Interview: Hjálmar Gíslason, CEO of DataMarket.com

Here is an interview with Hjálmar Gíslason, CEO of Datamarket.com  . DataMarket is an active marketplace for structured data and statistics. Through powerful search and visual data exploration, DataMarket connects data seekers with data providers.

 

Ajay-  Describe your journey as an entrepreneur and techie in Iceland. What are the 10 things that surprised you most as a tech entrepreneur.

HG- DataMarket is my fourth tech start-up since at age 20 in 1996. The previous ones have been in gaming, mobile and web search. I come from a technical background but have been moving more and more to the business side over the years. I can still prototype, but I hope there isn’t a single line of my code in production!

Funny you should ask about the 10 things that have surprised me the most on this journey, as I gave a presentation – literally yesterday – titled: “9 things nobody told me about the start-up business”

They are:
* Do NOT generalize – especially not to begin with
* Prioritize – and find a work-flow that works for you
* Meet people – face to face
* You are a sales person – whether you like it or not
* Technology is not a product – it’s the entire experience
* Sell the current version – no matter how amazing the next one is
* Learn from mistakes – preferably others’
* Pick the right people – good people is not enough
* Tell a good story – but don’t make them up

I obviously elaborate on each of these points in the talk, but the points illustrate roughly some of the things I believe I’ve learned … so far 😉

9 things nobody told me about the start-up business

Ajay-

Both Amazon  and Google  have entered the public datasets space. Infochimps  has 14,000+ public datasets. The US has http://www.data.gov/

So clearly the space is both competitive and yet the demand for public data repositories is clearly under served still. 

How does DataMarket intend to address this market in a unique way to differentiate itself from others.

HG- DataMarket is about delivering business data to decision makers. We help data seekers find the data they need for planning and informed decision making, and data publishers reaching this audience. DataMarket.com is the meeting point, where data seekers can come to find the best available data, and data publishers can make their data available whether for free or for a fee. We’ve populated the site with a wealth of data from public sources such as the UN, Eurostat, World Bank, IMF and others, but there is also premium data that is only available to those that subscribe to and pay for the access. For example we resell the entire data offering from the EIU (Economist Intelligence Unit) (link: http://datamarket.com/data/list/?q=provider:eiu)

DataMarket.com allows all this data to be searched, visualized, compared and downloaded in a single place in a standard, unified manner.

We see many of these efforts not as competition, but as valuable potential sources of data for our offering, while others may be competing with parts of our proposition, such as easy access to the public data sets.

 

Ajay- What are your views on data confidentiality and access to data owned by Governments funded by tax payer money.

HG- My views are very simple: Any data that is gathered or created for taxpayers’ money should be open and free of charge unless higher priorities such as privacy or national security indicate otherwise.

Reflecting that, any data that is originally open and free of charge is still open and free of charge on DataMarket.com, just easier to find and work with.

Ajay-  How is the technology entrepreneurship and venture capital scene in Iceland. What things work and what things can be improved?

HG- The scene is quite vibrant, given the small community. Good teams with promising concepts have been able to get the funding they need to get started and test their footing internationally. When the rapid growth phase is reached outside funding may still be needed.

There are positive and negative things about any location. Among the good things about Iceland from the stand point of a technology start-up are highly skilled tech people and a relatively simple corporate environment. Among the bad things are a tiny local market, lack of skills in international sales and marketing and capital controls that were put in place after the crash of the Icelandic economy in 2008.

I’ve jokingly said that if a company is hot in the eyes of VCs it would get funding even if it was located in the jungles of Congo, while if they’re only lukewarm towards you, they will be looking for any excuse not to invest. Location can certainly be one of them, and in that case being close to the investor communities – physically – can be very important.

We’re opening up our sales and marketing offices in Boston as we speak. Not to be close to investors though, but to be close to our market and current customers.

Ajay- Describe your hobbies when you are not founding amazing tech startups.

HG- Most of my time is spent working – which happens to by my number one hobby.

It is still important to step away from it all every now and then to see things in perspective and come back with a clear mind.

I *love* traveling to exotic places. Me and my wife have done quite a lot of traveling in Africa and S-America: safari, scuba diving, skiing, enjoying nature. When at home I try to do some sports activities 3-4 times a week at least, and – recently – play with my now 8 month old son as much as I can.

