One Large Network

If you haven’t checked out LinkedIn Labs, get on it! The site hosts a small set of projects and experimental features built by the employees of LinkedIn. They are billed as ‘low-maintenance’ experiments by the LinkedIn team, but they yield some very powerful help to the networker or job seeker. There are a number of really interesting tools that you can use such as:

• Integrating LinkedIn directly into Google Chrome
• Viewing your connections across the timeline of your career
• Getting your personalized LinkedIn Today headlines read to you on your mobile phone
• And many more…

I found Resume Builder, the Hackday Winner of March 2010 to be the most useful for me. You can “build, save & share beautifully formatted resumes based on your LinkedIn profile.” Providing you have a well defined LinkedIn profile, you will get some impressive results.

I was really interested in InMaps, which is classified as ‘LinkedIn Analytics‘ and enables you to “visualize your professional network, clustered in realtime based on their inter-relationships.” Unfortunately I was a very early adopter of LinkedIn and have been methodical about growing my connections and my network is now too large to be mapped. Cool idea though.

Related articles

• 2 Tools To Turn Your LinkedIn Profile Into A Neat-Looking Resume (makeuseof.com)
• 12 Awesome LinkedIn Infographics in 2011 (hubspot.com)
• HootSuite Integrates LinkedIn Company Pages & Groups (mashable.com)
• How do LinkedIn Advertisements Work? (pcworld.com)
• Sonar Connects New Contacts via LinkedIn (nyconvergence.com)

Image via Wikipedia

I have been working on this (mostly) annotated collection of  tools and articles that I believe would be of help to both the data dabbler and professional. If you are a data scientist, data analyst or data dummy, chances are there is something in here for you.

I included a list of tools, such as programming languages and web-based utilities, data mining resources, some prominent organizations in the field, repositories where you can play with data, events you may want to attend and important articles you should take a look at.

The second segment (BONUS!) of the list includes a number of art and design resources the infographic designers might like including color palette generators and image searches. There are also some invisible web resources (if you’re looking for something data-related on Google and not finding it) and metadata resources so you can appropriately curate your data.

This is in no way a complete list so please contact me here with any suggestions!

