Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

January 15, 2013

Maps in R: Plotting data points on a map

Filed under: Geographic Data,Geography,Mapping,Maps,R — Patrick Durusau @ 8:30 pm

Maps in R: Plotting data points on a map by Max Marchi.

From the post:

In the introductory post of this series I showed how to plot empty maps in R.

Today I’ll begin to show how to add data to R maps. The topic of this post is the visualization of data points on a map.

Max continues this series with datasets from airports in Europe and demonstrates how to map the airports to geographic locations. He also represents the airports with icons that correspond to their traffic statistics.

Useful principles for any data set with events that can be plotted against geographic locations.

Parades, patrols, convoys, that sort of thing.

January 6, 2013

CartoDB makes D3 maps a breeze

Filed under: CartoDB,D3,Geographic Data,Mapping,Maps — Patrick Durusau @ 9:59 pm

CartoDB makes D3 maps a breeze

From the post:

Anybody who loves maps and data can’t help but notice all the beautiful visualizations people are making with D3 right now. Huge thanks to Mike Bostock for such a cool technology.

We have done a lot of client-side rendering expirements over the past year or so and have to say, D3 is totally awesome. This is why we felt it might be helpful to show you how easy it is to use D3 with CartoDB. In the near future, we’ll be adding a few tutorials for D3 to our developer pages, but for now, let’s have a look.

Very impressive.

But populating a map with data isn’t the same as creating a useful map with data.

Take a look at the earthquake example.

What data would you add to it to make the information actionable?

January 5, 2013

Map Projections

Filed under: Cartography,D3,Graphics,Mapping,Maps — Patrick Durusau @ 7:36 am

Map Projections by Jason Davies.

If you are interested in map projections or D3, this page is a real delight!

Jason has draggable examples of:

Along with various demonstrations:

OK, one image to whet your appetite!

Waterman Butterfly Map
Waterman Butterfly Map

Follow the image to its homepage, then drag the image. I think you will be pleased.

December 31, 2012

Let’s Make a Map

Filed under: Mapping,Maps — Patrick Durusau @ 4:31 pm

Let’s Make a Map by Mike Bostock.

From the post:

In this tutorial, I’ll cover how to make a modest map from scratch using D3 and TopoJSON. I’ll show you a few places where you can find free geographic data online, and how to convert it into a format that is both efficient and convenient for display. I won’t cover thematic mapping, but the map we’ll make includes labels for populated places and you can extend this technique to geographic visualizations such as graduated symbol maps and choropleths.

Excellent introduction!

December 30, 2012

TopoJSON

Filed under: Geographic Data,Geography,Mapping,Maps — Patrick Durusau @ 8:34 pm

TopoJSON

From the webpage:

TopoJSON is an extension of GeoJSON that encodes topology. Rather than representing geometries discretely, geometries in TopoJSON files are stitched together from shared line segments called arcs. TopoJSON eliminates redundancy, offering much more compact representations of geometry than with GeoJSON; typical TopoJSON files are 80% smaller than their GeoJSON equivalents. In addition, TopoJSON facilitates applications that use topology, such as topology-preserving shape simplification, automatic map coloring, and cartograms.

I stumbled on this by viewing TopoJSON Points.

Displaying airports in the example but could be any geographic feature.

See the wiki for more details.

December 27, 2012

Majuro.JS [Useful Open Data]

Filed under: Mapping,Maps,Open Data,Visualization — Patrick Durusau @ 11:13 am

Majuro.JS by Nick Doiron.

From the homepage:

Majuro.JS helps you make detailed, interactive maps with open buildings data.

Great examples on the homepage but I prefer the explanation at Github.

This is wicked cool!

This type of open data I can see as the basis for “innovation.”

Resulting in a target for rich annotation by a topic map based application.

Outing Gun Owners?

Filed under: Mapping,Maps — Patrick Durusau @ 5:45 am

Map: Where are the gun permits in your neighborhood?

From the post:

The map indicates the addresses of all pistol permit holders in Westchester and Rockland counties. Each dot represents an individual permit holder licensed to own a handgun — a pistol or revolver. The data does not include owners of long guns — rifles or shotguns — which can be purchased without a permit. Being included in this map does not mean the individual at a specific location owns a weapon, just that they are licensed to do so.

