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Picasa vs. iPhoto vs. Flickr vs. Panoramio

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Ledges along Doan Brook in ClevelandEarlier I mentioned that I have some photos uploaded to Panoramio. I’ve also played with Flickr off and on, and have recently started uploading some photos there as well. To add to the confusion, I use Picasa to manage photos on my hard drive, and my wife uses iPhoto on her Mac. Picasa has a web albums feature, and I’m sure iPhoto has something similar with a .Mac account.

Why use four different services that overlap each other to such a degree? Picasa and iPhoto both do the important job of managing photos locally, Flickr seems to have the largest community and the most widgets written for it, and Panoramio integrates with Google Earth. Since I want to do all those things, I have to use them all.

There are ways to make them play nice together. You can use a Gmail account to email photos from Picasa to Flickr, and so far it seems to work fairly well. There are a few iPhoto plugins to upload to Flickr and you can use iPhoto to subscribe to Flickr photostreams. Google just bought Panoramio, so I’m sure there will be more integration there soon as well.

Even with all these options, there are some annoyances. Picasa’s keyword tagging is not very useful, it only allows one-word tags. I tried creating multi-word tags with dashes or by enclosing them in quotes, but Picasa ate the special characters. There’s also the complication of managing public photos vs private photos.

Still, it is amazing how well these different websites and programs work together, through the magic of RSS, web API, and plain old email.

If you’d like, you can see my Flickr photos here. You can also see my photos in Panoramio, or just look close enough in Google Earth, since a few of my photos now how up there.

Notes: Why are online catalogs still hard to use?

Academic Papers, Usability, , , , , ,

Borgman, C.L. (1996). Why are online catalogs still hard to use? Journal of the American Society for Information Science, 47 (7): 493-503. 

In this 1996 study, Borgman revisits a 1986 study of online library catalogs. In the original study, computer interfaces and online catalogs were still fairly new—the study looked at how the design of traditional card catalogs could inform the design of new online catalogs. By the time of this study online catalogs were common but still not easy to use. Three kinds of knowledge were seen as necessary for online catalog searching: conceptual knowledge about the information retrieval process in general, semantic knowledge of how to query the particular system, and technical knowledge including basic computer skills. Semantic knowledge and technical knowledge differ here in the same way as semantic and syntactic knowledge in computer science. The study also covers specific concepts like action, access points, search terms, boolean logic, and file organization. In the short term, Borgman recommends training and help facilities to help users gain the skills they need to use current systems. In the long run, though, libraries must employ the findings of information-seeking process research if they are ever going to create usable interfaces.

The study does point out a number of reasons why online catalogs are difficult for users, whether it’s because they lack computer skills or semantic knowledge. One good example is from a common type of query language. Even if the user knows that “FI” means “find” and “AU” means author, they may not know whether to use “FI AU ROBERT M. HAYES,” “FI AU R M HAYES,” “FI AU HAYES, ROBERT M,” etc., and how the results will differ. Unfortunately the article lacks clear instructions or examples of how to make the systems better. The conclusion that different types of training materials could be helpful seems to me like a bandage rather than a cure.

I think a lot of the criticisms are still true, but that modern cataloging and searching systems have become easier. I’m not so sure it’s because catalog designers have started applying information-seeking research in their interfaces, though. It almost seems like library systems are being made easier in self-defense. Users are getting more and more used to a Google or Yahoo type interface—a simple search box that looks at full text and uses advanced algorithms to find relevant results. I think part of this is due to the fact that people in the library field have experience with complicated, powerful structure search systems and are used to a lot of manual encoding of records. Web developers, lacking this background, have been more free to think in terms of searching massive amounts of unstructured data and automating the collection and indexing process. I also think that simple things such as showing the results, including summaries of each item, in a scrollable, clickable list, have helped a great deal to support the information seeking process. Things like search history and “back” and “forward” buttons, “search within these results,” automatic spell checking, etc. are becoming pretty standard as well.

Notes: Helping people find what they don’t know

Academic Papers, Writing, , , , ,

Nicolas J. Belkin, Helping people find what they don’t know, Communications of the ACM, v.43 n.8, p.58-61, Aug. 2000

In this article, Belkin argues that since people generally start searching for information when they don’t know much about a subject. It is therefore problematic that many search systems require knowledge of the domain in order to get good results, for example when users do not know either the specific keywords or controlled vocabulary of the system. His group feels that the best way around this is for the system to make suggestions along the way. There are two techniques that can be used: system-controlled, where the user’s query is enhanced automatically by the system using algorithms like word frequency, and user-controlled, where the user is given the results of their query along with suggestions to make it more effective. The author’s team found that suggestions were most effective when the user was able to control which suggestions were used and when the user knew how the suggestions were generated and was comfortable with the results.

The author’s findings seem both intuitive and promising. It makes sense that in an interactive structured searching system giving the user suggestions and allowing them to take them or leave them would work well, and the suggestions should neither be bizarre or mysterious. But with the rise of the World Wide Web, I think it’s pretty clear that users with less domain knowledge prefer less-structured searching environments. In my experience, users who are new to a system will type unstructured, keyword queries into anything that even looks like a search box, even if it is clearly labeled as a field for author name, product code, or start date. Power users, on the other hand, often have more knowledge about the data then the system’s programmers—so for these sorts of suggestions to be useful, the algorithm would need to do more than just call up synonyms. The article makes it clear that these findings are early, so I would be interested to see what they have come up with since 2000.

These ideas could be applied to both structured and unstructured searching environments, though my guess is that they would be easier to implement in more structured environments because the structure of the system can be used to generate the suggestions. There certainly have been a number of projects which have tried to provide something like this with general web searching. Rudimentary systems like Google Suggest  or more advanced ones like Teoma show off the potential. Notice, however, that neither of these has exactly taken the search engine industry by storm, meaning people are apparently happy to muddle along with plain keyword searching and advanced ranking algorithms. I do wonder if their finding that users liked to have some idea about how suggestions were found would apply here as well—would users be happier with Google if they were told why PageRank picked a certain site as the number one result? Since the algorithms used by Google, Yahoo, MSN and others are trade secrets I doubt we’ll see anything like that in the near future. On the other hand, Amazon.com’s recommendation engine does tell the user why a certain book was suggested, and allow the user to remove certain suggestions. Although it is not really a search tool, it follows the precepts discussed here and seems to be successful.