Data

Tools

1. Google Refine – A power tool for working with messy data (formerly Freebase Gridworks)
2. The Overview Project – Overview is an open-source tool to help journalists find stories in large amounts of data, by cleaning, visualizing and interactively exploring large document and data sets. Whether from government transparency initiatives, leaks or Freedom of Information requests, journalists are drowning in more documents than they can ever hope to read.
3. Refine, reuse and request data | ScraperWiki – ScraperWiki is an online tool to make acquiring useful data simpler and more collaborative. Anyone can write a screen scraper using the online editor. In the free version, the code and data are shared with the world. Because it’s a wiki, other programmers can contribute to and improve the code.
4. Data Curation Profiles – This website is an environment where academic librarians of all kinds, special librarians at research facilities, archivists involved in the preservation of digital data, and those who support digital repositories can find help, support and camaraderie in exploring avenues to learn more about working with research data and the use of the Data Curation Profiles Tool.
5. Google Chart Tools – Google Chart Tools provide a perfect way to visualize data on your website. From simple line charts to complex hierarchical tree maps, the chart galley provides a large number of well-designed chart types. Populating your data is easy using the provided client- and server-side tools.
6. 22 free tools for data visualization and analysis
7. The R Journal – The R Journal is the refereed journal of the R project for statistical computing. It features short to medium length articles covering topics that might be of interest to users or developers of R.
8. CS 229: Machine Learning – A widely referenced course by Professor Andrew Ng, CS 229: Machine Learning provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed.
9. Google Research Publication: BigTable – Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projects at Google store data in Bigtable, including web indexing, Google Earth, and Google Finance. These applications place very different demands on Bigtable, both in terms of data size (from URLs to web pages to satellite imagery) and latency requirements (from backend bulk processing to real-time data serving). Despite these varied demands, Bigtable has successfully provided a flexible, high-performance solution for all of these Google products. In this paper we describe the simple data model provided by Bigtable, which gives clients dynamic control over data layout and format, and we describe the design and implementation of Bigtable.
10. Scientific Data Management – An introduction.
11. Natural Language Toolkit – Open source Python modules, linguistic data and documentation for research and development in natural language processing and text analytics, with distributions for Windows, Mac OSX and Linux.
12. Beautiful Soup – Beautiful Soup is a Python HTML/XML parser designed for quick turnaround projects like screen-scraping.
13. Mondrian: Pentaho Analysis – Pentaho Open source analysis OLAP server written in Java. Enabling interactive analysis of very large datasets stored in SQL databases without writing SQL.
14. The Comprehensive R Archive Network
    - R is `GNU S‘, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please consult the R project homepage for further information.
    CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R. Please use the CRAN mirror nearest to you to minimize network load.
15. DataStax – Software, support, and training for Apache Cassandra.
16. Machine Learning Demos
17. Visual.ly – Infographics & Visualizations. Create, Share, Explore
18. Google Fusion Tables
    - Google Fusion Tables is a modern data management and publishing web application that makes it easy
    to host, manage, collaborate on, visualize, and publish data tables online.
19. Tableau Software
    - Fast Analytics and Rapid-fire Business Intelligence from Tableau Software.
20. WaveMaker
    - WaveMaker is a rapid application development environment for building, maintaining and modernizing business-critical Web 2.0 applications.
21. Visualization: Annotated Time Line – Google Chart Tools – Google Code
    An interactive time series line chart with optional annotations. The chart is rendered within the browser using Flash.
22. Visualization: Motion Chart – Google Chart Tools – Google Code
    A dynamic chart to explore several indicators over time. The chart is rendered within the browser using Flash.
23. PhotoStats
    Create gorgeous infographics about your iPhone photos, with Photostats.
24. Ionz Ionz will help you craft an infographic about yourself.
25. chart builder
    Powerful tools for creating a variety of charts for online display.
26. Creately
    Online diagramming and design.
27. Pixlr Editor A powerful online photo editor.
28. Google Public Data Explorer
    ?The Google Public Data Explorer makes large datasets easy to explore, visualize and communicate. As the charts and maps animate over time, the changes in the world become easier to understand. You don’t have to be a data expert to navigate between different views, make your own comparisons, and share your findings.
29. Fathom
    Fathom Information Design helps clients understand and express complex data through information graphics, interactive tools, and software for installations, the web, and mobile devices. Led by Ben Fry. Enough said!
30. healthymagination | GE Data Visualization
    Visualizations that advance the conversation about issues that shape our lives, and so we encourage visitors to download, post and share these visualizations.
31. ggplot2
    ggplot2 is a plotting system for R, based on the grammar of graphics, which tries to take the good parts of base and lattice graphics and none of the bad parts. It takes care of many of the fiddly details that make plotting a hassle (like drawing legends) as well as providing a powerful model of graphics that makes it easy to produce complex multi-layered graphics.
32. Protovis
    Protovis composes custom views of data with simple marks such as bars and dots. Unlike low-level graphics libraries that quickly become tedious for visualization, Protovis defines marks through dynamic properties that encode data, allowing inheritance, scales and layoutsto simplify construction.Protovis is free and open-source, provided under the BSD License. It uses JavaScript and SVG for web-native visualizations; no plugin required (though you will need a modern web browser)! Although programming experience is helpful, Protovis is mostly declarative and designed to be learned by example.
33. d3.js D3.js is a small, free JavaScript library for manipulating documents based on data.
34. MATLAB – The Language Of Technical Computing
    MATLAB® is a high-level language and interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming languages such as C, C++, and Fortran.
35. OpenGL – The Industry Standard for High Performance Graphics
    OpenGL.org is a vendor-independent and organization-independent web site that acts as one-stop hub for developers and consumers for all OpenGL news and development resources. It has a very large and continually expanding developer and end-user community that is very active and vested in the continued growth of OpenGL.
36. Google Correlate
    Google Correlate finds search patterns which correspond with real-world trends.
37. Revolution Analytics – Commercial Software & Support for the R Statistics Language
    Revolution Analytics delivers advanced analytics software at half the cost of existing solutions. By building on open source R—the world’s most powerful statistics software—with innovations in big data analysis, integration and user experience, Revolution Analytics meets the demands and requirements of modern data-driven businesses.
38. 22 Useful Online Chart & Graph Generators
39. The Best Tools for Visualization Visualization is a technique to graphically represent sets of data. When data is large or abstract, visualization can help make the data easier to read or understand. There are visualization tools for search, music, networks, online communities, and almost anything else you can think of. Whether you want a desktop application or a web-based tool, there are many specific tools are available on the web that let you visualize all kinds of data.
40. Visual Understanding Environment
    The Visual Understanding Environment (VUE) is an Open Source project based at Tufts University. The VUE project is focused on creating flexible tools for managing and integrating digital resources in support of teaching, learning and research. VUE provides a flexible visual environment for structuring, presenting, and sharing digital information.
41. Bime – Cloud Business Intelligence | Analytics & Dashboards
    Bime is a revolutionary approach to data analysis and dashboarding. It allows you to analyze your data through interactive data visualizations and create stunning dashboards from the Web.
42. Data Science Toolkit
    A collection of data tools and open APIs curated by our own Pete Warden. You can use it to extract text from a document, learn the political leanings of a particular neighborhood, find all the names of people mentioned in a text and more.
43. BuzzData
    BuzzData lets you share your data in a smarter, easier way. Instead of juggling versions and overwriting files, use BuzzData and enjoy a social network designed for data.
44. SAP – SAP Crystal Solutions: Simple, Affordable, and Open BI Tools for Everyday Use
45. Project Voldemort
46. ggplot. had.co.nz

