“Information professionals are designers. We build information systems, services, spaces, and objects that we hope will help users find, use, create, and share information.” Bowler et al. (2011, p.723)
It is important to understand a systems users’ information behaviour when designing usable systems. User centred design is one such technique that incorporates the potential user in the design process. One such approach is to incorporate social bookmarking/tagging. The ultimate goal is to have a retrieval system that adapts to user behaviour rather than expecting the user to adapt to the system. Social tagging has two broad implications for user-centred design: it provides users with a flexible and personalized organization/access tool and it offers a venue for collecting empirical data on how users categorize and name information resources.
For a digital Library to be effective it has to be user friendly and easy to use. A well designed retrieval system that incorporates some common standards should be able to achieve this.
•Social Tagging and Digital Library Collections
Bookmarking.Net via Facebook outlined that in order to instruct Google what to display, you need to specify Google-compatible Meta tags, and update your HTML schema. This can be applied to any platform.
•Social Tagging as a Flexible Mechanism for Organizing Information for Users
As a result of a community tagging resources, the collection of tags defined by them creates a tag-based organization which can be referred to as a folksonomy. A folksonomy is basically known as weighted set of tags, and may refer to a whole collection/site. Blog post by arkaitz on http://blog.zubiaga.org/
•Social Tagging as a Way to Understand Users
When it comes to annotation tools not only can users add comments and highlighting to articles and eBooks, but they can then log-in to their account and pull off all of these notes into one central document. The device can also be used to see which sections of text other users are focusing on. BMJ Group Blogs.
Challenges & Barriers
As with any design process there are always hurdles to overcome. Designing a retrieval system has always been an area of considerable difficulty. The interpretation of tagging between humans and machines may create new problems if essential questions about how social tagging corresponds to online communications, what objects the tags refer to, who the interpreters are, and why they are engaged are not explored systematically.
•A common problem with tagging is that words such as web are overused and therefore become both pointless and lost in a sea of countless search returns. Likewise specific tags like acronyms may only make sense or can even be interpreted differently, among their particular communities of users. Thirdly polysemy is a term has two or more similar meanings
•Confusion in social tagging occurs due to the interpretations of what tags are meant to represent. The difficulty lies in the interpretation between the technical and social dimensions. “Tags, as a form of descriptive and visible metadata need a conceptual framework so that they can be constructed, presented, and processed systematically” Huang, A. W. C., & Chuang, T. R. (2009, p.347).
•Another issue is that many social tagging systems come with a function that provides users with tags supplied by other users to suggest a tag for the resource. This in turn restricts the user in their ability to describe the resource uniquely or even at all differently. This defeats the purpose of the tagging system.
Reoccurring in Online Discussions
Attaining Best Results
Several themes were ever present throughout the environmental scan that would be of relevance to a digital library. Firstly social bookmarking is seen by many as a tool to expand yourself, your business or even a digital library and as such there are many organisations vying for people to use their tools in order to benefit from using social bookmarking effectively. With Twitters hash tag function it is easy to follow what tweets have tagged social book marking.
Daily Ponder wrote on April 6th wrote:
“The Advantages of Search Engine Submission http://freesearchenginesubmit.org #Socialbookmarking”
SanFranciscoMobile wrote on the March 31st:
“#SocialBookmarking is hot! Watch these videos and learn how to master #Social Book Marking! http://bit.ly/XTc3fT”
Throughout blogs and discussions people are championing different sites that cater for peoples information needs in the best possible manner. “erikchoi” posted on infoseeking.org on the April 14th:
“Pinterest is a sort of newer version of image bookmarking system in which people are allowed to create and manage images based on his/her personal interests.”
One of the main difficulties is to understand the intuition behind how people carry out searches so that you know what tags will gain you most exposure. Joanne Ptolomey wrote on her twitter:
“Exploring social tagging in relation to curating health information. Looking for examples.”