About-

http://datamarket.com/p/about/team/

Management

Hjalmar GislasonHjálmar Gíslason, Founder and CEO: Hjalmar is a successful entrepreneur, founder of three startups in the gaming, mobile and web sectors since 1996. Prior to launching DataMarket, Hjalmar worked on new media and business development for companies in the Skipti Group (owners of Iceland Telecom) after their acquisition of his search startup – Spurl. Hjalmar offers a mix of business, strategy and technical expertise. DataMarket is based largely on his vision of the need for a global exchange for structured data.

hjalmar.gislason@datamarket.com

To know more, have a quick  look at  http://datamarket.com/

Data Documentation Initiative

Here is a nice initiative in standardizing data documentation for social sciences (which can be quite a relief to legions of analysts)

http://www.ddialliance.org/what

 

 

 

 

Benefits of DDI

The DDI facilitates:

  • Interoperability. Codebooks marked up using the DDI specification can be exchanged and transported seamlessly, and applications can be written to work with these homogeneous documents.
  • Richer content. The DDI was designed to encourage the use of a comprehensive set of elements to describe social science datasets as completely and as thoroughly as possible, thereby providing the potential data analyst with broader knowledge about a given collection.
  • Single document – multiple purposes. A DDI codebook contains all of the information necessary to produce several different types of output, including, for example, a traditional social science codebook, a bibliographic record, or SAS/SPSS/Stata data definition statements. Thus, the document may be repurposed for different needs and applications. Changes made to the core document will be passed along to any output generated.
  • On-line subsetting and analysis. Because the DDI markup extends down to the variable level and provides a standard uniform structure and content for variables, DDI documents are easily imported into on-line analysis systems, rendering datasets more readily usable for a wider audience.
  • Precision in searching. Since each of the elements in a DDI-compliant codebook is tagged in a specific way, field-specific searches across documents and studies are enabled. For example, a library of DDI codebooks could be searched to identify datasets covering protest demonstrations during the 1960s in specific states or countries.
Also see-
  1. http://www.ddialliance.org/Specification/DDI-Codebook/2.1/DTD/Documentation/DDI2-1-tree.html
  2. http://www.ddialliance.org/Specification/DDI-Lifecycle/3.1/

 

Building a Regression Model in R – Use #Rstats

One of the most commonly used uses of Statistical Software is building models, and that too logistic regression models for propensity in marketing of goods and services.

 

If building a model is what you do-here is a brief easy essay on  how to build a model in R.

1) Packages to be used-

For smaller datasets

use these

  1. CAR Package http://cran.r-project.org/web/packages/car/index.html
  2. GVLMA Package http://cran.r-project.org/web/packages/gvlma/index.html
  3. ROCR Package http://rocr.bioinf.mpi-sb.mpg.de/
  4. Relaimpo Package
  5. DAAG package
  6. MASS package
  7. Bootstrap package
  8. Leaps package

Also see

http://cran.r-project.org/web/packages/rms/index.html or RMS package

rms works with almost any regression model, but it was especially written to work with binary or ordinal logistic regression, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.

For bigger datasets also see Biglm http://cran.r-project.org/web/packages/biglm/index.html and RevoScaleR packages.

http://www.revolutionanalytics.com/products/enterprise-big-data.php

2) Syntax

  1. outp=lm(y~x1+x2+xn,data=dataset) Model Eq
  2. summary(outp) Model Summary
  3. par(mfrow=c(2,2)) + plot(outp) Model Graphs
  4. vif(outp) MultiCollinearity
  5. gvlma(outp) Heteroscedasticity using GVLMA package
  6. outlierTest (outp) for Outliers
  7. predicted(outp) Scoring dataset with scores
  8. anova(outp)
  9. > predict(lm.result,data.frame(conc = newconc), level = 0.9, interval = “confidence”)

 

For a Reference Card -Cheat Sheet see

http://cran.r-project.org/doc/contrib/Ricci-refcard-regression.pdf

3) Also read-

http://cran.r-project.org/web/views/Econometrics.html

http://cran.r-project.org/web/views/Robust.html

 

Use R for Business- Competition worth $ 20,000 #rstats

All you contest junkies, R lovers and general change the world people, here’s a new contest to use R in a business application

http://www.revolutionanalytics.com/news-events/news-room/2011/revolution-analytics-launches-applications-of-r-in-business-contest.php

REVOLUTION ANALYTICS LAUNCHES “APPLICATIONS OF R IN BUSINESS” CONTEST

$20,000 in Prizes for Users Solving Business Problems with R

 

PALO ALTO, Calif. – September 1, 2011 – Revolution Analytics, the leading commercial provider of R software, services and support, today announced the launch of its “Applications of R in Business” contest to demonstrate real-world uses of applying R to business problems. The competition is open to all R users worldwide and submissions will be accepted through October 31. The Grand Prize winner for the best application using R or Revolution R will receive $10,000.