Data Mining

1. Weka -nWeka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes. Weka is open source software issued under the GNU General Public License.
2. PSPP- PSPP is a program for statistical analysis of sampled data. It is a Free replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions. The most important of these exceptions are, that there are no “time bombs”; your copy of PSPP will not “expire” or deliberately stop working in the future. Neither are there any artificial limits on the number of cases or variables which you can use. There are no additional packages to purchase in order to get “advanced” functions; all functionality that PSPP currently supports is in the core package.PSPP can perform descriptive statistics, T-tests, linear regression and non-parametric tests. Its backend is designed to perform its analyses as fast as possible, regardless of the size of the input data. You can use PSPP with its graphical interface or the more traditional syntax commands.
3. Rapid I- Rapid-I provides software, solutions, and services in the fields of predictive analytics, data mining, and text mining. The company concentrates on automatic intelligent analyses on a large-scale base, i.e. for large amounts of structured data like database systems and unstructured data like texts. The open-source data mining specialist Rapid-I enables other companies to use leading-edge technologies for data mining and business intelligence. The discovery and leverage of unused business intelligence from existing data enables better informed decisions and allows for process optimization.The main product of Rapid-I, the data analysis solution RapidMiner is the world-leading open-source system for knowledge discovery and data mining. It is available as a stand-alone application for data analysis and as a data mining engine which can be integrated into own products. By now, thousands of applications of RapidMiner in more than 30 countries give their users a competitive edge. Among the users are well-known companies as Ford, Honda, Nokia, Miele, Philips, IBM, HP, Cisco, Merrill Lynch, BNP Paribas, Bank of America, mobilkom austria, Akzo Nobel, Aureus Pharma, PharmaDM, Cyprotex, Celera, Revere, LexisNexis, Mitre and many medium-sized businesses benefitting from the open-source business model of Rapid-I.
4. R Project – R is a language and environment for statistical computing and graphics. It is a GNU projectwhich is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.R is available as Free Software under the terms of the Free Software Foundation‘s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.

Organizations

1. Data.gov
2. SDM group at LBNL
3. Open Archives Initiative
4. Code for America | A New Kind of Public Service
5. The # DataViz Daily
6. Institute for Advanced Analytics | North Carolina State University | Professor Michael Rappa · MSA Curriculum
7. BuzzData | Blog, 25 great links for data-lovin’ journalists
8. MetaOptimize – Home – Machine learning, natural language processing, predictive analytics, business intelligence, artificial intelligence, text analysis, information retrieval, search, data mining, statistical modeling, and data visualization
9. had.co.nz
10. Measuring Measures – Measuring Measures

Repositories

1. Repositories | DataCite
2. Data | The World Bank
3. Infochimps Data Marketplace + Commons: Download Sell or Share Databases, statistics, datasets for free | Infochimps
4. Factual Home – Factual
5. Flowing Media: Your Data Has Something To Say
6. Chartsbin
7. Public Data Explorer
8. StatPlanet
9. ManyEyes
10. 25+ more ways to bring data into R

Events

1. Welcome | Visweek 2011
2. O’Reilly Strata: O’Reilly Conferences
3. IBM Information On Demand 2011 and Business Analytics Forum
4. Data Scientist Summit 2011
5. IBM Virtual Performance 2011
6. Wolfram Data Summit 2011—Conference on Data Repositories and Ideas
7. Big Data Analytics: Mobile, Social and Web

Articles

1. Data Science: a literature review | (R news & tutorials)
2. What is “Data Science” Anyway?
3. Hal Varian on how the Web challenges managers – McKinsey Quarterly – Strategy – Innovation
4. The Three Sexy Skills of Data Geeks « Dataspora
5. Rise of the Data Scientist
6. dataists » A Taxonomy of Data Science
7. The Data Science Venn Diagram « Zero Intelligence Agents
8. Revolutions: Growth in data-related jobs
9. Building data startups: Fast, big, and focused – O’Reilly Radar

BONUS!

Art Design

1. Periodic Table of Typefaces
2. Color Scheme Designer 3
3. Color Palette Generator Generate A Color Palette For Any Image
4. COLOURlovers
5. Colorbrewer: Color Advice for Maps

Image Searches

1. American Memory from the Library of Congress The home page for the American Memory Historical Collections from the Library of Congress. American Memory provides free access to historical images, maps, sound recordings, and motion pictures that document the American experience. American Memory offers primary source materials that chronicle historical events, people, places, and ideas that continue to shape America.
2. Galaxy of Images | Smithsonian Institution Libraries
3. Flickr Search
4. 50 Websites For Free Vector Images Download
5. Design weblog for designers, bloggers and tech users. Covering useful tools, tutorials, tips and inspirational photos.
6. Images Google Images. The most comprehensive image search on the web.
7. Trade Literature – a set on Flickr
8. Compfight / A Flickr Search Tool
9. morgueFile free photos for creatives by creatives
10. stock.xchng – the leading free stock photography site
11. The Ultimate Collection Of Free Vector Packs – Smashing Magazine
12. How to Create Animated GIFs Using Photoshop CS3 – wikiHow
13. IAN Symbol Libraries (Free Vector Symbols and Icons) – Integration and Application Network
14. Usability.gov
15. best icons
16. Iconspedia
17. IconFinder
18. IconSeeker

