Monthly Archives April 2011

Show and Tell: Find Cool People on Twitter with Steve Odom’s Plum.ly

This is a guest post by friend of the Infochimps and twnty.com founder Steve Odom (@steveodom).

Several years ago, Kevin Rose launched WeFollow.com to help you find people on Twitter near you geographically with similar interests. The problem with it is you have to go to WeFollow and input your interests. It doesn’t pull your interests directly from your Twitter profile. It’s great but yet another account with data about you that you have to manage.

When Infochimps released their Twitter People Search API allowing for full text search of any twitter data field, I realized I could use it to easily build a search engine of Twitter bios, similar to WeFollow but much more powerful. Why ask users to input additional information about themselves when their twitter profile already contains lots of identifying data about them – their name, location, and whatever they say about themselves in their bio. Being able to search on this content makes for a tool like WeFollow, but one that searches every Twitter profile and not just accounts that people entered into WeFollow.

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Overview of Open Government Budget Crisis

It’s hard to say what will become of Data.gov and USAspending.com. Researcher and Scholar Vivek Wadhwa claims the sites have plenty of support from government officials, but do they have enough support from lawmakers to stay afloat? Reports claim that budget for Data.gov and USAspending.com will plummet from $35 million to $2 million.

If there’s one thing we like to do at Infochimps, it’s collecting interesting nuggets of information for you to use. So here are some useful posts on the matter. Please share them with your friends so we can ensure support for open government:

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Overview of Data 2.0 Conference Panel “The Price of Information”

Will increased competition and the race to undercut competitors commoditize information? Is data an asset, is it a public utility, or is it a fragmented network that resists commoditization? What types of data will resist commoditization? This panel featured our CEO Nick Ducoff and discusses the future of who will buy data at what cost.

Panelists include:
Geoff Domoracki, Moderator and Founder of midVentures
Nick Ducoff, Co-Founder and CEO of Infochimps
Hjalmar Gislason, Founder and CEO of DataMarket
David Coloff,Founder and CEO of Metamarkets
Ian White, CEO of Urban Mapping

3:00 Panelists introduce themselves

3:05 Domoracki: Who are your customers, and how does your pricing strategy differ?

Ducoff: Our customers vary from developers to analysts and academics. For developers, we offer access to an API and it is pay by the drink. For analysts, pricing is generally a la carte.

Gislason says DataMarket has integrated data from open sources. It starts off free and is still free on their site. They offer additional features on top of the data, which is what users pay for. They also sell premium data that is proprietary.

White says that Urban Mapping offers cheap data, but then also offers additional curated sources that provide extra value.

Soloff says that Metamarkets focuses on monetizing analysis and visualization of data. There is an appetite for market benchmarks. People are offering data in exchange for the ability to get data from other sources.

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Overview of Data-as-a-Service Panel from Data 2.0 Conference

Data-as-a-service is something new to many outside the enterprise space. This panel from the Data 2.0 Conference discusses where this market is headed.

Geoff Domoracki, Moderator and CEO of midVentures
Jay Adelson, CEO of SimpleGeo
Nick Halstead, Founder and CEO of Mediasift
Vivek Sodera, Co-Founder of Rapleaf
Gordan Redzic, Senior Product Manager at Navteq

2:30 Panelists introduce themselves.

2:31 Domoracki asks, “What is data-as-a-service”?

Halstead says that from the moment you start using a website, information is being collected about you. Web companies are disrupting traditional data providers because it is now easier to collect millions of records for smaller players in the space. This is a new service offered to businesses.

Sodera says that the vast amount of data available opens up potentials to use data effectively for small to medium sized businesses, not just enterprises who could afford the high prices for valuable data.

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Play by Play of Data 2.0 Panel “The Advertising Equation”

What does the future of advertising look like in a real-time personalized web? This panel features:
Miten Sampat, VP of Strategy for Quova
Martin Wesley, VP of Sales and Business Development for BrightTag
Graham Mudd, VP of comScore
Russell Glass, CEO of Bizo
Zach Coehlius, Co-Founder and CEO of Triggit
Geoff Domoracki, Moderator

11:23 Domoracki: Personalized, real time ads resemble “Minority Report”. Is that vision correct and should we go that way?

Coehlius says that people don’t want to see ads that don’t pertain to them. Targeted ads make the internet a better place. “Minority Report” is a bit of a farse.

Search has understood this model for years. This is why Google has made so much money because they do search relevant ads. The rest of the web should follow suit.

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Overview of Vivek Wadhwa’s Data 2.0 Talk, “The New Information Age”

Vivek Wadhwa is a senior research associate with the Labor and Worklife Program at Harvard Law School, an executive in residence/adjunct professor at the Pratt School of Engineering at Duke University, and a visiting scholar at the School of Information at University of California at Berkeley. This is an overview of his talk at the Data 2.0 Conference. You can see the livestream of this conference at the Data 2.0 Conference website.

9:19 Introduction
According to SxSW speech by LinkedIn founder Reid Hoffman:

Web 1.0 was about “go search, get data”
Web 2.0 is about “real identities and real relationships”
Web 3.0 “Real identities generating massive amounts of data”

9:21 Data pre-web was about weather, climate, employment, phone book. This was public information but did not provides insights about people.

web 2.0 generates data about our behavior—what we watch, where we shop, where we travel, etc. “So much data is being collected about us, Big Brother would be jealous.”

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