Archival Consciousness

Saving and growing knowledge with a hybrid annotation tool

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Our problem

Libraries and archives try to save knowledge by digitizing books. But they miss to collect the emerging knowledge when readers work with texts – interpretations, notes, connections and references. Furthermore searching for the right content and understanding the context and a topics reach is difficult. A lot of knowledge stays in the dark.

Machine learning combined with human annotations to grow a neural network

Our idea

Collection do povo is an online platform that enables researchers to contribute to and grow the content of a library by annotating words on book pages. These annotations create an interconnected graph of themes and topics which helps researchers to be inspired and discover correlations between books.

Our solution

A platform that allows for playful labeling

We stimulate users’ intrinsic motivation.

Following Andrzej Marczewski’s gamification model R.A.M.P. we demonstrate the purpose of user contribution. First, our onboarding explains that every contibution helps other researchers to find interconnected topics of their research. Secondly, every annotation is rewarded with a micro-animation of growing connections.

We give freedom of choice.

Autonomy is an important factor for users to deliberately interact with the content. Therefore we let them choose a page on a topic of their interest at the end of the onboarding. Furthermore, they can choose on their own which words they want to annotate.

We challenge the knowledge.

By a means of tunneling users are asked follow-up questions on annotations they made. These questions follow a What - Where - When - Why logic, which form extended connections to other topics. To users this seems like a quiz while at the same time we grow the body of knowledge.

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Our process

Following Google’s Design Sprint with a few tweaks

Phase 1: Understand

In the beginning, we broadened our perspective on the project by identifying our clients’ objectives, engaging with experts and users, and analyzing the competitors.

Phase 2: Define

In the second phase, we defined the main emphasis within the problem space and identified the goal and the users of our project by means of the gathered information.

Phase 3: Sketch

Afterwards, we indivudally generated several sketches influenced by our findings from research.

Phase 4: Decide

Together, we evaluated each of the ideas , iterated on them, and chose one concept would then be transferred to the digital space.

Phase 5: Prototype

In this phase, we envisioned our concept through a digital prototype to compare different solutions and validate various aspects in the following phase.

Phase 6: Test

In the validation phase, we gathered feedback and valuable insights from our users. These findings served together with the following ideation phase as a foundation to redefine the problem space.

Our Team

Joint talents and good team spirit

Image of Bianca Brandner

Bianca Brandner

  • Research & Concepting
  • UX/UI Design
  • Illustration & Animation
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Image of Martijn Fleurkens

Martijn Fleurkens

  • UX/UI Design
  • Full Stack Development
  • Concept Development
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Image of Lena Overkamp

Lena Overkamp

  • Team Lead & Project Management
  • UX/UI Design
  • Art Direction
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Image of Tatiana Vanegas

Tatiana Vanegas

  • Motion & Graphic Designer
  • Visual Design
  • UX/UI Design
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