A. Sarma. A survey of collaborative tools in software development. ISR Technical Report UCI-ISR-05-3, Donald Bren School of Information and Computer Science, University of California, Irvine, USA, 2005. [pdf]

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Collaboration is at the heart of software development. Virtually all software development requires collaboration among developers within and outside their project teams, to achieve a common ob jective. A number of classification frameworks exist that can be used to classify collaborative tools. In addition to placing the various tools in context, developers can use these kind of frameworks to select the right mix of tools for their situation. Each classification framework has a different focus: some provide a detailed taxonomy to compare tools in a particular area, some classify tools based on the functionality of the tools, some classify tools based on the high-level approach to collaboration that the tools take, and so on. However, currently no framework exists that classifies tools based on the user effort required to collaborate eectively. This however is also a critical component in choosing the “right” set of tools for a team.

In this survey, the authors take a look at collaborative tools from the perspective of user effort. For the purposes of this paper, the users define user eort as the time expended in setting up the tools, monitoring the tools, and interpreting the information from the tools. While they cannot quantify the efforts required of each tool in detail, it is clear that there is a natural ordering among dierent groups of tools. We propose a framework that identifies these groups and highlights this ordering. Based on this framework, their survey organizes the individual tools into tiers.

Tags: collaboration tools, software visualization

Google Trends is a nice tool to reconstruct how some search terms have been used over time. In the picture below I tried the name of two learning technologies paradigm which do not mean anything per se. Usually around these buzz words there are very different ideas and a great deal of interest. The graph shows how people are less and less using the word e-learning  and how the word mobile learning is barely used since the last quarter of 2004. Interesting.

With Google Trends, you can compare the world’s interest in your favorite topics. Enter up to five topics and see how often they’ve been searched for on Google over time. Google Trends also displays how frequently your topics have appeared in Google News stories, and which geographic regions have searched for them most often.

Tags: data mining, google, information metric, search engine, society, statistics

Finally I can write a RIP (Repose In Peace) on the Virtual Information Retrieval experiment. In the last strategy I was trying to detect possible differences between the two algorithms (LSI and CNG) to support the user in exploring the results of the query. Finally I found an effect when using the relative distance index between jumps.

Basically, when the user explores the results in the map, s/he select items one at a time. Our initial hypothesis was that the distance between each ‘jump’ was a function of the pertinence of the document (either detected by the user or as an absolute value).

We found that this hypothesis was not verified when looking at the distances from an absolute point of view, as the documents are not distributed equally in the map. On the contrary, if we look at these distances from a relative point of view (number of closer documents compared to the next document chosen), then we have a different overview of what happened.

It happens in fact that CNG is more efficient in splitting good results from the rest of the documents returned from the query. We have seen this through the heatmap, as LSI spreads the results all around. Subsequently, the user is more able to identify the good results as they are well isolated in the bottom part of the map. As the user moves from that selection the absolute distance increases a lot but the relative distance stays low. And certainly lower that what the user does using LSI (see test below).

> wilcox.test(distance_rel ~ as.factor(method))

Wilcoxon rank sum test with continuity correction

data:  distance_rel by as.factor(method)

W = 423460.5, p-value = 2.271e-12

alternative hypothesis: true mu is not equal to 0

In sum, we could not see an improvement of the performances as the task was maybe too difficult but we could register an interesting effect in the user strategy that reflects on the ability of each method to cluster the results in a way that facilitated the user.

Tags: clustering, information retrieval, Latent Semantic Analysis, map algorithms, spreading activation, user experience

Julian Beever is an English artist who is famous for his art on the pavements of England, France, Germany, USA, Australia and Belgium. Its peculiarity?  Beever gives his drawings an anamorphosis view, his images are drawn in such a way which gives them three dimensionality when viewing from the correct angle.

Copyright notice: the present content was taken from the following URL, the copyrights are reserved by the respective author/s.

Tags: anamorphosis maps, art, urban, urban exploration

As a final attempt to understand the exploration strategies used by the participants of the Visual Information Retrieval experiment we decided to try to map their jumps on the map in relation to the available possibilities calling this a “relative distance”. For instance, if two consecutive documents in the jump sequence were the absolute closest this would have produced a relative distance of 1.

On the contrary all the other documents which would have been at a shorter distance to the starting one, would count as more units on this relative distance.

This is a trick to understand to what extent the user tried to explore the nodes which were closer to the selected one, or, in other words, we wanted to understand whether the jumps distance was a function of the document pertinence.

The picture below represent a small excerpt of the results of this analysis. The last column tell use whether the user was reading a correct answer to the task.

