Data Transformation

Dan Suchy (aka celerysword) twitter:

“Data Transformation” sounds fancier than “Find and Replace”

I’m in the middle of some very complex and intellectually challenging Data Transformation.

LOL.

So I am told

http://www.gocomics.com/shoe/2008/06/29

Blogged with the Flock Browser

poor firefox

more cat pictures

to tag or not to tag

I was reading my Google Reader and Jonathan Rochkin’s Tagging and motivation in library catalog? post caught my attention. He asked about the “why” of tagging, the motivation that drive people to tag. He asked “Why would a user spend their valuable time adding tags to books in your library catalog?”

I have the same question as well, for I still don’t really grasp the social implication of tagging, aside from whatever stuff Dave Weinberger said on his ‘Everything is Miscellaneous’ blog on tagging.

Back to library catalog tagging: if I were a student and found a useful resource for my course, then I probably would tag it with my course number and the topic of the paper my professor assigned to me. That would make it easier for me to find that resource again. If my classmates did the same thing, then I could get a list of resources for my paper.

However, I probably would use the catalog as an “on demand” activity. That is, I would use the library catalog as needed and if I find a resource suitable for my paper, I want to get it right away and prefer none of my classmates find out about it. Chances are, my classmates would do the same thing. Tagging almost becomes a moot point.

OK. This doesn’t help. Sorry.

This might be different if I did a group project. Each of us could tag resources that would be useful for our project. We could have a list of resources that can be listed on our project report. That tagging collaboration would still be a short-live activity, however.

Personally, I found out that I am not really into the tagging thingy. I reviewed my delicious list and realized that my tags are actually the reflection of the content of the site, not the “why”. If I tag them by the “why”, most of them would probably tagged as “cool application” or “interesting stuff.” Or “the site mentioned by Tim O’Reilly because I follow his blog and, by the way, it is indeed an interesting stuff.”

ALA-accredited programs on Google Map

It’s nice to know where you can find the nearest library school.  American Library Association (ALA) office for Accreditation created a Google map showing their locations.

Each link goes to a description page on ALA website.  Some of the links go directly to the school’s website.

View Larger Map

power in simplicity

The title of this post is one of the comments for this comic, which I find very troo…

http://stuffthathappens.com/blog/2008/03/05/simplicity/

Horizon Reports – emerging technologies for higher education

Horizon Project is a collaboration between the New Media Consortium and the EDUCAUSE Learning Initiative. Since 2004, they produce reports on emerging technologies that “will impact higher education within three adoption horizons over the net one to five years.”

Last year (2007 Horizon Report) , their report touched user-created content and social networkings and projected this adoption in one year or less. The adoption mobile phones for education & learning and using virtual worlds as learning spaces were projected in two to three years. The new scholarship & emerging forms of publication (new models of publication and nontraditional scholarly products) as well as multi player educational gaming time-to-adoption were projected in four to five years.
This report can be found at http://www.nmc.org/horizon/2007/report

Recently, they just produced a new report (2008 edition) that touched several key emerging technologies to be applied to teaching and learning:
- Grassroots Video: better and cheaper (if not free) tools allow the creation of educational videos and disseminate them quickly. No need to rely on an exclusive group of professionals and on expensive equipments or infrastructure.
- Collaboration Webs: using web-based collaboration tools for teaching/learning and research activities.
- Mobile Broadband: more powerful personal devices and can be used to access the educational content.
- Data Mashups: combining data from different sources and producing new datasets.
- Collective Intelligence: knowledge and understanding that emerges from large groups of people. This is facilitated by the collaboration webs and utilizing the data mashups.
- Social Operating Systems: connecting people through network. The organization of the networking would be around people rather than around content.

This year’s report can be found at http://www.nmc.org/publications/2008-horizon-report

Most of the items mentioned above are probably already implemented at least on personal or group level (think YouTube, GoogleDocs, iPhone, or wikipedia.com.) Utilizing similar technology for teaching and learning does present some challenges especially in the area of assessments, policy, growing expectations, and changes in infrastructure.

WorldWideScience.org

WorldWideScience.org is a collaborated effort that allow scientists to do search on national and international databases. It was developed by the U.S. Department of Energy’s Office of Scientific and Technical Information in partnership with the British Library and other sources.

Pretty cool effort, considering they have to deal with various databases with different metadata, database structure, and search syntax.

I tried it out by using my usual dorky word search, “java”, because I always curious how a system would distinguish it between java programming language, java island, javanese people, java language (yes, the language of javanese), and, of course, java coffee.

Well, not much happening on the search result. You will get a list of results supposedly based on a relevancy and no clear categorization. However, I suppose the scientists will  probably use more specific search terms and can expect to get a more precise results.

Using wildcard (*) works, as well as boolean search.

Ten Root Conditions of Data Quality Problems

Ten Root Conditions of Data Quality Problems:

1. Multiple data sources. Multiple data sources of the same information produce different values for this information. This can include values that were accurate at a given point in time.
2. Subjective judgment in data production. Information production using subjective judgment can result in the production of biased information.
3. Limited computing resources. Lack of sufficient computing resources limits accessibility to relevant information.
4. Security/accessibility trade-off. Easy access to information may conflict with requirements for security, privacy, and confidentiality.
5. Coded data across disciplines. Coded data from different functions and disciplines is difficult to decipher and understand. Also, codes may conflict.
6. Complex data representations. Algorithms are not available for automated content analysis across instances of text and image information. Non-numeric information can be difficult to index in a way that permits location of relevant information.
7. Volume of data. Large volumes of stored information make it difficult to access needed information in a reasonable time.
8. Input rules too restrictive or bypassed. Input rules that are too restrictive may impose unnecessary controls on data input and lose data that has important meaning. Data entry clerks may skip entering data into field (missing information) or arbitrarily change a value to conform to rules and pass an edit check (erroneous information).
9. Changing data needs. As information consumers’ tasks and the organization environment (such as new market, new legal requirements, new trends) change, the information that is relevant and useful changes.
10. Distributed heterogeneous systems. Distributed heterogeneous systems without proper integration mechanisms lead to inconsistent definitions, formats, rules, and values. The original meaning of data may be lost or distorted as data flows and is retrieved from a different system, time, place, data consumer, for same or different purposes.

Lee, Yang et.al. Journey to Data Quality. Cambridge: The MIT Press, 2006. 80-81

So, what signage would you create for a librarian?