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jerryking : infochimps   8

Accessing Open Data via APIs: Never Mind the App, Is There a Market for That?
Mark Boyd, September 4th, 2013

But is the market ready to monetize? In Big Data: A Revolution That Will Transform How We Live, Work, and Think, authors Viktor Mayer-Schönberger and Kenneth Cukier argue that at present, those with “the most value in the big data value chain” are those businesses and entrepreneurs with an innovative mindset attuned to the potential of big and open data. While still in its nascence, “the ideas and the skills seem to hold the greatest worth”, they say. However, they expect:

“…eventually most value will be in the data itself. This is because we’ll be able to do more with the information, and also because the data holders will better appreciate the potential value of the asset they possess. As a result, they’ll probably hold it more tightly than ever, and charge outsiders a high price for access.”
data_scientists  open_data  massive_data_sets  entrepreneurship  start_ups  InfoChimps  Junar  mindsets  commercialization  monetization 
january 2014 by jerryking
Data as a Renewable Commodity and Profit Center — Jason Kolb dot Com
June 6, 2011 | Jason | By Jason Kolb.

One of the reasons I love data is because there’s so much potential for mining real value from it, especially when you combine it with other, new data sources. In fact it acts a lot like a traditional commodity such as copper or wool in that someone produces it, and then someone else buys the raw material and makes something new from it. It’s unique from traditional commodities, however, in that it doesn’t get used up at all when it’s used to create something new–this makes it particularly interesting from an economic point of view.

In addition, anyone can make it, it doesn’t get used up, and the industry of using data to create new and valuable things is still so young and ripe for profit-making. In fact I think it’s one of the areas that America needs to focus on if its economy is to recover because for the most part it’s still virgin territory and it’s going to create a lot of economic value. What I really don’t want to see is foreign companies being the first to capitalize on the data as that would suck most of the value out of our economy, just what we don’t need right now.
data  commercialization  renewable  commodities  metadata  Factual  Infochimps  data_scientists  information_sources 
june 2012 by jerryking
PeteSearch: How to turn data into money
October 20, 2010 by Pete Warden. The most important unsolved
question for Big Data startups is how to make money. Here's a hierarchy
showing the stages from raw data to cold, hard cash:
(1) Data. You have a bunch of files containing info. you've gathered,
way too much for any human to ever read. You know there's a lot of
useful stuff in there though, but you can talk until you're blue in the
face & the people with the checkbooks will keep them closed. The
data itself, no matter how unique, is low value, since it will take
somebody else a lot of effort to turn it into something they can use to
make $. (2) Charts. Take that massive deluge of data and turn it into
some summary tables & simple graphs. You want to give an unbiased
overview of the info., so the tables & graphs are quite detailed.
This makes a bit more sense to the potential end-users, they can at
least understand what it is you have, and start to imagine ways they
could use it. (3) Reports; (4) Recommendations.
analysis  commercialization  data  data_driven  data_marketplaces  data_scientists  entrepreneurship  hierarchies  ideas  InfoChimps  massive_data_sets  monetization  value_creation  visualization 
july 2011 by jerryking
Data-as-a-Service: Factual, InfoChimps & Google Squared
Oct. 20, 2010, By Imran Ali . Do you have unique datasets in
your biz. that could be valuable to others?...dB apps have been
curiously absent from the mix of web worker productivity tools...a new
generation of tools are providing this functionality. DaaS providers are
emerging enabling users to create, manage & publish specialized
datasets, providing both authoring tools & opportunities to
participate in a web of data, not just of pgs...Factual bills itself as
an “open data repository” where users can upload & create datasets,
as well as add data hosted by Factual to their own sites &
apps...InfoChimps positions itself as a “data mktplace” enabling
publishers & owners of datasets to charge for their usage.
Publishers can offer free & paid datasets, charging either for API
access or for making them downloadable. Some datasets are organized into
collections from particular organizations,e.g. Wikipedia &
==> InfoChimps allows orgs. to outsource mgmt. of their open data
What's an example of a company creating a valuable dataset from scratch?
DaaS  Infochimps  Factual  data  Google_Squared  Freshbooks  massive_data_sets  databases  data_scientists  commercialization 
july 2011 by jerryking
Big Thoughts on Big Data: Infochimps
Mar. 2, 2011, | Gigaom -- Cloud Computing News | By Stacey Higginbotham
data  massive_data_sets  Infochimps  DaaS  databases  Freshbooks  data_scientists 
july 2011 by jerryking
Data markets aren't coming. They're already here
26 January 2011 | O'Reilly Radar| by Julie Steele.

Jud Valeski is cofounder and CEO of Gnip, a social media data provider
that aggregates feeds from sites like Twitter, Facebook, Flickr,
delicious, and others into one API.

Jud will be speaking at Strata next week on a panel titled "What's Mine
is Yours: the Ethics of Big Data Ownership."
Find out more about growing business of data marketplaces at a "Data
Marketplaces" panel with Ian White of Urban Mapping, Peter Marney of
Thomson Reuters and Dennis Yang of Infochimps.

What do you wish more people understood about data markets and/or the
way large datasets can be used?

Jud Valeski: First, data is not free, and there's always someone out
there that wants to buy it. As an end-user, educate yourself with how
the content you create using someone else's service could ultimately be
used by the service-provider. Second, black markets are a real problem,
and just because "everyone else is doing it" doesn't mean it's okay.
markets  data  analytics  massive_data_sets  digital_economy  content_creators  black_markets  Infochimps  Gnip  Thomson_Reuters  commercialization  data_scientists  data_marketplaces  social_data  financial_data 
may 2011 by jerryking

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