Archive for the ‘surveillance’ Category
This tells me my job with foursquare is to be “driven” like a calf into a local business. Of course, this has been the assumption from the start. But I had hoped that somewhere along the way foursquare could also evolve into a true QS app, yielding lat-lon and other helpful information for those (like me) who care about that kind of thing. (And, to be fair, maybe that kind of thing actually is available, through the foursquare API. I saw a Singly app once that suggested as much.) Hey, I would pay for an app that kept track of where I’ve been and what I’ve done, and made that data available to me in ways I can use.
foursquare as a kind of Lifebits I think is what Doc Searls is describing. A form of self-tracking a la Stephen Wolfram or Gordon Moore. Instead foursquare is the carrot being dangled to lure you into giving your business to a particular retailer. After that you accumulate points for numbers of visits and possibly unlock rewards for your loyalty. But foursquare no doubt accumulates a lot of other data along the way that could be use for the very purpose Doc Searls was hoping for.
Gordon Moore’s work at Microsoft Research bootstrapping the My Lifebits project is a form of memory enhancement, but also logging of personal data that can be analyzed later. The collection or ‘instrumentation’ of one’s environment is what Stephen Wolfram has accomplished by counting things over time. Not to say it’s simpler than the My Lifebits, but it is in someways lighter weight data (instead of videos and pictures, mouse clicks and tallies of email activity, times of day, etc.) There is no doubt that foursquare could make a for profit service to paying users where they could collect this location data and serve it up to subscribers, letting them analyze the data after the fact.
I firmly believe a form of My Lifebits could be aggregated across a wide range of free and paid services along with personal instrumentation and data collecting like the kind Stephen Wolfram does. If there’s one thing I’ve learned readings stories about inventions like these from MIT’s Media Lab is that it’s never an either or proposition. You don’t have to just adopt Gordon Moore’s technology or Stephen Wolfram’s techniques or even foursquare’s own data. You can do all or just pick and choose the ones that suit your personal data collection needs. Then you get to slice, dice and analyze to your heart’s content. What you do with it after that is completely up to you and should be considered as personal as any legal documents or health records you already have.
Which takes me back to an article I wrote some time ago in reference to Jon Udell calling for a federated LifeBits type of service. It wouldn’t be constrained to one kind of data, but all the LifeBits aggregated potentially and new repositories for stuff that must be locked down and private. So add Doc Searls to the list of bloggers and long time technology writers who see an opportunity. Advocacy (in the case of Doc’s experience with foursquare) on behalf of sharing unfiltered data with the users on whom data is collected is one step in that direction. I feel Jon Udell is also an advocate for users gaining access to all that collected and aggregated data. But as Jon Udell asks, who is going to be the first to attempt to offer this up as a pay-for service in the cloud where you can for a fee access your lifebits aggregated into one spot (foursquare,twitter,facebook,gmail,flickr,photostream,mint,eRecords,etc.) so that you don’t spend your life logging on and logging off from service to service to service. Aggregation could be a beautiful thing.
- Picture This: Hosted Lifebits in the Personal Cloud | Cloudline | Wired.com (carpetbomberz.com)
- Stephen Wolfram Blog : The Personal Analytics of My Life (carpetbomberz.com)
- Foursquare Takes on Yelp With Recommendations. Our Verdict: Good Start, Not There Yet (readwriteweb.com)
On Tuesday, the company unveiled its new ARM Cortex-M0+ processor, a low-power chip designed to connect non-PC electronics and smart sensors across the home and office.
Previous iterations of the Cortex family of chips had the same goal, but with the new chip, ARM claims much greater power savings. According to the company, the 32-bit chip consumes just nine microamps per megahertz, an impressively low amount even for an 8- or 16-bit chip.
Lower power means a very conservative power budget especially for devices connected to the network. And 32 bits is nothing to sneeze at considering most manufacturers would pick a 16 or 8-bit chip to bring down the cost and power budget too. According to this article the degree of power savings is so great in fact that in sleep mode the chip consumes almost no power at all. For this market Moore’s Law is paying off big benefits especially given the bonus of a 32bit core. So not only will you get a very small lower power cpu, you’ll have a much more diverse range of software that could run on it and take advantage of a larger memory address space as well. I think non-PC electronics could include things as simple as web cams or cellphone cameras. Can you imagine a CMOS camera chip with a whole 32bit cpu built in? Makes you wonder no just what it could do, but what ELSE it could do, right?