Invisible Web

1. 10 Search Engines to Explore the Invisible Web
   Like the header says…
2. Scirus – for scientific information
   The most comprehensive scientific research tool on the web. With over 410 million scientific items indexed at last count, it allows researchers to search for not only journal content but also scientists’ homepages, courseware, pre-print server material, patents and institutional repository and website information.
3. TechXtra: Engineering, Mathematics, and Computing
   TechXtra is a free service which can help you find articles, books, the best websites, the latest industry news, job announcements, technical reports, technical data, full text eprints, the latest research, thesis & dissertations, teaching and learning resources and more, in engineering, mathematics and computing.
4. Welcome to INFOMINE: Scholarly Internet Resource Collections
   INFOMINE is a virtual library of Internet resources relevant to faculty, students, and research staff at the university level. It contains useful Internet resources such as databases, electronic journals, electronic books, bulletin boards, mailing lists, online library card catalogs, articles, directories of researchers, and many other types of information.
5. The WWW Virtual Library
   The WWW Virtual Library (VL) is the oldest catalogue of the Web, started by Tim Berners-Lee, the creator of HTML and of the Web itself, in 1991 at CERN in Geneva. Unlike commercial catalogues, it is run by a loose confederation of volunteers, who compile pages of key links for particular areas in which they are expert; even though it isn’t the biggest index of the Web, the VL pages are widely recognised as being amongst the highest-quality guides to particular sections of the Web.
6. Intute Intute is a free online service that helps you to find web resources for your studies and research. With millions of resources available on the Internet, it can be difficult to find useful material. We have reviewed and evaluated thousands of resources to help you choose key websites in your subject. The Virtual Training Suite can also help you develop your Internet research skills through tutorials written by lecturers and librarians from universities across the UK.
7. CompletePlanet – Discover over 70,000+ databases and specially search engines
   There are hundreds of thousands of databases that contain Deep Web content. CompletePlanet is the front door to these Deep Web databases on the Web and to the thousands of regular search engines — it is the first step in trying to find highly topical information. By tracing through CompletePlanet’s subject structure or searching Deep Web sites, you can go to various topic areas, such as energy or agriculture or food or medicine, and find rich content sites not accessible using conventional search engines. BrightPlanet initially developed the CompletePlanet compilation to identify and tap into many hundreds and thousands of search sources simultaneously to automatically deliver high-quality content to its corporate and enterprise customers. It then decided to make CompletePlanet available as a public service to the Internet search public.
8. Infoplease: Encyclopedia, Almanac, Atlas, Biographies, Dictionary, Thesaurus.
   Information Please has been providing authoritative answers to all kinds of factual questions since 1938—first as a popular radio quiz show, then starting in 1947 as an annual almanac, and since 1998 on the Internet at www.infoplease.com. Many things have changed since 1938, but not our dedication to providing reliable information, in a way that engages and entertains.
9. DeepPeep: discover the hidden web DeepPeep is a search engine specialized in Web forms. The current beta version currently tracks 45,000 forms across 7 domains. DeepPeep helps you discover the entry points to content in Deep Web (aka Hidden Web) sites, including online databases and Web services.
   Advanced search allows you to perform more specific queries. Besides specifying keywords, you can also search for specific form element labels, i.e., the description of the form attributes.
10. IncyWincy: The Invisible Web Search Engine IncyWincy is a showcase of Net Research Server (NRS) 5.0, a software product that provides a complete search portal solution, developed by LoopIP LLC.
    LoopIP licenses the NRS engine and provides consulting expertise in building search solutions.

Metadata

1. Description Schema: MODS (Library of Congress) and Outline of elements and attributes in MODS version 3.4: MetadataObject
   This document contains a listing of elements and their related attributes in MODS Version 3.4 with values or value sources where applicable. It is an “outline” of the schema. Items highlighted in red indicate changes made to MODS in Version 3.4.All top-level elements and all attributes are optional, but you must have at least one element. Subelements are optional, although in some cases you may not have empty containers. Attributes are not in a mandated sequence and not repeatable (per XML rules). “Ordered” below means the subelements must occur in the order given. Elements are repeatable unless otherwise noted.”Authority” attributes are either followed by codes for authority lists (e.g., iso639-2b) or “see” references that link to documents that contain codes for identifying authority lists.For additional information about any MODS elements (version 3.4 elements will be added soon), please see the MODS User Guidelines.
2. wiki.dbpedia.org : About DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link other data sets on the Web to Wikipedia data. We hope this will make it easier for the amazing amount of information in Wikipedia to be used in new and interesting ways, and that it might inspire new mechanisms for navigating, linking and improving the encyclopaedia itself.
3. Semantic Web – W3C In addition to the classic “Web of documents” W3C is helping to build a technology stack to support a “Web of data,” the sort of data you find in databases. The ultimate goal of the Web of data is to enable computers to do more useful work and to develop systems that can support trusted interactions over the network. The term “Semantic Web” refers to W3C’s vision of the Web of linked data. Semantic Web technologies enable people to create data stores on the Web, build vocabularies, and write rules for handling data. Linked data are empowered by technologies such as RDF, SPARQL, OWL, and SKOS.
4. RDA: Resource Description & Access | www.rdatoolkit.org Designed for the digital world and an expanding universe of metadata users, RDA: Resource Description and Access is the new, unified cataloging standard. The online RDA Toolkit subscription is the most effective way to interact with the new standard. More on RDA.
5. Cataloging Cultural Objects Cataloging Cultural Objects: A Guide to Describing Cultural Works and Their Images (CCO) is a manual for describing, documenting, and cataloging cultural works and their visual surrogates. The primary focus of CCO is art and architecture, including but not limited to paintings, sculpture, prints, manuscripts, photographs, built works, installations, and other visual media. CCO also covers many other types of cultural works, including archaeological sites, artifacts, and functional objects from the realm of material culture.
6. Library of Congress Authorities (Search for Name, Subject, Title and Name/Title) Using Library of Congress Authorities, you can browse and view authority headings for Subject, Name, Title and Name/Title combinations; and download authority records in MARC format for use in a local library system. This service is offered free of charge.
7. Search Tools and Databases (Getty Research Institute) Use these search tools to access library materials, specialized databases, and other digital resources.
8. Art & Architecture Thesaurus (Getty Research Institute) Learn about the purpose, scope and structure of the AAT. The AAT is an evolving vocabulary, growing and changing thanks to contributions from Getty projects and other institutions. Find out more about the AAT’s contributors.
9. Getty Thesaurus of Geographic Names (Getty Research Institute) Learn about the purpose, scope and structure of the TGN. The TGN is an evolving vocabulary, growing and changing thanks to contributions from Getty projects and other institutions. Find out more about the TGN’s contributors.
10. DCMI Metadata Terms
11. The Digital Object Identifier System
12. The Federal Geographic Data Committee — Federal Geographic Data Committee

