1. The future of collaborative working

2. In 20 years how would analysts collaborate to report on a major global event as it happens? What kind of technologies would be available to augment this work? Research Questions

3. The Environment

4. Van Dam, Andries, (1997). "Post-WIMP user interfaces." Communications of the ACM, 40.2 (1997): 63-67. Harper, R. H. (2008). Being human: Human-computer interaction in the year 2020. Microsoft Research Limited. Benko, H., Jota, R., & Wilson, A. (2012). MirageTable: freehand interaction on a projected augmented reality tabletop. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 199-208). ACM. Evolving Hardware

5. Van Dam, Andries, (1997). "Post-WIMP user interfaces." Communications of the ACM, 40.2 (1997): 63-67. Harper, R. H. (2008). Being human: Human-computer interaction in the year 2020. Microsoft Research Limited. Benko, H., Jota, R., & Wilson, A. (2012). MirageTable: freehand interaction on a projected augmented reality tabletop. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 199-208). ACM. Evolving Hardware

6. Van Dam, Andries, (1997). "Post-WIMP user interfaces." Communications of the ACM, 40.2 (1997): 63-67. Harper, R. H. (2008). Being human: Human-computer interaction in the year 2020. Microsoft Research Limited. Benko, H., Jota, R., & Wilson, A. (2012). MirageTable: freehand interaction on a projected augmented reality tabletop. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 199-208). ACM. Evolving Hardware

7. Van Dam, Andries, (1997). "Post-WIMP user interfaces." Communications of the ACM, 40.2 (1997): 63-67. Harper, R. H. (2008). Being human: Human-computer interaction in the year 2020. Microsoft Research Limited. Benko, H., Jota, R., & Wilson, A. (2012). MirageTable: freehand interaction on a projected augmented reality tabletop. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 199-208). ACM. Evolving Hardware

9. Challenges Collaboration Dealing with massive data streams: Refining data Credibility of sources Expertise and knowledge

12. “I” Intention “We” Intention “I” Intention

13. Collaborative Group Member Selection Technology assisted selection Professional recommendation

16. Handling Massive Data: AI

17. Conceptual Semantic Networks Represent knowledge in a machine-readable form to allow automated inferences based on relationships between things rich data queries Retain knowledge within a system Integrate data from disparate sources Connect data conceptually to allow easier collaboration and sharing

18. Artificial Neural Networks Attempt to model the connective features of the human brain Learn by adjusting to changes in an information environment according to certain algorithms and laws. Can find patterns in data, even when the data is incomplete, ambiguous, complex or noisy. Can analyse the data and network activity in CSNs to analyse data and model outcomes including human behaviours. Stevens, R., & Casillas, A. (2006). Artificial neural networks. In Automated Scoring of Complex Tasks in Computer Based Testing: An Introduction. Lawrence Erlbaum, Mahwah, NJ, 259-312.

19. Thank You Any Questions? Beeston G.P. Blair R.D. Fair N.S.R. Fitzsimmons G. Green L. Munson J.E. Rimington E.M. Weston A.