INTRE:FACE conference archives: Jürgen Neumann and Jörg Richter presenting DeepaMehta

The INTRE:FACE Digital Conference (06.02.2016-07.02.2016), organized by Katharina Deloglu and Tom Bresemann, hosted by Andreas Bülhoff, tackled many important questions regarding digital literature. In a series of articles we bring you the speeches and discussions held at the INTRE:FACE Digital Conference, dealing with problems regarding digital literature and different tools used to construct it, for example how can digital tools be used to offer new approaches to production, what digital tools already exist and how are they structured, to more applied problems, such as how can literary activists use digital means to connect with one another, how we can make most of digital material and many other interesting topics.

Jürgen Neumann and Jörg Richter joined us to explain the concept behind their software DeepaMehta, used for the OMNIBUS reading tour app. DeepaMehta is a software platform for knowledge workers. The special feature of DeepaMehta is the situation-centered user interface: information belonging to one working context is — together with its meaningful relationships — displayed and edited in a single window. Whether it is text, images, documents, emails, web pages, events or for example contacts.


For understanding of the software, several questions have to be asked:

  • What do you expect from the network?
  • Why should we map a social network and how?
  • To what extent can we create an effective interface with DeepaMehta?

However, to begin with, we should maybe go back to the start and ask ourselves – What’s the difference between data, information and knowledge? Everything in the computer is data – but what turns it into knowledge?

The group present at the conference proposed several ideas, that knowledge combines data in a form, creates links between singular entities; that knowledge can be received by someone else, it can be shared – it needs a human being to process the data; that data can be read and interpreted, so that it becomes knowledge – this assumes a means of interpretation, be that language, code, a type of intuitive language or a certain type of interface.

DeepaMehta can show the association between two pieces of data – we, as intelligent human beings, can later give these associations meaning. We can read them in the form [Subject, predicate(object)]. For example, the data item (person) ‘Hannes Bajohr’ has a connection ‘Editor’ with another data item (work) ‘Code und Konzept’.

Creating connections in Deepa Mehta
Creating connections in Deepa Mehta

Regarding cognition, in DeepaMehta, there is no need for lots of sense information in order to interpret the data, as with normal cognition. The visual information on the screen is reduced. Thinking is proposed as ‘a way of modelling the world’. As everyone models their world in a subjective way, we need to give people the chance to model the network for themselves. DeepaMehta allows people to create their own maps which show them the connections which are relevant for them – it shows you ‘your view on your work’.

A problem all knowledge based tools face is how to turn data into something useful. To show how it can be done, we can resort to the Actor-Network
theory (ANT). It tries to explain how material semiotic networks come
together to act as a whole. The networks are composed out of relations
between human beings (actors) and technical artefacts (actants) and
also between each of them. It assumes that relations are both material
and semiotic and that these relations need to be repeatedly re-enacted
for them to be meaningful. This could maybe be applied to the literary scene as things are always changing. In the real world, relationships are always refreshed. On a database, it is stagnant – it is hard to know whether the data is relevant. Should we integrate a relevancy function that could possibly have a time limit on the data? Should the relevancy be determined by how much interaction the user has with the information, similarly to how Facebook judges who are our closest friends based on the frequency of our interactions?

But when does a sum of parts become a whole? This question evokes an individual response depending on the field it is raised in. For literary networks such as CROWD, we would need to develop a common understanding of what constituted an ‘author’ or ‘institution’, for example, in the database, i.e., what would be the component parts of the person which are useful for the purposes of CROWD? – Name, date of birth, nationality, languages, address? What properties are missing?

To answer that we have to look at what information is necessary for the CROWD and establish how the network can have value for a company or organization, CROWD, be that economic, productive, collaborative…

Is this just a visualization of an excel sheet?

Jürgen Neumann: No, because you can create a personalized space which shows connections that are relevant to you or your organization.

We want this to be an open source network, but also we realize the necessity to define user profiles with different administrative roles. Who will assign these roles and how?

Jürgen Neumann: “Knowledge is power” – we have to focus on the political aspects of who has access to these maps. These questions need to be reflected on seriously before we decide who will be able to add or edit information at each level of the database.

Surely this information exists already? Is this map not superfluous?


Jürgen Neumann: The internet is full of information, but it can be hard to synthesize or to keep track on how it all links together. DeepaMehta clearly shows both the information and how it is linked to other information. You could think of it as your Google Search history shown as a map – it gives you a context of where you came from and provides a situational work environment.

I want a map of reliable information – if everyone can input information, how can you make sure the data is reliable? Up to date?

There are many essential decisions to be taken and discussion to be
made as how DeepaMehta should be structured and governed by the CROWD network and it’s actors. Questions about who should have responsibility and access levels of the system are intrinsically tied with the question of who is going to keep the data up to date.

How can you maintain relevancy of information? Could we include an ‘error found’ button for wrong information? A yearly/monthly subscription?

Other questions which need to be considered by CROWD:

-How will you archive it? Are you going to keep versions of the DeepaMehta map?

-What terms do you use to define the relationships? How do we decide on a common language in the system that can be relevant for all users? For example, is the title “Work” an effective way of denoting all artistic works? Is “institution” the right name for all literary organizations/ groups?

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