engineers working with interactivity, digital pictures, virtual and augmented reality. He joined the médialab laboratory at Sciences Po at its foundation during the spring of 2009, as the digital manager of this digital research laboratory dedicated to fostering the use of digital methods and tools in Social Sciences. Since then he oversees the technical direction of the many research projects as collaborations between social sciences, knowledge engineering and information design. His present research fields are digital methods for social sciences, exploratory data analysis and enhanced publication though digital story telling. https://github.com/paulgirard

Daniele Guido Daniele Guido is a visual interaction designer interested in data mining applications, text analysis and network tools. He collaborates with researchers in History and Social Science, designers and engineer to conceive and develop digital tools for the humanities. He recently joined the DIgital Humanities lab at CVCE team in Luxembourg after several years working at the Sciences-Po Medialab team in Paris, where he was engaged in the FORCCAST project (forccast.hypotheses.org) and in the AIME project (modesofexistence.org) https://github.com/danieleguido

More and more people work with graphs nowadays, but it is not always easy to publish and share the graph interpretation on the web. Manylines is a web tool built at Sciences Po médialab to solve this issue. Some researchers and students use network visualizations to explore their data, but networks are not as clear as maps and sharing one’s interpretation is difficult. Manylines main innovation is to allow the user to explain and share a narrative about his network: an interactive story where each “slide” is a particular zoom, pan and filtering of the network, completed by a title and description, with fluid transitions like in Prezi.

Published as an open source prototype with the source code available on GitHub, Manylines is currently built around three screens: - The first screen allows applying the ForceAtlas2 layout to the network, in order to settle the “basemap”: the definitive positions of nodes and edges used to support further interpretations. - The second screen allows zooming and filtering the network to explore the data and “take snapshots” representing different insights. - The third screen allows composing narratives by building a series of snapshots, adding a title and short description for each step. The result is an interactive slideshow widget where the user's exploration of the network is guided step by step, revealing the key interpretation points one by one.

Manylines is a single webpage app built for HTML5 browsers. It makes an extensive use of the sigma.js library to deal with networks within the browser and it implements different features inspired from Gephi, the reference desktop graph viz platform. The WebGL visualization (with Canvas fallback) implemented by Sigma.js allows great performance for networks up to 1000 nodes on an average computer. To reach this level of performance, we optimized the javascript version of the ForceAtlas2 algorithm used by sigma.js. We ported it to use web workers and we optimized the Barnes-Hut quadtree approximation in this context by implementing it as an iterative and not recursive process. We made an extensive use of sigma.js' custom renderers and cameras to build dynamic graph thumbnails, snapshots and widgets. The server side stores the networks, snapshots and narrative data in a Couchbase database (which we discovered in FOSDEM 2014) accessed by a Node.js express REST API.