Je ne connaissais pas #wolfram_alpha. Moteur de... #connaissance, #analyse, #interprétation ? En langage naturel. Vraiment impressionnant, mange aussi des textes, des tableaux, des images...
http://www.wolframalpha.com
#moteur #recherche #sémantique #langage_naturel
#DMS : #Data management systems
http://blog.okfn.org/2012/03/09/from-cms-to-dms-c-is-for-content-d-is-for-data
What must a DMS do?
A mature DMS will let people do all the following things:
Load and update data from any source (ETL)
Store datasets and index them for querying
View, analyse and update data in a tabular interface (spreadsheet)
Visualise data, for example with charts or maps
Analyse data, for example with statistics and machine learning
Organise many people to enter or correct data (crowd-sourcing)
Measure and ensure the quality of data, and its provenance
Permissions; data can be open, private or shared
Find datasets, and organise them to help others find them
Sell data, sharing processing costs between users
In short, it’s what the elite data wrangling teams inside places like #Wolfram Alpha and Google’s #Metaweb teams do. But made easier and more visible using standardised tools and protocols.
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Windows / OSX (+ Excel / #LibreOffice / …) – the desktop serves as a (good enough so far) DMS
CKAN software – started as a data catalog, but has grown into more and powers the DataHub, a community data hub and market. Created by the Open Knowledge Foundation
ScraperWiki- coming from the viewpoint of a programmer, good at ETL
Infochimps/DataMarket – approaching it as a data marketplace
BuzzData – specialising in the social aspects
Tableau Public – specialising in visualisation
Google Spreadsheets – coming from the web spreadsheet direction
Microsoft Data Hub – corporate information management
PANDA – making a DMS for newsrooms