Why are most Twitter clients for the iPad just so bad?
Recently there is has been lots of innovation in App design for tablets. Apps like Qwiki, Flipboard, Zite, Pulse, Reedr have really figured out how to give a good user experience on a tablet. However, sadly, most twitter clients have not. Even iphone twitter clients like TweetBot are better than most iPad twitter clients as they are more optimised for the display size. The fundamental problem seems to be that twitter client developers think that iPad is just a scaled up iPhone.
With the help of this thinking various successful iPhone twitter client developers have released new iPad clients which are nothing more than scaled up versions of their iPhone application, with some added iPad elements. For instance, the following screenshots are from Twitterific and Echofon on the iPad.
T
As you may observe, over 90% of the screen it taken up by a single UITableView. IMO the UITableView is an efficient way to present of a list of items (or a stream of tweets) in a small display. It makes no sense however, to just adopt the same thinking on a larger screen. A better use of the iPad screen is made in TweetDeck for instance. It makes more rich use of the screen, as the following screenshot depicts. However, unfortunately, the TweetDeck app has some performance issues.
Recently a new bread of applications such as Flipboard and Zite have emerged. These applications enable you to consume information in a magazine like fashion. I believe they too are an efficient way to consume your twitter feed and lists however they are not design to be full fledged clients. I believe there is a gap in the iPad App market for twitter clients that make rich use of the screen yet do so in a computationally efficient manner.
If you are aware of any good twitter clients please post to the comments...
How cloud computing has transformed the PC
Increase Loopback devices in Ubuntu
I've been using a lot of VMs recently. By default the number of loopback devices set in Ubuntu is just 8. So if you want to mount 10 VM disks, your out of luck.
An easy way I'v found to increase loopback devices is:
edit /etc/modprobe.d/options
and enter the line (replace n, for the number of loopback devices you want. Max. number is 255).
options loop max_loop=n
Apple To Dominate Tablet Market Through 2012, iSuppli Says
How to recover data from an formatted HFS Drive
Last week my Time Machine Backup Hard disk suddenly died! Everytime I plugged the hard disk, my mac did not recognise the file system (it was a HFS+ partition) and asked my to format it. I did format it, only to realise that I had lost some precious data.
How do you recover data from a formatted hard disk? Enter Data Rescue from PROSoft Engineering. I used Data Rescue II (only to realise afterwards that a new version was available). It took more than 2 days to scan the hard disk (1 TB hard disk, sector by sector analysis) and afterwards it recreated the files it found.
Recreation of the files, was also a lengthy process, and took nearly 10 hrs. After it recovers the files it presents a list of the kinds of files you might be interested in restoring. I selected the files I was interested in, research papers and my iPhoto Collection.
Recovery of the selected files (around 55.6GB) took around 3 hrs.
All in all I'm really grateful for such fantastic software. For all the windows users out there.... My NTFS hard disk has failed as well 
(bad start to the year! 
). Currently I'm using ParetoLogic's Data Recovery Pro. The data recovery process is currently on going (since 5 days).
Is Data Science emerging as a New Domain in Computer Science?
I've just completed reading Chapter 5 of Beautiful Data. I planned to write a 
blog post about this book, however this chapter contained some new insights for me which I thought were valuable to share. This book has some excellent chapters covering significant developments in the domain of data storage, retrieval and analysis. Chapter 5 is titled "Information Platforms and the Rise of the Data Scientist" written by Jeff Hammerbacher.
The chapter explores the challenges Facebook faced in analysing the data it is collecting and how existing RDMS solutions (MySQL and Oracle) were not up to the task of collecting and enabling analysis of highly fluid data such as clickstreams from millions of users (Currently 2.5 Petabytes is stored and new data is collected at 14 TB/day). The author goes on to discuss the solution they developed internally at Facebook (based on Cloud technologies such as Hadoop and unstructured data).
Analysis of large scale data is becoming a common problem in a large number of domains. Web companies such as Facebook, Google are not the only ones in the World that analyse huge amounts of data. Several scientific experiments such as the CERN LHC produce gigantic amounts of data that needs to be analysed (The recent book Fourth Paradigm by Microsoft Research explores data intensive scientific initiatives).
So many new skills are required to manage this data: designing storage architectures, high speed retrieval architectures, authoring data analysis workflows and finally communicating the results of the analysis. All these tasks are multi-disciplinary. Some tasks are related to Computer Science (design of data storage and retrieval systems), some to Business Analysis (authoring data analysis), some tasks belong to statisticians (the actual algorithms performing the analysis) and some to engineers (the underlying infrastructure for storing and processing the data).
Can this multi-discplinary approach to data management be termed as "Data Science". This is a term which I believe is increasingly gaining traction.
Making the move to Cloud backup
My Time Machine Hard disk failed 2 days ago. I lost all my backups! Unfortunately I had reinstalled my system just last week and had not yet fully restored from the latest time machine backup. Fortunately I have recovered everything other than my pictures.
I don't want to experience such loss again, so I'm moving towards Cloud based backup. I gain a few things, but loose some as well. The service I selected is Mozy. They provide unlimited storage at an economical rate. However their backup/restore tool for the Mac does not support Proxies (their windows one apparently does). Moreover, Mozy's tool also does not allow me to browse my backups in a fine-grained fashion as Time Machine does. In Time Machine I can restore individual folders and files and browse my backup history over weeks and months. The Mozy tool does not provide such fine-grained history browsing.
Finally, uploading is such a hassle! It took me more than a day to upload a limited subset of data from my laptop (~60GB). Downloading fortunately is faster.
What do I gain from a cloud based backup solution? Hopefully I will not loose my data again.
However because there are certain advantages to local backups as well, I plan to do daily Time machine backups, on a new 1TB HD and weekly cloud backups. As for my pictures, I have a MobileMe subscription and those albums I shared there with friends and family I still have them. So in future I plan to upload all my new pictures to MobileMe.
Turing (A Novel about Computation) Review
I just completed reading Turing (A Novel about Computation). Its a post-modern novel around a computer programme named "Turing". It has a captivating story line that guides the reader through centuries of human ingenuity and intellectual achievement. The book also presents a successful fusion of history, economics, mathematics, computer science that is brilliant and original. I would definitely recommend it to people who know little about computing, because the book explains a lot about the core principles behind computer science in a down to earth fashion. However sometimes the explanations are so rudimentary and superficial that they are rendered inaccurate. Nevertheless its a good book and is definitely worth a read.
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