Muddiest Point from Sept. 30 Class

I'm a little confused about the review before the lecture about MARC being replaced with a new system, which I know nothing about- Shouldn't we be learning more about it? Also, it was discussed that we as students- who are about to enter the field, we don't need to know how to manage and create databases but only know how they work conceptually. I just don't understand then what I should be focusing on gaining from the lectures now.

Sept. 30 Required Readings: Metadata and Content Management

1. Intro to Metadata, Pathways to Digital Information
     This reading discusses how libraries create metadata (data about data) for indexes, abstracts, bibliographic records, and really any document or data in their collection to provide access to it. But in the digital age, it's not just librarians/information professionals who are creating metadata about an object. Really anyone can create metadata by saying what the content, context, and/or structure of the object, data, information, etc is and user created metadata is gaining momentum online.
     Metadata is governed by a "community-fostered" to ensure quality and consistency but there is no consistent metadata standard that is interdisciplinary enough to be adequate for all collections/materials in all fields. Theres also an issue of managing and maintaining metadata, but algorithms can at times ease this difficulty.
    All-in-all this reading reinforced my knowledge of how metadata certifies authenticity, establishes context of content, identifies relationships between other information, provides access points, and much more to create, organize and describe information. The reading kept mentioning folksonomies, which I have no idea what that is.

2. Dublin Core Data Model
     The reading describes a data model that attempts to create international and interdisciplinary metadata. This RDF and Dublin Core initiative will identify common cross-domain qualifiers through internationalization, modularization, element identification, semantic refinement, identification of coding schemes, and identification of structured compound values.
     It's called RDF-W3C's resource description framework and it looks a lot like HTML meets a MARC record. I think it would be incredibly helpful and almost revolutionary if it worked and took over metadata standards. But it seems like one of those things that sound great in theory- but could never truly work in reality.

3. Using Mendeley
     I really like the authors approach and writing style for this reading. He seemed very honest and real about how Mendeley worked and made me consider more of his opinions had he been a more boring writer. I actually download Zotero after reading the article (I already have and use Mendeley).
     But, he basically explained Mendeley's key features and their pros and cons. His point about the social networking aspect is really relevant, because the feature really is only as good as the people in your field that are using it. The feature does not add any value if no one is using it. But, the feature does make Mendeley a strong competitor for scholarly collaboration.
     Other cool features include the recommendation feature that's based off of the papers you view and share. How Mendeley will organize your documents and cite for you. It's also free to use (expect more storage cost money).

Muddiest Point from Sept. 23 Class

I''m still pretty confused about relational databases and how the whole primary key thing works.

Sept. 23 Required Readings: Database Technologies and Applications

1. Database

• Database management systems (DBM)- software apps that capture and analyze data and allows the definition, creation, querying, update, and administration of the database. It is also responsible for maintaing the integrity and security of the stored data and for recovering infer if the system fails.
• A database is created to operate large quantities of information by inputting, storing, retrieving and managing information.
• Database design and modeling: produce a conceptual data model that reflects the information to be put in the the database, many use the entity-relationship model to do this, and that will translate into a schema that implements the relevant information into a logical database design (the most popular is the relational model represented by SQL language- this model uses a methodical approach which is normalization.
• Databases can be classified by contents, application area, and by technical aspect.

     This reading was actually the most helpful and easy to understand out of all of the readings. I think it did the best job of explaining what normalization and a what a relationship model is. There were some parts that went over my head, but I think I picked up enough of the basics to understand the main concept of databases. I thought the History section was interesting and also hard to follow but I got the most out of the Design and Modeling section.

2. Entity Relationship Model in Database

• The ER model is a data model used for describing the data aspects of a business domain- it is a systematic way of describing and defining a business process with components linked by relationships.
• The database organizes and shows entities and the relationships that exist between them and that database.
• Entity- noun, capable of independent existence
• Relationship- verb, captures how entities are related to one another
• There are different levels of entity relationship models, these include: conceptual data model, logical data model, physical data model

     This reading was very dense and required the reader to have a lot of background information to understand some of the concepts. Even after reading the Database wiki site, I struggled to understand some of the terms and explanations. The author didn't give enough information for me to understand things like cardinality constraints and what a sound definition of attributes would be. I also believe one of the challenges was that I wasn't sure what in the article I needed to be understand more than the rest. I know it all pertains to class but I didn't know what I was supposed to understand at the end. Knowing that could've helped me weed through the very dense reading.

3. Database Normalization Process
     I think this article could have been much more helpful if it was in its original format. Trying to follow explanations that required images that were missing was very challenging. I could tell that a good deal of terms and definitions were trying to be explained to the reader in a simple way, but without the images I really gained nothing from the reading other than a definition of normalization and atomicity. But who know, it seems hard for me to grasp a lot of the tech concepts- so maybe even with the images I would have been just as lost.

• Normalization- natural way of perceiving relationships between data
• Atomicity- the indivisibility of an attribute into similar parts
• Primary key- the uniques identifier required of each row

Muddiest Point from Sept. 16 Class

There wasn't too much from the lecture or assignments that I am confused on- so my muddiest point isn't going to relate directly to the class but to the readings that we were assigned. It sucks that links get broken, but I am hoping that we can go over more of what the third reading was trying to explain about database normalization. I got lost without the pictures and the layout of text made it confusing to follow the narrative.