With the general consensus being whatever seems the most logical fit. The socialmaximiser blog states you should not use automated tools which do not care a thing for quality. Social bookmarking is effective only if you submit to most relevant categories, using proper tags, titles and descriptions. This underlies the importance to give careful consideration as to what tags to use and to try and think what other people will search for.
There is clearly money to be made from perfecting the perfect tool that returns the best search results. Tools seek to make content more accessible, practical and valuable through an automated generation of semantic metadata, the incorporation of user-defined metadata and to incorporate the capabilities of user-contributed tags. However this is an extremely difficult practice, as is shown in the next two examples. Chrisjhorn wrote on his blog March 2nd:
“OpenCalais’s behaviour is clearly unstable and unpredictable. I’ve little doubt that OpenCalais will continue to improve: as I noted above, it is already a very good tool, albeit at this time largely limited to the English language.”
Another possible software choice is Sophia which StevenArch explained:
“Sophia uses algorithms based on semiotics to identify and categorize documents. Per se, it does not have any knowledge about any specific natural language, and so instead analyses the patterns of words and constructs appearing in the documents which it is given.”
While there were many other areas discussed pertaining social tagging online, these were three that stood out and can be easily applicable to any digital library that wants to look at this issue. This tied in conjunction with the previous sections, common themes as well as challenges and barriers lays out a much clearer picture for the area of social tagging as a method of information retrieval.
Issues for a Digital Library
The overriding issue to incorporate this method is its overall functionality. Can digital libraries make it efficient and also a worthwhile endeavour? In terms of ARTstor there are certain issues that need to be given adequate attention if they were to incorporate social tagging in an information retrieval capacity. Firstly a key issue concerns the impact of social tags to the subject indexing process of an information organization. Who is going to oversee the implementation and monitor whether it is working or not, adjust it appropriately so the best results are achieved and importantly make sense of it all. These are all time consuming restraints that must be given careful consideration and the financial aspect must not be forgotten.
As Kakali and Papatheodorou (2010) outline that a relevant issue concerns the process of the social tags exploitation. It is crucial to come up with a system that takes in to consideration the frequency and the criteria of the tag assessment process. They continue to explain that one method to carry this out would be to refine the inserted tags by searching, in predefined time periods, and in turn to identify overlapping terms and keep in the folksonomy only the non-overlapping tags, while the overlapping to be inserted in the local authority file. This of course is not straight forward and issues potentially arising are extremely apparent to see especially when taking in to consideration that libraries have a limited number of personnel. One can imagine for example ArtSTOR which would need to incorporate this new system by having even more tags to be catalogued.
Kohl (2010) explains ARTstor has some noticeable weaknesses that include the inability of the user to browse by artist; the lack of suggestions for possible misspellings; and the lack of bibliographic resources for further research. On top of this, it would be beneficial if each classification in the Browse function was further subdivided by material. While most likely due to issues of copyright, the collection had limited coverage of modern and contemporary art. It is clear to see that this coupled with the fact there is a lack of image and subject descriptors that this could be improved with community social tagging.
As unearthed in the environmental scan the issue of users tagging in a manner that is useful can also be problematic. Kakali (2010) & Farooq et al. (2007) go in to some detail on this matter. One important component to social tagging being a successful tool is to incorporate a system that suggests tags by other users. One system suggested is CiteULike which combats this, it allows users when tagging items to conveniently select and reuse tags from their personal collections. Cataloguers have expressed their reservation about the tags being inserted by less qualified users such as undergraduate students and external users. It was stated that if faculty and post-graduate students tagged items a better end result would be achieved. Nevertheless a possibility is to buy LibraryThing’s tags or to encourage the users to enrich the local folksonomy.
Note: ARTstor received a three year grant by The Institute of Museum and Library Services (IMLS) of $413,378 to support a project investigating and evaluating ways of improving library and museum searching and social tagging in 2011 and it will be interesting to see the results once available. The issues raised here will no doubt be considered carefully when trying to implement a successful system.
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