List of 100 as a Thinking Tool

Last week, I was looking at an article about thinking titled – Tackle Any Issue with a List of Hundred. I liked the concept but I was not sure about finding a list of hundred ideas. So I decided to give it a try by listing  different ways of using InfoMinder, one of our products.

Here is the list. To be true to the experiment, I did not try to organize it too much, remove duplicates or even refine it too much. Now that I made the first hundred, I am encouraged to make it 200 or even more. The items are not that important or interesting to you (unless you are an information professional). However, the process of going through the exercise and making the list is important.

  1. Track competition product releases
  2. Track competition partnerships
  3. Track competition team changes
  4. Track competition advertisements?
  5. Track competition hiring
  6. Track competition research efforts (research publications, grants)
  7. Track competition presence in social media (twitter, facebook, linkedin)
  8. Competition pricing deals on the sites
  9. Track competition evangelism (where they speak, write, blog)
  10. Track the shows competitors go to
  11. Track where competitors advertise
  12. Track new RFPs from government
  13. Track funding on venture sites
  14. Track companies being funded (from a list on venture sites or other sources)
  15. Track job postings
  16. Track opportunities by tracking certain technology, job trends
  17. Track products in your customer’s  space (PR companies, product groups)
  18. Track Services (professional) related to products (bizdev, marketing, sales)
  19. Track product enhancements (both inside and third party)
  20. Track open source initiatives in a specific space
  21. Track University Research
  22. Track social innovation efforts and initiatives
  23. Track Foundations and projects
  24. Track world bank projects and initiatives
  25. Track IMF projects
  26. Track government projects and initiatives in various countries
  27. Track NSF (Australian and European organizations) research funding efforts
  28. Material Research
  29. Science Research
  30. Energy Research
  31. Green Tech Research
  32. Take all the public data and put it in open linked data
  33. Take all the data and do entity extraction
  34. Go to magazine sites in a specific industry and get table of contents (scrape and RSS feeds)
  35. Mine ODP data
  36. Update ODP data
  37. Set up connections between entities – companies/orgs, people, places, products, technology, events, resources
  38. Mine Blogs
  39. Find blog rolls and convert them into opml
  40. Create faceted blog directories
  41. Find experts in different areas
  42. Find resources in different areas
  43. Track the customer mentions in magazines web sites
  44. Track customer mention in blogs
  45. Track customer mention on Twitter
  46. Track customer mention Social Networks (find groups, fans)
  47. Track customer mentions in discussion forums
  48. Track bookmarks to customer sites in social bookmarking sites
  49. Track customers competitors
  50. Track 1-6 for each competitor
  51. Build customer competitor portals (specific to each customer)
  52. Build customer industry events (based on customer interests)
  53. Track news for customer industry (based on interests)
  54. Track development tools
  55. Track technical books
  56. Track technical articles
  57. Track blog posts on a certain topic
  58. Track industry events on software
  59. Track trends in the software industry
  60. Track discussions
  61. Track code libraries
  62. Track design patterns and anti-patterns
  63. Track best practices
  64. Track programming language trends
  65. Track skill trends (from job trends)
  66. Track software methodologies
  67. Track web frameworks
  68. Track databases
  69. Track software standards
  70. Track jobs on your customers’ job pages
  71. Track jobs on job search engines
  72. Track specific job trends on indeed
  73. Track keywords
  74. Track searches on Google
  75. Track trends on Google
  76. Track wikipedia
  77. Track wikipedia’s changed pages
  78. Track new portals being setup in wikipedia
  79. Track planet (aggregation pages) like javaplanet, pythonplanet, dotnetplanet, rdfplanet etc.
  80. Track top bookmarks on del.icio.us, stumble upon
  81. Track open source collaboratories like sourceforge, google code
  82. Track discussions
  83. Track Digg (top pages or new pages)
  84. Track reddit
  85. Track slashdot
  86. Track answer pages
  87. Track skills required
  88. Track institutes building the skills
  89. Track google blogs for breaking news from google
  90. Track microsoft blogs for breaking news about microsoft
  91. Track you tube video searches
  92. Track conference wiki sites
  93. Track conference exhibitor pages
  94. Monitor websites for health
  95. Monitor websites for hacks (if any specific keywords phrases appear on web pages)
  96. Track gaming sites for new games or comments on games
  97. Track movie sites for comments, ratings
  98. Track lists (like alltop) for changes
  99. Track twitter Searches (create a search, track the page for changes and get notified if any specific keywords appear in changes)
  100. Track Facebook applications (for new apps) or other similar app directories
  101. Track government data sites
  102. Track different types of government data (state and federal initiatives) data.gov, xml.gov etc.
  103. Do legal research
  104. Convert web page changes to RSS feeds

Who can use it?

Almost any one who need to keep track of information on the web but do not want to go and check your book marked pages periodically. Some of the uses are very simple. Just add the page to the list you monitor. Some of them are more complex or require you to customize InfoMinder results. Our customers use it for job tracking, lead generation, competitive research, legal research, PR and include government agencies, financial institutions, small businesses.

Now that I have a list, I can think of 100 landing pages or even cluster them based on the type of professional who may use it and do sub-lists.

This exercise has been useful. I think I will make List of Hundred a frequent exercise. It is a great thinking tool.

