According to a 2009 Gartner study, businesses estimated that they are losing an average of $8.2 million per year because of poor data quality. Five years on, we are storing, managing and relying on more data than ever before.
Open Data, Quality and Visualization with Données Ouvertes Montréal
Wednesday, Oct 22, 2014, 5:30 PM
Radialpoint 2050 Bleury, Suite 300 Montréal, QC
58 Data hackers Attending
This month, we will be talking about open data.
We will have a main presentation from Diane Mercier about Montreal's open data portal followed by an example of how to visualize Montreal's open bike data in R from Toby Hocking. For those of you that followed our last meetup, a team has implemented a new solution to Kaggle's Titanic competition. They...
Last year saw the emergence of the first Massive Open Online Courses (MOOCs) focused on geospatial topics. Developed at Penn State, Maps and the Geospatial Revolution enrolled over 48,000 students from 150+ countries. In addition to offering a new (free) way to access skills and...
"Crowdsourcing for data integration: quality assurance, data fusion and conflation issues"
The value of crowdsourcing including citizen science data has been recognised as providing timely and complementary data in many different situations but this value is diminished as the data is often considered of low quality and potentially biased compared to authoritative. Quality assurance of crowdsourced data is therefore looked for either at the data collection stage or as a post-process. This quality assurance needs also to consider future use of this data (usability criterion) and particularly its combination under conflation or fusion schemes with authoritative data within spatial data infrastructures.
Contributions related to quality assurance considered in tandem with conflation or fusion within the remits of the ISSDQ for any crowdsourcing setting from citizen science to web crawling will be welcome to this session. Particular discussions around the following topics will be looked for:
-fusion and conflation algorithms in environmental policy making -quality standards and other metrics for fusion algorithms
-decision making improvement from data conflation/fusion of authoritative data and crowdsourced data
-metaquality aspects in data conflation/fusion and impact in decision making -impact of the multivariate role of the quality elements
Submissions should fit to the ISPRS Meeting Template - http://www.isprs.org/documents/orangebook/app5.aspx - and should range between 4 and 6 pages. You will be asked to mention the session where you wish to present your paper where you will mention “Crowdsourcing for data integration: quality assurance, data fusion and conflation issues”. This follows the general call for papers http://www.isprs- geospatialweek2015.org/files/ISSDQ2015_CallForPaperAndSession.pdf where more information on the conference can be found.
Note that the ISPRS Geospatial Week 2015 is from the 28th of September to the 3rd of October with the opportunity to register to multiple events/conferences.
Researchers say they can predict the outbreak of an infectious disease by watching people search Wikipedia for information and symptoms. The technique could yield a global disease-forecasting system, they suggest.
On the corroborating crowdsourced information! or even here forecasting!
No word has a value that can be identified independently of what else is in its vicinity.; Author: Marc Clifton; Updated: 25 Oct 2014; Section: Algorithms & Recipes; Chapter: General Programming; Updated: 25 Oct 2014...
Second one in the Guardian is by a PhD student Sarah Byrne titled Interdisciplinary research: why it's seen as a risky route. It discusses, fairly accurately, that while funding agencies and academic leaders give lip service to ...
Swarm Behavior - A single ant or bee isn't smart, but their colonies are. The study of swarm intelligence is providing insights that can help humans manage complex systems, from truck routing to military robots.
First beautiful picture ... and if we re-scoop this it may become buzz ... then we will have acted like a swarm does! but I guess what is really interesting is when something goes buzz and modify itself at the same time and then another buzz mixes with it creating a quite new ... that's quite complex as one cna only identify the origin at the beginning of the mix of things / ideas etc.!
This is the BPMN representation of the SIEL model (Loireau et al. (2006)) some interesting error propagation studies betwen categories (e.g. soil), quantitative attribute (e.g. biomass), positions (e.g. vegetaion map) etc ...are currently investigated. These would make such scientific geoworklfow models very useful for decision making.
Can meta-propagation with multivariate uptake using copula distribution be more than a theoretical solution?
I think that would do a very interesting PhD. email me if you are interested!
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