Activity Streaming as Information X-Docking

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Activity Streaming as Information X-Docking

  1. 1. Activity Streaming as Information X-Docking Dr. Kai Riemer, Discipline of Business Information Systems
  2. 2. Activity streams - what's the idea? <ul><li>Spurred by the emergence of Twitter or Facebook </li></ul><ul><li>Bundle status updates from a wide variety of sources in one integrated stream </li></ul><ul><ul><li>human-generated messages (as in microblogging or social networking) </li></ul></ul><ul><ul><li>machine-generated updates (e.g. from ERP or project software), </li></ul></ul><ul><ul><li>sensor data or other machinery. </li></ul></ul><ul><li>ONE integrated stream of real-time information for decision making. </li></ul>Dr. Kai Riemer, Discipline of Business Information Systems Image: http://intelligentsiya.blogspot.com/2009_02_01_archive.html &quot;One stream to feed them, one stream to serve them, in real-time to inform them.&quot;
  3. 3. Activity streams – no magic ring. <ul><li>How do we decide what's important in the abundance of information that speeds past in this integrated stream every split second? </li></ul><ul><li>How do we organise following relationships, filtering, tapping into this massive stream? </li></ul>&quot;One stream to overload them, one stream to blind them, in information to bury them.&quot; Image: http://www.tungstenlord.com/tungsten-carbide-lord-of-the-ring.html Dr. Kai Riemer, Discipline of Business Information Systems
  4. 4. Analogy of X-Docking as a framework <ul><li>What is cross-docking (X-Docking)? </li></ul><ul><ul><li>Retail industry concept </li></ul></ul><ul><ul><li>Warehouse without inventory  only sorting facility </li></ul></ul><ul><ul><li>Speed up distribution processes between manufacturers and retail outlets. </li></ul></ul><ul><li>This is how it works: </li></ul><ul><ul><li>Manufacturers deliver products in full truck loads, </li></ul></ul><ul><ul><li>X-Docking area is a automated sorting system using transport belts </li></ul></ul><ul><ul><li>Full truck loads leave to the outlets Outbound deliveries contain a mix of products with whatever the respective outlet needs. </li></ul></ul>Dr. Kai Riemer, Discipline of Business Information Systems
  5. 5. X-Docking Receiving Sorting Shipment Manufacturers Outlets (cf. http://people.hofstra.edu/geotrans/eng/ch5en/conc5en/crossdocking.html) Dr. Kai Riemer, Discipline of Business Information Systems
  6. 6. X-Docking Receiving Sorting Shipment Manufacturers Outlets Manufacturers Outlets Before X-Docking Manufacturers Outlets After X-Docking X-Dock (cf. http://people.hofstra.edu/geotrans/eng/ch5en/conc5en/crossdocking.html) Dr. Kai Riemer, Discipline of Business Information Systems
  7. 7. How does X-Docking relate to activity streams? <ul><li>Goals of X-Docking and Activity Streaming are much the same: </li></ul><ul><ul><li>Consolidate item flows from different sources, </li></ul></ul><ul><ul><li>Centralise the flow of items in one place, </li></ul></ul><ul><ul><li>Rather than store items, facilitate near-time distribution, and </li></ul></ul><ul><ul><li>Ship items to a the right customers. </li></ul></ul><ul><li>Analogy exposes areas, in which implementing activity streams will be challenging: </li></ul><ul><ul><li>Sorting/streaming: This is not where the challenges lie! </li></ul></ul><ul><ul><li>Inbound delivery: data items need to be enriched with meta information in order to enable distribution to the right receivers. </li></ul></ul><ul><ul><li>Outbound delivery: users to to be able to articulate their information needs; needs have to be translated and propagated through to information sources.    </li></ul></ul>
  8. 8. Activity Streaming Tagging Streaming Filtering Sources Users Sources Users Before Activity Streams Sources Users Stream After Activity Streams Dr. Kai Riemer Note that the colouring of the items is changed  this is to emphasise the user focus in activity streaming. The focus is not on the information sources and their information, but on the various information needs, which need to be articulated.
  9. 9. Activity Streaming vision  challenges <ul><li>Determine information needs </li></ul><ul><li>Information tagging and meta data </li></ul><ul><li>Data filtering and contextual delivery </li></ul><ul><li>Heterogeneous nature of receivers </li></ul><ul><li>Heterogeneous nature of senders </li></ul><ul><li>Integration with user environment </li></ul>Dr. Kai Riemer, Discipline of Business Information Systems
  10. 10. 1. Determine information needs <ul><li>Depending on the usage scenario information needs can </li></ul><ul><ul><li>emerge instantly (e.g. a fire is reported), </li></ul></ul><ul><ul><li>be very contextual (e.g. focused on a geographical area) </li></ul></ul><ul><ul><li>and might change rapidly (the fire spreads, the scenario changes from fire containment to evacuation). </li></ul></ul><ul><li>Mechanism is needed to populate changing needs to data sources. </li></ul><ul><li>Open questions: </li></ul><ul><ul><li>How can such information needs be determined or articulated by the users? </li></ul></ul><ul><ul><li>Manually, automatically? </li></ul></ul><ul><ul><li>In what way? </li></ul></ul><ul><ul><li>With what devices? </li></ul></ul><ul><ul><li>How are they passed to the sources? </li></ul></ul>Dr. Kai Riemer, Discipline of Business Information Systems