The bonus-prize winner for the best application using features unique to Revolution R Enterprise – such as itsbig-data analytics capabilities or its Web Services API for R – will receive $5,000. A panel of independent judges drawn from the R and business community will select the grand and bonus prize winners. Revolution Analytics will present five honorable mention prize winners each with $1,000.

“We’ve designed this contest to highlight the most interesting use cases of applying R and Revolution R to solving key business problems, such as Big Data,” said Jeff Erhardt, COO of Revolution Analytics. “The ability to process higher-volume datasets will continue to be a critical need and we encourage the submission of applications using large datasets. Our goal is to grow the collection of online materials describing how to use R for business applications so our customers can better leverage Big Analytics to meet their analytical and organizational needs.”

To enter Revolution Analytics’ “Applications of R in Business” competition Continue reading “Use R for Business- Competition worth $ 20,000 #rstats”

So how useful is Data.gov anyway

As per official statistics, not many people download data from it .

Why dont they just donate the data and save taxpayers some money

http://www.data.gov/metric

Summary

Agency/Sub-Agency/Organization Raw Datasets
(high-value)
Tools
(high-value)
Geodata Total Latest Entry # of times downloaded
within the last week*
TOTAL
3,486 (2,163) 1,071 (393) 386,429 390,986 08/24/2011 0

* These numbers represent the number of times a user has clicked on the “XML” or “CSV” (for example) links in the Raw Data Catalogs to download datasets and user downloads of tools in the Tool Catalog available in these categories.

But apparently lots of people like it still

http://www.data.gov/metric/visitorstats/monthlyredirecttrend

More list of public data repositories-

Google http://www.google.com/publicdata/directory

DataMob http://datamob.org/datasets

Amazon http://aws.amazon.com/publicdatasets/

DataMarket http://datamarket.com/

Infochimps http://www.infochimps.com/

From SEC, the Edgar  http://www.sec.gov/edgar/searchedgar/companysearch.html

More lists of lists

http://www.kdnuggets.com/2011/02/free-public-datasets.html

But who  gets more downloads last week than Data.gov !

 

 

 

 

 

 

 

 

 

 

Workflows and MyExperiment.org

Here is a great website for sharing workflows – it is called MyExperiment.org and it can also include Work flows from many software.

myExperiment currently has 4742 members270 groups1842 workflows423 files and 173 packs

Could it also include workflow from Red-R from #rstats or Enterprise Miner

Continue reading “Workflows and MyExperiment.org”

Machine Learning Contest

New Contest at http://www.ecmlpkdd2011.org/dcOverview.php

 

 

Discovery Challenge Overview

Organization | Overview | Task and DatasetsTimeline

 

General description: tasks and dataset

VideoLectures.net is a free and open access multimedia repository of video lectures, mainly of research and educational character. The lectures are given by distinguished scholars and scientists at the most important and prominent events like conferences, summer schools, workshops and science promotional events from many fields of Science. The portal is aimed at promoting science, exchanging ideas and fostering knowledge sharing by providing high quality didactic contents not only to the scientific community but also to the general public. All lectures, accompanying documents, information and links are systematically selected and classified through the editorial process taking into account also users’ comments.

The ECML-PKDD 2011 Discovery Challenge is organized in order to improve the website’s current recommender system. The challenge consists of two main tasks and a “side-by” contest. The provided data is for both of the tasks, and it is up to the contestants how it will be used for learning (building up) a recommender.

Due to the nature of the problem, each of the tasks has its own merit: task 1 simulates new-user and new- item recommendation (cold-start mode), task 2 simulates clickstream based recommendation (normal mode). Continue reading “Machine Learning Contest”

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