Data for all permit categories, unrestricted carry, premises, business, employment, target and hunting, is included, but permit information is not available on an individual basis.

To create the map, The Journal News submitted Freedom of Information requests for the names and addresses of all pistol permit holders in Westchester, Rockland and Putnam. By state law, the information is public record.

The mapping has provoked considerable discussion (35,153 Facebook recommendations as of December 27, 2012).

Several additional or alternative mappings come to mind:

  • Mapping the addresses of people arrested for gun related violence and intersecting those addresses with the gun permit addresses.
  • Mapping the addresses of people arrested for drug offenses and intersecting those addresses with the gun violence addresses.
  • Or using a topic map to create more detailed maps of associations (political contributions?) and other data.

Who do you want to “out” and on what basis?

I found this following this post by Ed Chi, which in turn lead to a post by Jeremiah Owyang here, who remarks: “Perhaps one of the most controversial things I’ve seen in tech.”

I fail to see the “controversy.” The permit owners did in fact give their addresses as part of public records.

What part of not disclosing information you want to remain private seems unclear?

December 20, 2012

Maps in R: Introduction – Drawing the map of Europe

Filed under: Mapping,Maps,R — Patrick Durusau @ 7:36 pm

Maps in R: Introduction – Drawing the map of Europe by Max Marchi.

How many lines of R code to draw a map of Europe?

Write down your answer.

Now follow the link to the original post.

Close? Far away?

December 16, 2012

Asterank: an Accurate 3D Model of the Asteroids in our Solar System

Filed under: Astroinformatics,Mapping,Maps — Patrick Durusau @ 9:02 pm

Asterank: an Accurate 3D Model of the Asteroids in our Solar System by Andrew Vande Moere.

From the post:

Asterank 3D Asteroid Orbit Space Simulation [asterank.com], developed by software engineer Ian Webster, is a 3D WebGL-based model of the first 5 planets and the 30 most valuable asteroids, together with their respective orbits in our inner solar system.

Asterank’s database contains the astronomically accurate locations, as well as some economic and scientific information, of over 580,000 asteroids in our solar system. Each asteroid is accompanied by its “Value of Materials”, in terms of the metals, volatile compounds, or water it seem to contain. The “Cost of Operations” provides a financial estimation of how much it would cost to travel to the asteroid and move the materials back to Earth.

Will you be ready as semantic diversity spreads from the Earth out into the Solar System?

December 14, 2012

OpenTopography Project

Filed under: LiDAR,Mapping,Maps,Topography — Patrick Durusau @ 10:19 am

OpenTopograpy: A Portal to High-Resolution Topography Data and Tools

Which ironically has its “spotlight” on:

Discover Lidar Data Hosted by NCALM and USGS from OpenTopography

Which is summarized in the “spotlight” as:

The OpenTopography Find Data page is updated to display not only OpenTopography hosted-data, but also provides linkages to data hosted at the NCALM Data Distribution Center and USGS Center for Lidar Coordination and Knowledge (CLICK). The goal of this collaboration is to make it easier for lidar users to discover and link to online sources of data regardless of host.

Non-self referential and/or paid links that lead to additional content of interest to the reader.

If enough people did that, why we would have a useful WWW.

PS: Introduction to LiDAR video by the Idaho State University Geoscience Department

December 6, 2012

50 years of Rolling Stones tours

Filed under: Mapping,Maps — Patrick Durusau @ 11:38 am

50 years of Rolling Stones tours by Nathan Yau.

From the post:

CartoDB mapped every Rolling Stones tour from 1963 to 2007.

This is awesome.

More to follow.

December 3, 2012

“I Have Been Everywhere” by Johnny Cash

Filed under: Humor,Mapping,Maps,Music — Patrick Durusau @ 3:31 pm

A Real-Time Map of the Song “I Have Been Everywhere” by Johnny Cash

From the post:

Freelance web developer Iain Mullan has developed a map mashup titled “Johnny Cash Has Been EVERYWHERE (Man)!” [iainmullan.com].

The concept is simple yet funny: using a combination of an on-demand music service, an online lyrics catalog and some Google Maps programming magic, all the cities mentioned in the song are displayed simultaneously as they are mentioned during the song, as performed by Johnny Cash.

Some maps are meant to amuse.

BTW, Johnny prefers Safari or Chrome (as in won’t work with FireFox and I suspect IE as well).

