Herder, Eelco

Hopfgartner, Frank

Kay, Judy

Kummerfeld, Bob

Plumbaum, Till

Rapp, Amon

English

Institutional Research Information System University of Turin

LinkQS:	  Workshop	  on	  Linking	  The	  Quantified	  Self	  (LQS	  2014)	  	  Quantified	  Self	  (QS),	  also	  known	  as	  Personal	  Informatics	  (PI),	  is	  a	  school	  of	  thought	  that	  aims	  to	  use	  technology	  for	  acquiring	  and	  collecting	  data	  on	  different	  aspects	  of	  the	  daily	  lives	  of	  people.	  These	  data	  can	  be	  internal	  states	  (such	  as	  mood	  or	  glucose	  level	  in	  the	  blood)	  or	  indicators	  of	  performance	  (such	  as	  the	  kilometers	  run).	  The	  purpose	  of	  collecting	  these	  data	  is	  self-­‐monitoring,	  performed	  in	  order	  to	  gain	  self-­‐knowledge	  or	  some	  kind	  of	  change	  or	  improvement	  (behavioral,	  psychological,	  therapeutic,	  etc.).	  Although	  the	  current	  spread	  on	  the	  market	  of	  these	  kinds	  of	  tools,	  many	  issues	  arise	  when	  we	  consider	  their	  usage	  in	  the	  daily	  lives	  of	  common	  people,	  such	  as	  the	  meaningfulness	  and	  utility	  of	  the	  gathered	  data	  for	  the	  final	  users.	  We	  can	  think	  to	  address	  some	  of	  these	  issues	  looking	  beyond	  the	  Quantified	  Self	  for	  finding	  new	  technologies	  and	  design	  techniques	  that	  could	  be	  applied	  to	  this	  field.	  One	  of	  the	  main	  challenges	  of	  self-­‐tracking	  data	  is	  that	  it	  comes	  in	  heterogeneous	  and	  often	  very	  unstructured	  form.	  One	  of	  the	  possible	  ways	  is	  leveraging	  Semantic	  Web	  techniques	  for	  integrating	  heterogeneous	  data	  originated	  from	  different	  devices	  and	  applications	  and	  give	  them	  some	  kind	  of	  structure.	  In	  Quantified	  Self,	  in	  fact,	  the	  information	  gathered	  by	  QS	  tools	  are	  scattered	  in	  autonomous	  silos,	  that	  can	  hardly	  be	  meshed	  together	  in	  order	  to	  provide	  users	  a	  complete	  and	  satisfying	  mirror	  of	  their	  behaviors	  and	  physical	  or	  psychological	  states.	  Besides,	  often	  QS	  tools	  simply	  juxtapose	  different	  data	  in	  their	  visualizations	  but	  they	  are	  not	  able	  to	  highlight	  meaningful	  correlations	  and	  provide	  structures	  for	  the	  data	  gathered.	  Given	  that	  the	  quantified-­‐self	  trend	  is	  just	  gaining	  momentum,	  it	  is	  not	  unlikely	  that	  we	  will	  soon	  have	  more	  and	  more	  users	  who	  create	  their	  own	  personal	  repositories,	  also	  referred	  to	  lifelogs.	  	  Structuring	  the	  data	  in	  these	  lifelogs	  is	  of	  particular	  importance	  in	  the	  context	  of	  user	  modeling.	  User	  Modeling	  techniques	  can	  provide	  useful	  insights	  for	  reasoning	  on	  data	  gathered,	  since	  users	  are	  not	  only	  in	  search	  of	  the	  possibility	  to	  visualize	  their	  behavioral	  data,	  but	  also	  to	  receive	  useful	  suggestions	  for	  improving	  their	  habits	  and	  behavior.	  Although	  QS	  tools	  have	  at	  their	  disposal	  huge	  amount	  of	  data	  on	  user	  behavior,	  they	  are	  not	  currently	  exploiting	  them	  for	  modeling	  users	  and	  providing	  them	  personalized	  recommendations.	  	  In	  this	  workshop	  we	  tried	  to	  investigate	  challenges,	  open	  issues	  and	  new	  perspectives	  related	  to	  the	  dominion	  of	  data	  employed	  in	  Quantified	  Self	  and	  Personal	  Informatics	  technologies.	  The	  workshop	  organizers:	  Amon	  Rapp	  Università	  di	  Torino	  Frank	  Hopfgartner,	  Technische	  Universität	  Berlin	  Till	  Plumbaum,	  Technische	  Universität	  Berlin	  Judy	  Kay,	  University	  of	  Sydney	  Bob	  Kummerfeld,	  University	  of	  Sydney	  Eelco	  Herder,	  L3S	  Research	  Center	  Hannover	  	  	  Program	  	  (accepted	  papers)	  	  Federica	  Cena,	  Silvia	  Likavec,	  Amon	  Rapp,	  Martina	  Deplano	  and	  Alessandro	  Marcengo.	  Ontologies	  for	  Quantified	  Self:	  a	  semantic	  approach	  Faisal	  Alquaddoomi,	  Cameron	  Ketcham,	  Deborah	  Estrin.	  The	  Email	  Analysis	  Framework:	  Aiding	  the	  Analysis	  of	  Personal	  Natural	  Language	  Texts	  Timothy	  Wayne	  Cook	  and	  Luciana	  Tricai	  Cavalini.	  A	  Multilevel-­‐Model	  Driven	  Social	  Network	  for	  Healthcare	  Information	  Exchange.	  	  Program	  Committee	  Rami	  Albatal,	  Dublin	  City	  University	  Federica	  Cena,	  University	  of	  Torino	  Na	  Li,	  Dublin	  City	  University	  Alessandro	  Marcengo,	  Telecom	  Italia	  Jochen	  Meyer,	  OFFIS,	  Germany	  

LinkQS: Workshop on linking the quantified self (LQS 2014)

https://iris.unito.it/bitstream/2318/1663600/1/2014-LQS2014_Preface.pdf

LinkQS: Workshop on linking the quantified self (LQS 2014)

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