Swisscom Auto-id is a spin-off of Swisscom telecommunication that aims at hitting the radio frequency tags business market. The main applications developed will target companies logistics:

Swisscom Auto-ID Services can help speed up your company’s supply management thanks to Radio Frequency Identification (RFID) technology. RFID, which allows high-speed automatic data recording using radio waves, is able to identify all manner of objects without direct contact, and can be used in applications such as logistics, inventory management and industrial automation.

One of the crucial point I am facing is that of being able to monitor the SMS activity of the participant of the field trial of STAMPS. This will provide useful information to compare the spatialized messaging with canonical strategies of communication. There are a couple of technical limitations which prevent a direct monitoring on the outgoing box so I have been thinking on possible workarounds.

1st solution: monitor the inbox for incoming messages from one of the group participant. This will require to know the numbers of all the participants which is possible. One of the limitation is that it will also parse other messages with possible infringement of the privacy.

2nd solution: ask the user to use a second phone knowing that this second device, the SMS exchanges will be monitored. A bit more fair but not practical to hang around with two phones in the pocket.

3rd solution: implement an internal private and direct one-to-one communication with other participants. This will be mostly transparent to the user but it will face the risk of not being used because people are accustomed to current SMS mechanisms.

Interesting meeting this afternoon with Martin Rajman on information retrieval techniques in relation to the STAMPS project. One of the first reference I picked up was that of the link mining, which is the data mining activity of constructing links between documents.

Then Dr. Rajman, gave me two references to the weighting scheme which are currently used to make rankings on a certain data structures: Prosit (also known as DFR) and Okapi (a variant of TF*IDF).

He mentioned briefly a technique they are working on at LIA to combine a selection technique with a Random Walk data structure which should be based on probabilistic formulas.

Basically, the building of the structural part on the graph is the result of how people would have walked our graph through many interactions.

An interesting comment Dr. Rajman made is that the different layers / properties we are trying to combine (social, semantic, geometric) are mostly precious if kept separated. These are maybe interesting to use at different time during the user interaction: for instance the user may start looking for a specific area on the map and then s/he might want to zoom on a more specific subset of the result, maybe this time focussing more on the social layer and using this to trim the results. We should enquiry how to use pertinence propagation across the different layers.

Another interesting thought from Dr. Rajman is that words are interesting to look at because they do not follow gaussian distributions in phenomena.

E. F. Churchill, J. Trevor, S. Bly, L. Nelson, and D. Cubranic. Anchored conversations: chatting in the context of a document. In Proceedings of the SIGCHI conference on Human factors in computing systems, pages 454 – 461, The Hague, The Netherlands, 2000. Association for Computing Machinery. [pdf]

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This paper describes an application-independent tool called Anchored Conversations that brings together text-based conversations and documents. The design of Anchored Conversations is based on our observations of the use of documents and text chats in collaborative settings. We observed that chat spaces support work conversations, but they do not allow the close integration of conversations with work documents that can be seen when people are working together face-to-face. Anchored Conversations directly addresses this problem by allowing text chats to be anchored into documents. Anchored Conversations also facilitates document sharing; accepting an invitation to an anchored conversation results in the document being automatically uploaded. In addition, Anchored Conversations provides support for review, catch-up and asynchronous communications through a database. In this paper we describe motivating fieldwork, the design of Anchored Conversations, a scenario of use, and some preliminary results from a user study.

Pierre told me about this work today. I was a bit surprised that he slipped over this important reference till this moment. I think this paper is extremely important for my research as focusing on making links to between specific points of the document where the discussion concentrates. In this sense the document can be seen as a map on top of which the chat has been anchored. Can we find an asynchronous alternative to this?

Tags: collaboration tools, context, graphical user interface, interaction design, map algorithms

Fortunately there are Italians like Antonio Scarponi around. They represent the genius and the creativity of some of us against the barbarian disgrace that Italy is living in this period.

His latest project is called ‘Italia in fumo’ (Italy burned and transformed in smoke). The goal of the project is to raise the awareness around the italian constitution, a document that is largely unknown by most of the italians 🙁 .

Antonio proposes to use some common form of public display to spread the knowledge of the constitution articles. With the same graphic language of the european directive concerning the cigaret consumption, the project web site proposes a series of widgets that is possible to download and use to spread the constitution around. On the picture below, for instance, there is the model for building a cigaret box cover. I find it really neat and smart! Thanks Antonio!

Tags: education, information visualization, Italy, learning technology, pedagogy, politics