December 2, 2012

Grow up, use Mindmaps [Or, Grow confident and use what works for you.]

Filed under: Mapping,Maps,Mind Maps — Patrick Durusau @ 3:59 pm

Grow up, use Mindmaps by Anne Balke.

From the post:

No matter what the industry, there is one thing that all business owners have in common. We need to find ways to best utilize our time and to stay organized. Whether you’re just starting out or have had a successful business for years, in order to grow you need to plan for the future. The trick is finding a way to organize all the information that you gather along the way so that you can effectively develop a plan of action. You also need to be able to share your ideas and vision with others in a way that is concise and easy to follow.

The Solution – Mind Mapping

For small-business owners, mind maps are a useful tool for everything from brainstorming to strategic planning. Mind mapping is a way to visualize what you need to do and helps to organize information the same way that your brain does. NovaMind explains it quite well:

Our brains like thinking in pictures…The left half thinks linearly following direct linkages to related ideas. Our right brain likes to see the whole picture with colors and flow. A Mind Map caters to both sides of the brain… [making] it a very good way of storing and recalling information, presenting things to other people, and brainstorming new ideas.

I wasn’t aware the mind map folks had solved the problem of how brains work. Someone needs to call MIT to let them in on the news. 😉

Mind maps can be useful and may even be an authoring step prior to creation of a topic map. But a universal panacea, their not.

I won’t ever make a very good software zealot. What software is best for you depends on your requirements and resources.

It is dishonest, intellectually and morally to pretend otherwise.

If you are organizing a Christmas play for the approaching holidays, a topic map would do the job. But a spiral notebook and #2 pencil (with a pennalet for storage) has a shallower learning curve.

I would rephrase the title just a bit: Grow confident, use software that meets your needs, not what’s “hot” or popular.

November 28, 2012

xkcd: Calendar of meaningful dates

Filed under: Graphics,Mapping,Visualization — Patrick Durusau @ 6:37 am

xkcd: Calendar of meaningful dates by Nathan Yau.

From the post:

Using the Google ngrams corpus, xkcd sized the days of the year based on usage volume. Lots of firsts of the month and September 11th.

Interesting presentation of date usage in English language books since 2000.

Suggestive though of other applications.

Such as plotting the number of sick days taken by particular departments? Or on what day of the week?

Thinking product releases scheduled for when staff isn’t getting sick or caught up after being out.

Calendars are familiar objects and for some types of data, might make a useful mapping target/interface.

iFinder (Knowledge Maps)

Filed under: iFinder,Mapping,Maps — Patrick Durusau @ 6:06 am

iFinder (Knowledge Maps)

From the webpage:

Knowledge Maps

Search from a different angle

As we know from current studies and user data analyses of search engine providers, most users enter max. two terms to start their search. By using the Knowledge Map, it is no longer necessary to enter even a single search term – just by a few mouse clicks the user can targetedly and comprehensibly reach the desired search result.

Your corporate knowledge at a glance

The IntraFind solution “Knowledge Map” offers a user-friendly surface for doing research in company internal data sources.

All available data are clearly visualized in a “360 degree view” and can be quickly and easily narrowed to the desired hit document just by mouse click without the need to enter one single search term.

The product guide for IntraFind’s Knowlege Map enhancement for iFinder has several riffs adaptable to promoting topic maps.

Difficult to tell from the product literature, which was sparser than most, what lies under the hood. Appears to be a metadata harvesting/navigation solution.

Did not see any signs of the ability to share/combine mappings together.

If you took this as a baseline, the value of mapping, then topic maps are a value-add to traditional mapping.

November 25, 2012

HIVE: Handy Integration and Visualisation of multimodal Experimental Data

Filed under: Bioinformatics,Biomedical,Graphs,Mapping,Merging,Visualization — Patrick Durusau @ 2:05 pm

HIVE: Handy Integration and Visualisation of multimodal Experimental Data

From the webpage:

HIVE is an Add-on for the VANTED system. VANTED is a graph editor extended for the visualisation and analysis of biological experimental data in context of pathways/networks. HIVE stands for

Handy Integration and Visualisation of multimodal Experimental Data

and extends the functionality of VANTED by adding the handling of volumes and images, together with a workspace approach, allowing one to integrate data of different biological data domains.

You need to see the demo video to appreciate this application!