Related articles

• NSA Extends Label-based Security to Big Data Stores (pcworld.com)
• Cassandra 1.0, the cloud, and the future of big data (rackspace.com)

So my application was accepted and I’m now a part of the O’Reilly Blogger Review Program! Tight…

Image by AlphachimpStudio via Flickr

Aside from my internship at the Smithsonian Institution, I had one goal this summer: dig deeper into understanding, analyzing and representing information.

I set out to learn more about theory, analysis, and implementation through a fairly methodical method. As a Master’s student at Syracuse University’s School of Information Studies, I have already had a huge head start and knew where to look and what to look for. There are also the blogs and twitter accounts I follow. Combining everything, I was able to come up with common trends and themes and vet them against what everybody was saying and writing.

What turned out was a list that will take you from the big picture, atmospheric view all the way down to pixel level decisions and everything in between.

I am in varying stages of completion (there is another list I am working through as well) with the listed books and will keep hammering at them throughout the upcoming semester. BTW, a number of these books can be purchased through O’Reilly Media, which regularly has some pretty sweet sales (buy 2 get one free, discounts for digital books, etc.).

Theory

I was first made aware of Edward R. Tufte‘s work in Jaime Snyder‘s course on Information Design. The guy is essentially the godfather/granddaddy of information design and visualization, analytic design, and associated creative processes. Definitely worth getting the hardcover editions of both. They are full color and gorgeous.

• The Visual Display of Quantitative Information - Edward R. Tufte
• Envisioning Information - Edward R. Tufte

Analysis

This is  a wonderfully comprehensive book and, like the Yau offering, could be listed in multiple categories. I put it under ‘Analysis’ because it is a great – and friendly – primer for really digging deep into data analysis. I got the Ebook (available in the following f ormats: APK, DAISY, ePub, Mobi, PDF) and found that to work best for me. I am on the computer already so having the digital copy there makes it easy.

• Head First Data Analysis - Michael Milton

Implementation

Processing is an open source programming language and environment for people who want to create images, animations, and interactions. Since created by Casey Reas and Ben Fry, it has taken off like wildfire and, from what I found, is standard, required knowledge for taking information interpretation to the next level. Though I am (not yet) a programmer, I have been able to battle through the tomes with some success. I got the Pearson book in soft cover (nice color graphics in the beginning and comes with the Ebook free) and the others in Ebook format.

1. Generative Art – Matt Pearson
2. Getting Started with Processing - Casey Reas, Ben Fry
3. Visualizing Data – Ben Fry

Related articles

• Ben Fry, Information Designer (slate.com)
• Slopegraphs (kottke.org)
• What I am reading at the moment (kitlas.com)

Image by Steven Combs via Flickr

Copy/paste this string (in bold) into your Google search bar: “crm database” “manager” (intitle:resume)
Yup that is me. The number 3 result on a Google search for CRM Database Manager. Read on for tips on how people can find you online. I imagine this will be helpful to job seekers.

———————————–

Like anyone else, I am interested in what the outside world thinks of me – especially when I do not have to solicit directly from them. Part of the beauty of the web is that, with the right tools, it is really easy to get a variety of statistics about the visitors to your website. My blog is a pretty basic operation and, though there are a trove of utilities out there, there are three places I primarily get my data analytics from.

One is my WordPress Dashboard under ‘Site Stats’ as well as two plugins I installed – WassUp Keywords and WassUp Stats.

Two is under my cPanel (a backend site maintenance utility provided to me by my web host). There are a number of packages there, but I typically use Awstats.

Third is Google Analytics.

I used to have a casual relationship with the statistics of my site. It is a personal blog. There is no commerce. It is interesting to see who is visiting from where, what they are viewing, my most popular posts, etc.

It is also interesting to check out what terms people are using to get to your site. For example, the following search engine terms are a small example of terms people used to find my blog.

