@misc{haslhofer2013semantic,
  abstract = {Tags assigned by users to shared content can be ambiguous. As a possible solution, we propose semantic tagging as a collaborative process in which a user selects and associates Web resources drawn from a knowledge context. We applied this general technique in the specific context of online historical maps and allowed users to annotate and tag them. To study the effects of semantic tagging on tag production, the types and categories of obtained tags, and user task load, we conducted an in-lab within-subject experiment with 24 participants who annotated and tagged two distinct maps. We found that the semantic tagging implementation does not affect these parameters, while providing tagging relationships to well-defined concept definitions. Compared to label-based tagging, our technique also gathers positive and negative tagging relationships. We believe that our findings carry implications for designers who want to adopt semantic tagging in other contexts and systems on the Web.},
  author = {Haslhofer, Bernhard and Robitza, Werner and Lagoze, Carl and Guimbretiere, Francois},
  interhash = {84516aa456894b6d6adf86abd2386656},
  intrahash = {a653f1a0a1ac5084e80757ec277b1184},
  note = {cite arxiv:1304.1636Comment: 10 pages},
  title = {Semantic Tagging on Historical Maps},
  url = {http://arxiv.org/abs/1304.1636},
  year = 2013
}

@inproceedings{rezel2010swefe,
  abstract = {This paper presents SWE-FE: a suite of methods to extend folksonomies to the worldwide Sensor Web in order to tackle the emergent data rich information poor (DRIP) syndrome afflicting most geospatial applications on the Internet. SWE-FE leverages the geospatial information associated with three key components of such collaborative tagging systems: tags, resources and users. Specifically, SWE-FE provides algorithms for: i) suggesting tags for users during the tag input stage; ii) generating tag maps which provides for serendipitous browsing; and iii) personalized searching within the folksonomy. We implement SWE-FE on the GeoCENS Sensor Web platform as a case study for assessing the efficacy of our methods. We outline the evaluation framework that we are currently employing to carry out this assessment.},
  author = {Rezel, R. and Liang, S.},
  booktitle = {2010 International Symposium on Collaborative Technologies and Systems (CTS)},
  doi = {10.1109/CTS.2010.5478494},
  interhash = {9eb696593932c517873232386f8f61bf},
  intrahash = {d5b71572c7fea6504a0c0a3d84a9ecf0},
  month = may,
  pages = {349--356},
  publisher = {IEEE},
  title = {SWE-FE: Extending folksonomies to the Sensor Web},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5478494},
  year = 2010
}