It offers import of data, mapping rules to merge data from different data sets, easy visualization as a graph and other features.

Did I mention it also has 3-D image techniques as well?

PS: Yes, it is another example of “Who moved my acronym?”

November 20, 2012

Gaza-Israel crisis 2012: every verified incident mapped

Filed under: Government,Mapping,Maps — Patrick Durusau @ 7:42 pm

Gaza-Israel crisis 2012: every verified incident mapped by Ami Sedghi, John Burn-Murdoch and Simon Rogers.

What has happened in Gaza and Israel since the assassination of Hamas leader Ahmed al-Jabari last week? This map shows all the verified incidents reported by news sources and wires across the region since then. Click on a dot to see an event – or download data for yourself. Search an address or share view to get the precise url

How can you help?

If you know of an event we’ve missed, help us add it to the map by giving us the details below at this Google Form or email us data@guardian.co.uk. We’re also looking for your photos and videos

Nice to know someone trusts us with the real data. Instead of sound bite summaries.

November 19, 2012

Georeferencer: Crowdsourced Georeferencing for Map Library Collections

Filed under: Crowd Sourcing,Geo-Indexing,Geographic Data,Geographic Information Retrieval,Geography,Georeferencing,Mapping,Maps — Patrick Durusau @ 4:56 pm

Georeferencer: Crowdsourced Georeferencing for Map Library Collections by Christopher Fleet, Kimberly C. Kowal and Petr Přidal.

Abstract:

Georeferencing of historical maps offers a number of important advantages for libraries: improved retrieval and user interfaces, better understanding of maps, and comparison/overlay with other maps and spatial data. Until recently, georeferencing has involved various relatively time-consuming and costly processes using conventional geographic information system software, and has been infrequently employed by map libraries. The Georeferencer application is a collaborative online project allowing crowdsourced georeferencing of map images. It builds upon a number of related technologies that use existing zoomable images from library web servers. Following a brief review of other approaches and georeferencing software, we describe Georeferencer through its five separate implementations to date: the Moravian Library (Brno), the Nationaal Archief (The Hague), the National Library of Scotland (Edinburgh), the British Library (London), and the Institut Cartografic de Catalunya (Barcelona). The key success factors behind crowdsourcing georeferencing are presented. We then describe future developments and improvements to the Georeferencer technology.

If your institution has a map collection or if you are interested in maps at all, you need to read this article.

There is an introduction video if you prefer: http://www.klokantech.com/georeferencer/.

Either way, you will be deeply impressed by this project.

And wondering: Can the same lessons be applied to crowd source the creation of topic maps?

November 16, 2012

Maps before maps

Filed under: Mapping,Maps — Patrick Durusau @ 6:08 am

Maps before maps by Nathan Yau.

From the post:

Amanda Uren has a fun collection of map-like scans from the 11th century. Some of them are geographic, but most of them are more like rough sketches of how the individual saw the area the image represents. It’s like those stereotype maps that people like to make, except no one’s trying to be funny.

I recognized a few of the maps but not enough to be useful. Annotations with names and bibliographic information would greatly improve the usefulness of these maps, at least to me.

And they are maps. Not “maps before maps.” Maps always represent a point of view.

Modernity’s obsession with “correct” maps is a symptom of its imperialist ideology and its need to exclude alternative viewpoints.

November 13, 2012

Mapping Racist Tweets

Filed under: Mapping,Maps,Tweets — Patrick Durusau @ 2:54 pm

Where America’s Racist Tweets Come From by Megan Garber.

WARNING: The cited article has very racist and offensive tweets. They are reproduced to illustrate the technique, not to promote racism.

Megan reports on the work of Floating Sheep, geography academics.

Surprising thing about the geographic distribution (it’s pretty much all over the nation) is the lack of racist tweets from Montana. Where all the survivalist types have bunkered up.

Then I remembered, they don’t have Internet access in log and dirt bunkers. Probably no electricity or running water as well. Some politics are their own reward. 😉

You may also appreciate the longer original post at Floating Sheep: Mapping Racist Tweets in Response to President Obama’s Re-election.

Illustrates mapping of tweets by geo-locations.

Mapping against other characteristics of geo-locations could be interesting as well.

I first saw this in a tweet by Ed Chi.

November 9, 2012

Cartograms for Topic Maps?