I took a look at the below key phrases a couple weeks ago (I am way behind on finishing up and publishing drafts of some posts) and here is what came up.

While it is totally awesome that I rank as the number one Google result for ‘singing rice cooker‘ and number four for ‘circadian rhythm test‘, the biggie here (and thrust of this post) is that all of the traffic was driven to my site by the ‘-inurl’ search operator mixed in with some job candidate requirements.

These people landed on my site because they were looking to fill a position and were specifically targeting attributes of potential candidates.

What brought them there? What else, my resume. Not from Monster.com or another job site, but from the very humble kitlas.com.

So, what are these search operators? A basic description from Copernic Inc.:

A search operator is an instruction that joins keywords to form a new, more complex query. It enables you to look for several words at once by telling …. how to link keywords. The most common search operators are the three Boolean operators (AND/+, OR and NOT/-), which allow the inclusion or exclusion of documents from the search results.

So, what does the ‘inurl’ command do?

If you include inurl: in your query, Google will restrict the results to documents containing that word in the URL. For instance, [ inurl:print site:www.googleguide.com ] searches for pages on Google Guide in which the URL contains the word “print.” It finds pdf files that are in the directory or folder named “print” on the Google Guide website. The query [ inurl:healthy eating ] will return documents that mention the words “healthy” in their URL, and mention the word “eating” anywhere in the document.

There are tons of advanced search operators that are laid out beautifully by Google Guide. You can find them here.

These are tools in the proverbial toolbelt. There is a lot more to being found on the web than making a blog and posting resumes. I got lucky in that what I was doing was obviously right, but luck is not necessary. Using these operators to test your content can help greatly in your online presence.

You need content, you need it online, and it needs to be very purposeful. If you look at my resume, you will see very little ‘fat’. I also take a lot of time working on it. Sometimes every week I make changes. Whether it is a new skill I picked up, relevant coursework, or a new piece of software I have mastered, I post it.

The moral of the story is that, if you want to be found online, you need to:

• help people find you by making yourself visible
• find out where they are looking for and compare to what you have and see how well you match up
• tweak as necessary

As you may imagine, I have now moved from having a passive/casual relationship with my site statistics to a very active one.

Related articles

• How to Find Relevant Link Targets (searchenginepeople.com)
• Hands-On Tips For Link Building (seomoz.org)
• How Hackers Use Google Search For Hacking (myassgeek.wordpress.com)

Image via Wikipedia

I came across this nifty page on ESPN.com that will compare your salary with that of top-tier professional players from the NBA, NHL and MLB. You get a breakdown of how long it takes a player to earn your annual salary (before taxes).

For instance, if you make $65,000 a year…

Peyton Manning makes $65,000 after the following…

.06 Games
.12 Touchdown passes
16.97 Passing yards
1.63 Pass completions

You will need to work 276.92 years in order to make Peyton Manning’s annual salary.

To find out how long it takes your favorite sports personality to earn your wages, enter your annual salary here.

Since I’ve been hurting for content lately (translation I have a ton of draft posts but have been lazy) I am being totally lame and reposting and AWESOME article about manipulating GIF images from the good people at Photojojo. Check it out and if you are not on their mailing list, you should be. They have the best photo shiz anywhere. Read on.

Extra photos for bloggers: 1, 2

Like instant film and harem pants, GIFs are making quite the comeback.

They may have had an awkward start back in their earlier days, but now GIFs are easier to craft and looking better than ever thanks to lasers, smart phones, and good old fashioned creativity.

We found the raddest and baddest ways to make and show off GIFs from real-life GIF zoetropes to making your phone’s background animated.

Creepy dancing Ally McBeal baby, step aside. There are new GIFs in town.

How to Kick Your GIFs Up a Notch

Main image credit: GIF Shop

1. HISTORY OF THE GIF

Short for Graphics Interchange Format, the GIF came out in the late eighties as a bitmap image format that was able to support animation.

Like the adolescent years, many of the earlier GIFs were animated awkwardly and sometimes spastically.

Yet their ability to capture animation captured our own beating hearts by providing us the means to make a more dynamic kind of photo or illustration.

Like Batman. With kittens. Awww.

GIF via this isn’t happiness.

2. HEY IPHONE, YOU GIF?

Your iPhone can GIF thanks to some neat apps, like:

• GIF Shop – Lets you edit and loop your GIFS with neat features like onion skinning, which helps you line up different shots.

• Giffer – Has a cool photo picker that lets you select more than one photo at a time.

• Loopcam – This one’s free! It’s a stripped-down app that lets you make GIFs from photos quick and easy.

• Figgif – Lets you make a GIF from video you record on your phone.

Android users: As of now, we haven’t found stellar GIF apps for Android, but we’ll update here if any better ones pop up!

3. THE CINEMAGRAPH: THE GLORIFIED GIF

If early GIFs are comparable to the awkward adolescent years, then cinemagraphs are GIFs in their most golden age—sleek and très chic.

First introduced by the talented team of photographer Jaime Beck and motion designer Kevin Burg, these sophisticated GIFs took the web world by storm, eliciting oooo’s and aah’s from fascinated viewers.

Get inspired by Beck and Burg’s cinematic creations, and then get right into making your with our cinemagraph tutorial!