RDBMS: Tired Software?

Michael Stonebraker calls RDBMs “Tired Software”. Stonebraker is a well known guru in the DBMS community. As the architect of Berkeley Ingres, Postgres, Illustra and Streambase, he has been constantly innovating in the database space.

So when he speaks, a lot of us listen. If you are a database developer or designer, this article on the future of databases may be worth a read. A few snippets:

If we examine the nontrivial-sized DBMS markets, it turns out that current relational DBMSs can be beaten by approximately a factor of 50 in most any market I can think of. What follows are a few examples.

  • In the data warehouse market, a column store beats a row store by approximately a factor of 50 on typical business intelligence queries. The reason….
  • In the online transaction processing (OLTP) market, a lightweight main memory DBMS beats a row store by a factor of 50.
  • In the science DBMS market, users have never liked relational DBMSs and want a non-relational model and query facility.
  • If you are storing Resource Description Framework (RDF) data, which is popular in the bio community and elsewhere, then “Scalable Semantic Web Data Management Using Vertical Partitioning” points out that column stores are very good at certain RDF workloads
  • Text applications have never used relational DBMSs.
  • Even in XML specialized engines beat conventional RDBMS

Stonebraker goes on to explain why RDBMs technologies show signs of age and describes several possible alternatives.

Meta:

When we first built a relational engine in mid 80s the only resource we had was C.J.Date’s book. After the first iteration, I managed to get hold of a set of papers on relational database mangement system from Michael Stonebraker. We learned a lot from them. So to me Michael Stonebraker is a bit of a hero. In a conference at Hyatt Rickey’s in Palo Alto, I was lucky to meet all my RDB heros – Codd, Date, Michael, Lawrence Row and many others. After that I bumped into Stonebraker once in Illustra (we build an ODBC driver for them). I lost track of Stonebraker after that. I kept hearing about him a bit when I was doing some consulting work on Streaming Database for an XML acceleration company. So when I found this article, in the Semantic Web group in LinkedIn, I was really happy.

This is an area that bears a bit of investigation. Would love to get back and dabble in RDF stores, one of the most promising technologies on the horizon.

Stephen Hawking: Self Designed Evolution

A Broader View from Stephen Hawking:

“I think it is legitimate to take a broader view, and include externally transmitted information, as well as DNA, in the evolution of the human race,” Hawking said.

In the last ten thousand years the human species has  been in what Hawking calls, “an external transmission phase,” where the internal record of information, handed down to succeeding generations in DNA, has not changed significantly. “But the external record, in books, and other long lasting forms of storage,” Hawking says, “has grown enormously. Some people would use the term, evolution, only for the internally transmitted genetic material, and would object to it being applied to information handed down externally. But I think that is too narrow a view. We are more than just our genes.”

I really like this part. There is, of course, a big IF:

If the human race manages to redesign itself, to reduce or eliminate the risk of self-destruction, we will probably reach out to the stars and colonize other planets.

An exciting future to think about.

Python: Evolutionary Computing, API for Structured Data, Interface to R Language…

Python Alerts from InfoStreams:

Multicore: 800 TFlops, Bulk MultiCore, HMPP Workbench and More

  • 800 TFLOPS chip for ray tracing 800 TFLOPS chip for ray tracing Courtesy of Multicoreinfo.com, Tops Systems Corp of Japan, a venture involved in multicore technology, together with Toyota Motor Corp and Nihon Unisys Ltd, both of Japan, is developing a dedicated integrated circuit (IC) for ray tracing*, an image rendering method used in 3D computer …
  • The Bulk Multicore Architecture The Bulk Multicore Architecture The Bulk Multicore Architecture for Improved Programmability, by Josep Torrellas, Luis Ceze, James Tuck, Calin Cascaval, et al., describes a novel, general-purpose multicore architecture called the Bulk Multicore that is designed to enable a highly programmable environment. In the Bulk Multicore, the programmer and run time …
  • CAPS announces new version parallel programming workbench CAPS announces new version parallel programming workbench This over the email transom last week. CAPS Entreprise has announced a new version of its HMPP (Hybrid Multicore Parallel Programming) workbench Based on C and FORTRAN directives, HMPP Workbench provides developers with powerful data-parallel code generators that efficiently leverage the computing power …
  • NetLogic-RMI to intensify multicore battle NetLogic-RMI to intensify multicore battle NetLogic Microsystems Inc.’s recent move to acquire RMI Corp. will help the multicore processor specialist to devise new products more rapidly, according to executives. The move will also intensify the battle in the emerging embedded multicore sector. During a press event here on July 1, …
  • Report: UPCRC Summer School on Multicore Programming Report: UPCRC Summer School on Multicore Programming Program featured both and hands-on projects Sponsored Topics: Multicore cable – Programming – Education – Parallel computing – UPCRC Summer School
  • ARM licenses graphics processor to MediaTek ARM licenses graphics processor to MediaTek by Richard Wilson ARM has announced that MediaTek has licensed the Mali-400 MP multicore graphics processing unit (GPU) for integration in its system-on-chip (SoC) technology. Increasingly, ARM is seeing its Mali graphics processor IP as a differentiator for adoption of its IP in consumer …