Filed under: Cartogram,Cartography,Mapping,Maps — Patrick Durusau @ 7:18 am

Simon St. Laurent tweeted a link to: Maps of the 2012 US presidential election results by M. E. J. Newman.

Newman used cartograms to create presentations of the 2012 U.S. presidential election results. (Cartograms substitute another variable for land area in the presentation.)

Newman’s maps correct the distortion that has most of the U.S. colored “red,” when in fact the “blue” candidate, Obama, carried both the popular and electorial vote.

I don’t recall any topic map display that I would call cartograms. You?

Leaving aside a cartogram applied to a geographic map as an interface to a topic map, how else to apply cartograms to a topic map?

Depends on the characteristics of the topics but are there general principles? Even for classes of characteristics?

October 30, 2012

The one million tweet map

Filed under: Geography,Mapping,Maps,Tweets — Patrick Durusau @ 2:43 pm

The one million tweet map

Displays the last one million tweets by geographic location, plus the top five (5) hashtags.

So tweets are not just 140 or less character strings, they are locations as well. Wondering how far you can take re-purposing of a tweet?

Powered by Maptimize.

I first saw this at Mashable.com.

BTW, I don’t find the Adobe Social ad (part of the video at Mashable) all that convincing.

You?

October 25, 2012

Insisting on beautiful maps

Filed under: Cartography,Mapping,Maps — Patrick Durusau @ 3:00 pm

Insisting on beautiful maps by Nathan Yau.

Nathan calls our attention to the publication of:

the Atlas of Design, published by the North American Cartographic Information Society,….

Definitely be on the short list of books for the holiday season!

October 11, 2012

Conflict History: All Human Conflicts on a Single Map [Battle of Jericho -1399-04-20?]

Filed under: Geography,History,Mapping,Maps — Patrick Durusau @ 3:44 pm

Conflict History: All Human Conflicts on a Single Map

From the post:

Conflict History [conflicthistory.com], developed by TecToys, summarizes all major human conflicts onto a single world map – from the historical wars way before the birth of Christ, until the drone attacks in Pakistan that are still happening today. The whole interactive map is build upon data retrieved from Google and Freebase open data services.

The world map is controlled by an interactive timeline. An additional search box allows more focused exploration by names or events, while individual conflict titles or icons can be selected to reveal more detailed information, all geographically mapped.

I had to run it back a good ways before I could judge its coverage.

I am not sure about the Battle of Jericho occurring on 04-20 in 1399 BCE. That seems a tad precise.

Still, it is an interesting demonstration of mapping technology.

For Eurocentric points, can you name the longest continuous period of peace (according to European historians)?

…[A] Common Operational Picture with Google Earth (webcast)

Filed under: Geographic Data,Geographic Information Retrieval,Google Earth,Mapping,Maps — Patrick Durusau @ 10:01 am

Joint Task Force – Homeland Defense Builds a Common Operational Picture with Google Earth

October 25, 2012 at 02:00 PM Eastern Daylight Time

The security for the Asia-Pacific Economic Collaboration summit in 2011 in Honolulu, Hawaii involved many federal, state & local agencies. The complex task of coordinating information sharing among agencies was the responsibility of Joint Task Force – Homeland Defense (JTF-HD). JTF-HD turned to Google Earth technology to build a visualization capability that enabled all agencies to share information easily & ensure a safe and secure summit.

What you will learn:

  • Best practices for sharing geospatial information among federal, state & local agencies
  • How to incorporate data from many sources into your own Google Earth globe
  • How do get accurate maps with limited bandwidth or no connection at all.

Speaker: Marie Kennedy, Joint Task Force – Homeland Defense

Sponsored by Google.

In addition to the techniques demonstrated, I suspect the main lesson will be leveraging information/services that already exist.

Or information integration if you prefer a simpler description.

Information can be integrated by conversion or mapping.

Which one you choose depends upon your requirements and the information.

Reusable information integration (RI2), where you leverage your own investment, well, that’s another topic altogether. 😉

Ask: Are you spending money to be effective or spending money to maintain your budget relative to other departments?

If the former, consider topic maps. If the latter, carry on.

October 7, 2012

The Forgotten Mapmaker: Nokia… [Lessons for Semantic Map Making?]