Sept. 16 Required Readings: Multimedia Representation and Storage

Data Compression. http://en.wikipedia.org/wiki/Data_compression 

• Data compression is encoding information using fewer bits than what's in the original representation to reduce the size of the data file
• Lossless- removing statistical redundancy
• Lossy- unnecessary information is removed
• Ultimately: data compression saves space but does not always save time- and many times the quality of the data is reduced

     This article gave me the basic understanding of what data compression is. I now understand what is happening with a ZIP file. It also shed some light of compression of different kinds of data like audio and video. It seems that one needs to really consider what to compress and what not to compress if quality is a matter of importance to the particular data in question.


Data compression basics (long documents, but covers all basics and beyond): http://dvd-hq.info/data_compression_1.php  

     The above article reaffirmed the issue of choosing between quality and saving space. And a lot of it went over my head, especially when it started explaining different sort of algorithms for different kinds of data. What I did understand was really interesting. The main points that I took away include:

• Data compression allows users to store more in the same space and allows them to transfer data in less time or using less bandwidth
• Lossless compression recovers information identical to the original data (before compression)
• Lossy does not recover identical data because bits are removed
• Some compression does not always make the data smaller (the example when using RLE) so consideration needs to take place on how to compress different data
• There are different algorithms to save space for different data sequences, but quality can be lost in all of them

Edward A. Galloway, “Imaging Pittsburgh: Creating a shared gateway to digital image collections of the Pittsburgh region” First Monday 9:5 2004 http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/1141/1061 

     "Imaging Pittsburgh" was a really interesting account of how the University created online access to 20 different photographic collections spread across the University Archives Service Center, Carnegie Museum of Art, and the Historical Society of Western Pa. The University of Pittsburgh's Digital Research Library was awarded the National Leadership from IMLS to fund this project and what a lot of the account focused on and what I found most interesting was challenges to orchestrating the project. A lot of it seemed to stem from conflict of different organizational between the institutions- especially when it came setting a universal metadata scheme for the project when every institution had their own metadata scheme. It was interesting how the leaders of the project found a way to work with the different institutions and create a cohesive plan of execution.


Paula L. Webb, YouTube and libraries: It could be a beautiful relationship C&RL News, June 2007 Vol. 68, No. 6 http://crln.acrl.org/content/68/6/354.full.pdf 

     This article was a super cool read about how to use YouTube to the advantage of libraries. I think it's a cool idea because YouTube is free for the library to use and free for the patron to access. I liked how the article focused on college libraries and how to get students more familiar with the library and find out where the library is. YouTube is perfect for students because it is a very familiar platform and would probably be preferred over Libguides. It's also great because students can still have access to the videos after they graduate. It could also be a lot of fun for the librarians and staff to create videos and if they do it right, it could make the library a more efficient and familiar tool at patrons disposal.

Muddiest Point from Sept. 9 Class

I was a little bit confused about the digitization portion of Assignment 1- Are we to start with ten separate images/objects to digitize but only submit two images for grading through our flickr accounts?

Muddiest Point from Sept 2 Class

I was a little unclear if I was to create a blog entry on the required readings for week one and week two. Or if I was to skip week 1. I know it was discussed, but so much was covered that I couldn't trust my memory. Luckily an announcement was posted on course web for clarification. The announcement also clarified that I am to generate a muddiest point question, which I don't remember that being discussed in class. But all is well now.

Sept. 9 Required Readings: Computer Basics, Digitization

1. 1)  Vaughan, J. (2005). Lied Library @ four years: technology never stands
   still. Library Hi Tech, 23(1), 34-49.
   
        This article was a case study of the technology changes and up-keep in an academic library. I was impressed by how efficient the library and staff were at planning and executing swapping out every computer in what seemed to be a very busy library. But what really caught my attention was that 10% of computer time was used by the community- which I think it's great to allow the community access to the library resources but, in the case study, it became a problem for students when computer terminals would fill up.
        I wonder how the community members could use the computers? Wouldn't access require a log-in ID and password? And wouldn't such a log-in only be given to students and faculty. I understand that space and funds are limited- but if the library is going to allow community members access, then shouldn't there be an effort to provide enough computers so that users are not asked to sign off? If community members can use the computers then they should not be the first to be asked to sign off (as the case study explained). I don't think the library should allow access to "everyone" if "everyone" cannot be equally accommodated.
   
   2)  Doreen Carvajal. European libraries face problems in digitalizing. New York Times. October 28, 2007
   http://www.nytimes.com/2007/10/28/technology/28iht-LIBRARY29.1.8079170.html 
   
      
        This was an interesting article that explained the ongoing attempts of many European countries combined and individual European libraries and museum to some-what follow in Googles footsteps by digitizing collections. The goal is to preserve the cultural heritage without  violating any copyright laws (as Google did). The governments of these countries have put a lot of money towards this project, but more is needed to accomplish the goal. These libraries and museums are now looking to private companies, like Google, to help fund the digitization project.
      When the goal is to preserve the heritage of an entire culture, who is responsible to pay the large amount of money to make it happen? Is digitization really the same thing as preservation? Should private companies be allowed to pay in to try to make a profit off a culture?
   
   3)  A Few Thoughts on the Google Books Library Project http://www.educause.edu/ero/article/few-thoughts-google-books- library-project
   
       I found the authors argument about how Google does not make books obsolete, but helps to preserve books. And of course Google is giving a second life to many books that have been out of print or would have otherwise been very difficult to gain access to. Google can make very strong arguments about all the good the Google Books project is doing for people, culture, and books. But is digitization really preserving anything? Technologies are always changing. What if Google goes out of business? All the books could be lost. And if someone finds away to ensure permanent online access and preservation to the Google books, are they really preserved when Google cannot properly catalog or index the books in an intelligent manner?