  11. 11. 2. Information tagging and meta data <ul><li>Inbound data items need to be enriched with meta data </li></ul><ul><ul><li> tagging. </li></ul></ul><ul><li>Depending on source (software, people on Twitter, sensors delivering status updates etc.) such mechanisms will likely be very different. </li></ul><ul><li>Open questions: </li></ul><ul><ul><li>How is this tagging going to work? </li></ul></ul><ul><ul><li>How can tagging tie in with articulation of information needs? </li></ul></ul><ul><ul><li>Will this be achieved in real time in time critical scenarios? </li></ul></ul>Dr. Kai Riemer, Discipline of Business Information Systems
  12. 12. 3. Data filtering and contextual delivery <ul><li>Sorting the activity stream to derive outbound deliveries is key. </li></ul><ul><li>Users need an effective mechanism to filter the stream, </li></ul><ul><ul><li>only relevant data is delivered, </li></ul></ul><ul><ul><li>often relevant only for a specific context (e.g. when evacuating a suburb the decision makers will have to have ready access to and focus only on information relevant to this task). </li></ul></ul><ul><li>Open questions: </li></ul><ul><ul><li>How will filtering work? </li></ul></ul><ul><ul><li>How does it tie in with tagging? </li></ul></ul><ul><ul><li>The two are closely related, as the one will not work without the other. </li></ul></ul>Dr. Kai Riemer, Discipline of Business Information Systems
  13. 13. 4. Heterogeneous nature of receivers <ul><li>Unlike X-Docking, receivers or user of information show much more variance. </li></ul><ul><li>Outbound streams might be organised for organisational roles, entire teams, divisions, projects or otherwise contexts, not just for individuals </li></ul><ul><li>Open questions: </li></ul><ul><ul><li>How will information needs be determined for these different user groups? </li></ul></ul><ul><ul><li>How can such information be represented? </li></ul></ul><ul><ul><li>Who decides on information needs? </li></ul></ul>Dr. Kai Riemer, Discipline of Business Information Systems
  14. 14. 5. Heterogeneous nature of senders <ul><li>Complexity in Activity Streaming is higher than in X-Docking </li></ul><ul><li>Major challenges here are </li></ul><ul><ul><li>tapping into external, public sources (e.g. Twitter) </li></ul></ul><ul><ul><li>making available data from legacy systems in reliable form. </li></ul></ul><ul><li>EXAMPLE: Twitter in a disaster scenario: </li></ul><ul><ul><li>people start sharing information (e.g. regarding fire spread) using hash-tags </li></ul></ul><ul><ul><li>hashtags (#fire) gain widespread adoption in a matter of minutes. </li></ul></ul><ul><ul><li>mechanism is needed to pick up the emergence of such tags </li></ul></ul><ul><li>Open questions: </li></ul><ul><ul><li>How can a socio-technical solution facilitate such information access from external sources? </li></ul></ul><ul><ul><li>Will learning algorithms facilitate streaming of such information? </li></ul></ul>Dr. Kai Riemer, Discipline of Business Information Systems
  15. 15. 6. Integration with user environment <ul><li>In X-Docking, once products have been delivered to supermarket, they are put on the shelves. That's it. </li></ul><ul><li>Use of information is very different; </li></ul><ul><ul><li>ties in with users' work practices </li></ul></ul><ul><ul><li>determining information needs, filtering, tagging, information consumption needs to become part of such work practices. </li></ul></ul><ul><li>Open questions: </li></ul><ul><ul><li>How can activity streams be made available in different scenarios? And with various devices? </li></ul></ul><ul><ul><li>How will integration with existing software, application and work practices be achieved? </li></ul></ul>Dr. Kai Riemer, Discipline of Business Information Systems
  16. 16. Activity Streaming in Disaster Management(example) Twitter Call Center Field Staff Weather sensors Satellite Data Fire fighters (field staff) Decision makers Evacuation related etc. Tagging Filter Collate Distribute Dr. Kai Riemer, Discipline of Business Information Systems
  17. 17. Contact information <ul><li>Dr. KAI RIEMER | Senior Lecturer Discipline of Business Information Systems | Business School                                                                          THE UNIVERSITY OF SYDNEY                </li></ul><ul><li>T +61 2 9036 9053  | F +61 2 9351 7294   E [email_address] | W http://sydney.edu.au/business/staff/kair Blog http://byresearch.wordpress.com </li></ul><ul><li>Collaborators: </li></ul><ul><ul><li>A/Prof Deborah Bunker (USYD): [email_address] </li></ul></ul><ul><ul><li>Dr. Alexander Richter (Bundeswehr Uni Munich): [email_address] </li></ul></ul>

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