Filed under: Mapping,Maps,Semantics — Patrick Durusau @ 7:57 pm

The Forgotten Mapmaker: Nokia Has Better Maps Than Apple and Maybe Even Google by Alexis C. Madrigal.

What’s Nokia’s secret? Twelve billion probe data points a month, including data from FedEx and other logistic companies.

Notice that the logistic companies are not collecting mapping data per se, they are delivering goods.

Nokia is building maps based on data collected for another purpose, a completely routine and unrelated purpose to map making.

Does that suggest something to you about semantic map making?

That we need to capture semantics as users travel through data for other purposes?

If I knew what those opportunities were I would have put them at the top of this post. Suggestions?

PS: Sam Hunting pointed me towards this article.

October 4, 2012

Google Maps: A Prelude to Broader Predictive Search

Filed under: Interface Research/Design,Mapping,Maps — Patrick Durusau @ 2:01 pm

Google Maps: A Prelude to Broader Predictive Search by Stephen E. Arnold.

From the post:

Short honk. Google’s MoreThanaMap subsite signals an escalation in the map wars. You will want to review the information at www.morethanamap.com. The subsite presents the new look of Google’s more important features and services. The demonstrations are front and center.The focus is on visualization of mashed up data; that is, compound displays. The real time emphasis is clear as swell. The links point to developers and another “challenge.” It is clear that Google wants to make it desirable for programmers and other technically savvy individuals to take advantage of Google’s mapping capabilities. After a few clicks, Google has done a good job of making clear that findability and information access shift a map from a location service to a new interface.

You really need to see the demos to appreciate what can be done with the Google Map API.

Although, I remember the flight from Atlanta to Gatwick (London) as being longer than it seems in the demo. 😉

October 2, 2012

Torque for mapping temporal data

Filed under: Graphics,HTML5,Mapping,Temporal Data,Visualization — Patrick Durusau @ 2:49 pm

Torque for mapping temporal data by Nathan Yau.

From the post:

Mapping data over time can be challenging, especially when you have a lot of data to load in the beginning. Torque, the new open source project by CartoDB, is a step towards making the process easier.

Torque allows you to create beautiful visualizations with big temporal datasets by bundling HTML5 browser rendering technologies with a generic and efficient temporal data transfer format created using the CartoDB SQL API. Torque visualisations work on desktop and ipads, and work well on temporal datasets with hundreds of thousands or even millions of datapoints.

Isn’t data always mapped over time?

Data always originates at a time, observed at a time, recorded at a time (by an observer, mechanical or otherwise), is valid through a time, etc.

We may omit time for some reason or purpose but that is our choice.

October 1, 2012

Google Maps Goes Deep-Sea Diving to Chart the World’s Ocean Floors

Filed under: Mapping,Maps — Patrick Durusau @ 2:47 pm

Google Maps Goes Deep-Sea Diving to Chart the World’s Ocean Floors by David Gianatasio.

A quick blurb about Google Maps adding select sea beds to its map collection.

Suggestions on what other ocean floor data is commonly available?

And with data in hand, what other data would you merge it with?

Apple Maps: By the “big data” short hairs

Filed under: BigData,Mapping,Maps — Patrick Durusau @ 10:48 am

Mike Loukides in Apple’s maps: Apple’s maps problem isn’t about software or design. It’s about data nails the problem with Apple Maps. It’s the data stupid!

Here’s the difficulty. As Stephen O’Grady has pointed out, the problem with maps is really a data problem, not a software or design problem. If Apple’s maps app was ugly or had a poor user interface, it would be fixed within a month. But Apple is really looking at a data problem: bad data, incomplete data, conflicting data, poor quality data, incorrectly formatted data. Anyone who works with data understands that 80% of the work in any data product is getting your data into good enough shape so that it’s useable. Google is a data company, and they understand this; hence the reports of more than 7,000 people working on Google Maps. And even Google Maps has its errors; I just reported a “road” that is really just a poorly maintained trail.

Mike’s post is amusing and informative so be sure to read it.

But remember these two points:

  1. Data is always dirty, syntactically and/or semantically. “Big data” is “big dirty data.”
  2. Google has 7,000 people, not servers, clusters, algorithms, etc., working on Google Maps. (Is that evidence that “big dirty data” requires human correction?)

The bigger the data, the more dirt you will encounter.

Is your data application going to be the next “Apple Maps?”

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