4. GIF UP YOUR IPHONE SCREEN!

For you iRebels rockin’ jailbroken iPhones, show off more of that dissident spirit by GIF-ing up your lockscreen.

With some patience and this custom lockscreen tutorial, an animated iPhone lockscreen will soon be yours to rock and roll.

Warning to tech n00bs—this requires quite some tinkering to work, so proceed with caution and extra patience!

5. THE REAL WORLD: GIF EDITION

Wait, you mean, GIFs aren’t limited to viewing just on the computer screen?

Nope—thanks to Greg Borenstein & Scott Wayne Indiana, the creative folks who make GIF zoetropes at Physical GIFs!

Physical GIFs are based on the persistence of vision: when a series of frames moving quickly is perceived as one moving image by your eyes and brain.

Each frame of a GIF is carved by lasers out of plexiglass, and then the frames are animated with the use of a spinning disc and a strobe light. See one in action in this video!

They’ve recently reached their fundraising goal on Kickstarter, so expect to see some real-time GIFs proudly displayed on some lucky coffee tables soon!

6. TURN VIDEOS INTO GIFS!

Wanna make a GIF from a section of your favorite YouTube video, or your own video files? GIF ‘em right up with the following converter sites:

• GIFsoup – The chicken soup for your digital soul, GIFsoup basically helps you turn your own YouTube videos into a GIF!
• Bender Converter – This nifty converter can make GIFs from a plethora of sites, including YouTube, Vimeo, and Facebook!

GIF created from video featuring Raoul Ortega and filmed by David McClymonds.

GIF ME MORE

• Have Photoshop or Gimp but never GIF-ed before? Learn how to make ‘em inPhotoshop and in Gimp.
• No Photoshop? No worries! GIFninja is here to save the day. As is Picasion andGickr! These are just three examples of free GIF makers available for you to use on the interwebz.
• Not only can your GIFs move, they can wiggle and look 3D, too. Make your own wiggle 3D GIF—like David Fitzsimmon’s GIF above!
• Fruits can get their GIF on, too—check out these amazing animated MRI fruit scans created by MRI technologist Andy Ellison!
• Made an awesome GIF and dying to share it to the world? Upload your pixel-moving masterpieces to your own blog, or have ‘em join the GIF party! Did your cat star in your GIF? There’s a page to showcase your cat’s animated antics, too!

Related articles

• How-To: Cinemagraphs (makezine.com)
• The Best 150 Animated Gifs. Really. Gifs. (cartoonsmartblog.wordpress.com)
• ARTspiration: Cinemagraph – Still Photos with Subtle Motions (aybanlim.wordpress.com)
• This Week In GIFs (videogum.com)
• Tutorial: How to Make Cinemagraphs with Photoshop (labnol.org)

Smithsonian Castle Interior (Belly of the Whale)

A version of this is also posted on the Syracuse University iSchool blog, Information Space.

I am now nearing the end of my internship. In my last post, I promised to make this one about the projects I am working on and the skills and tools I am using to execute them. If at any point this post begins to sound like an advertisement or glowing review of the Syracuse University School of Information Studies…it is.

There were many things that first drew me to this internship at the Smithsonian Institution – the focus on professional development, the rigorous and diverse set of projects, and that the work combined library and information science skills and information management skills. I am jointly pursuing a LIS and IM degree so getting an internship that had elements of each was critical.

Of all the courses I have taken in my year at the iSchool, the following four classes – in this order – have provided me with the skills, tools, and knowledge to execute the projects I am working on at the Smithsonian

• IST 659 Data Administration Concepts and Database Management (Bei Yu)
  • From day one, I was writing SQL scripts to organize, manipulate, and extract data from entities with tens of thousands of records. This is not something for Excel. As nice as Excel is, and I do really like the software, it just does not have the engine to work nimbly with very large amounts of information. Aside from SQL, I was called on a couple times to explain theory and best practice in database design – all learned from Bei Yu and IST 659.
• IST 616 Information Resources: Organization and Access (Jian Qin)
  • I have had to do a LOT of ordering and structuring of digital resources in this internship. Every day I have worked through the nature of information-based problems and how information systems address these problems, the concepts, principles, standards, and technologies of information organization, the human aspects of information organization, and how organized information affects information search/retrieval.
• IST 600 Information Design (Jaime Snyder)
  • This course is a great companion to just about everything at the iSchool. It should be required, in my opinion. How did I use what I learned in Information Design at this internship? Primarily on a theoretical level and linked closely to the practicality of what I learned in 616, but also in designing the components of information-driven systems in my projects.
• IST 631 Enterprise Technologies (Dave Dischiave)
  • More than once the enterprise technology concepts discussed in this class came up. After educating some senior (rank not age) staff members about virtualization and ‘scaling up’ versus ‘scaling down’, I was labeled as ‘the expert’. In the meetings and casual water cooler conversations following, I was asked regularly to weigh in on questions about enterprise technology issues a lot more than I anticipated, sometimes daily.

As you can see, there is both a mix of IM and LIS classes and their real world applications. There are also bits and pieces from other classes that I employed on a regular basis. The iSchool had me well prepared, to say the least. On a separate note, if anyone wonders about the credibility of the iSchool in the real world, I definitely got more than a handful of ‘oohs’ and ‘ahhs’ after telling new colleagues and staffers my academic affiliation.

It has been a great experience and I only regret that the internship does not run longer.

If you want to ask me any questions, please do not hesitate – my email is jkitlas@syr.edu or you can go to http://kitlas.com

Below is a recap of a public symposium I recently attended. It was organized by the Board on Research Data and Information National Research Council. An abbreviated version is published on the blog of Syracuse University’s School of Information Studies.

Crowdsourcing is a straightforward concept – rally people around a cause or concept and get them to contribute their thoughts, observations, and insights. The term is widely attributed to Jeff Howe in a June 2006-Wired magazine article. It is everywhere:

• People have monetized it –  CloudCrowd, Innovation Exchange
• People have helped people with it – Katrina PeopleFinder Project, Ushahidi (Swahili for “testimony” or “witness”)
• People have influenced people – FlipperTV (2007) and McCainpedia (2008) (The Democratic National Committee – both)

And…..scientists and researchers have been using it for generations to acquire scientific data.

Interesting (recent) Historical Note

One of the earlier documented records of scientific crowdsourcing was through an organization from the U.K. called Mass Observation. Early in 1937, three young men got together to create an “anthropology of ourselves” – a study of the everyday lives of ordinary people in Britain. In an effort to achieve their goal, the group set out to encourage a national panel of volunteers to reply to regular questionnaires on a variety of matters.

A team of paid investigators went into a variety of public situations: meetings, religious occasions, sporting and leisure activities, in the street and at work, and recorded people’s behavior and conversation in as much detail as possible. The material they produced is a varied documentary account of life in Britain. As time progressed, the emphasis shifted away from social issues and towards consumer behavior. In 1949, Mass Observation registered as a company and now boasts a deep repository of British behaviors.

The Little Guy Wins Big

Going back further (back being the mid-1500s); people started offering monetary rewards to solve the problem of measurement of longitude at sea. This was a huge issue – an estimated 2,000 Britons died in the Scilly Naval Disaster (1707). How? They were lost. In the English Channel. Ouch. The Longitude prize was an open competition attacked by many notable scientists – Galileo, Halley, Werner, and Newton. A clockmaker and carpenter from England, John Harrison, amassed all data that had been generated by others to solve the problem and eventually won the prize.

Today

The Human Genome Project is more recent example of scientific crowdsourcing through social networking with work completed at laboratories as part of publically funded projects in the US, parts of Asia, and parts of Europe.

SARS (Severe Acute Respiratory Syndrome) was solved through the formation of a collaborative multicenter research project that helped the rapid identification, sequencing, and testing of the coronavirus.

NOAA, aside from being generally amazing, is doing some REALLY AMAZING work with a site called oldweather.org. NOAA is not just engaging the public in climate science, but exploiting crowdsourcing to digitize and analyze climate data. After digitizing historic documents, users get the chance to decode handwriting (something that machine cannot do very well) for NOAA and learn about what happened in the past by reading the ship logs, user accounts and so on. When a citizen becomes a volunteer in a project like this, you get participatory science.

The World Wildlife Fund is mapping the future of Virunga forests with the Moabi crowdsourcing system. PatientsLikeMe is crowdsourcing information about illnesses and treatments so others can learn about what they are going through and find support from similarly afflicted individuals.

The list of modern day crowdsourcing goes on and on. Here is a brief list of some current projects:

• Galaxyzoo.org
• Citizen science alliance
• Recaptcha
• Zooniverse (exploring partnership w NOAA)
• Oldweather.org
• Surfacetemperatures.org
• Tropical cyclone reanalysis

The sky is the limit (check out the DARPA Balloon Hunt – ha ha) with crowdsourcing.

(If you need even more examples of crowdsourcing, there is a mammoth list here)

Event Details:

Crowdsourcing: Improving the Quality of Scientific Data through Social Networking

Organized by the Board on Research Data and Information National Research Council

(http://www.nationalacademies.org/brdi)

Speakers

Roberta Balstad, Columbia University and BRDI Vice-Chair, Gregory Phelan, State University of New York at Cortland, Scott Hausman, NOAA National Climatic Data Center, Leo Bottrill, World Wildlife Fund, David Clifford, Manager of Public Policy and Government Affairs, PatientsLikeMe, Michael Keller, Stanford University and BRDI Member

• Linked Data – The Story So Far

  http://tomheath.com/papers/bizer-heath-berners-lee-ijswis-linked-data.pdf

• How to Publish Linked Data on the Web

  http://www4.wiwiss.fu-berlin.de/bizer/pub/LinkedDataTutorial/

• Linked Data

  http://www.w3.org/DesignIssues/LinkedData.html

• Scientific Data Management

  http://personal.cscs.ch/~mvalle/sdm/scientific-data-management.html

• Managing and Sharing Data

  http://www.data-archive.ac.uk/media/2894/managingsharing.pdf

• Faceted Wikipedia Search

  http://dbpedia.neofonie.de/browse

• Getting Started with Processing by Casey Reas, Ben Fry
• Metadata by Marcia Lei Zeng and Jian Qin