The term ‘Internet of Things‘ is bandied about quite a bit as people dream about cpus and networks connecting ALL the things. And what would be the outcome if your umbrella was connected to the Internet? What if ALL the umbrellas were connected? You could log all kinds of data, whether it was opened or close, what the ambient temperature is. It would be like a portable weather station for anyone aggregating all the logged data potentially. And the list goes on and on. Instead of Tire pressure monitors, why not also capture video of the tire as it is being used commuting to work. It could help measure the tire wear and setup and appointment when you need to get a wheel alignment. It could determine how many times you hit potholes and suggest smoother alternate routes. That’s the kind of blue sky wide open conjecture that is enabled by a 32-bit low/no power cpu.
- ARM Upgrades Cortex-M0 Processor for Low-power Applications (pcworld.com)
- ARM Cortex-M0+ targets low power tech (slashgear.com)
One day I’m sure everyone will routinely collect all sorts of data about themselves. But because I’ve been interested in data for a very long time, I started doing this long ago. I actually assumed lots of other people were doing it too, but apparently they were not. And so now I have what is probably one of the world’s largest collections of personal data.
In some ways similar to Stephen Wolfram, Gordon Bell at Microsoft has engaged in an attempt to record his “LifeBits” using a ‘wearable’ computer to record video and capture what goes on in his life. In my opinion, Stephen Wolfram has done Gordon Bell one better by collecting data over a much longer period and of a much wider range than Gordon Bell accomplished within the scope of LifeBits. Reading Wolfram’s summary of all his data plots is as interesting as seeing the plots themselves. There can be no doubt that Stephen Wolfram has always and will continue to think differently than most folks, and dare I say most scientists. Bravo!
The biggest difference between MyLifeBits versus Wolfram’s personal data collection is the Wolram’s emphasis on non-image based data. The goal it seems for the Microsoft Research group is to fulfill the promise of Vannevar Bush’s old article titled “As we may think” printed in the Atlantic, July 1945. In this article Bush proposes a prototype of a more ‘visual computer’ that would act as a memory recall and analytic thinking aid. He named it the Memex.
Gordon Bell and Jim Gemmell of Microsoft Research, seemed to be focused on the novelty of a camera carried and taking pictures automatically of the area immediately in front of it. This log of ‘what was seen’ was meant to help cement visual memory and recall. Gordon Bell had spent a long period of time digitizing, “articles, books, cards, CDs, letters, memos, papers, photos, pictures, presentations, home movies, videotaped lectures, and voice recordings and stored them digitally.” This over emphasis on visual data I think if used properly might be useful to some but is more a product of Gordon Bell’s own personal interest in seeing how much he could capture then catalog after the fact.
Stephen Wolfram’s data wasn’t even necessarily based on a ‘wearable computer‘ the way MyLifeBits seems to be. Wolfram built in a logging/capture system into things he did daily on a computer. This even included data collected by a digital pedometer to measure the steps he would take in a day. The plots of the data are most interesting in comparison to one another especially given the length of time over which they were collected (a much bigger set than Gordon Bell’s Life Bits I dare say). So maybe this points to another step forward in the evolution of Lifebits perhaps? Wolfram’s data seems to be more useful in a lot of ways, he’s not as focused on memory and recall of any given day. But maybe a synthesis of Wolfram’s data collection methods and analysis and Gordon Bell’s MyLifeBits capture of image data might be useful to a broader range of people if someone wanted to embrace and extend these two scientists’ personal data projects.
- Stephen Wolfram – The Personal Analytics of My Life (adafruit.com)
- 5 Things I Learned About the Future from Stephen Wolfram (readwriteweb.com)
While I agree there might be a better technical solution to the DNS blocking adopted by SOPA and PIPA bills, less formal networks are in essence filling the gap. By this I mean the MegaUpload takedown that occurred yesterday at the the order of the U.S. Justice Department. Without even the benefit of SOPA or PIPA, they ordered investigations, arrests and takedowns of the whole MegaUpload enterprise. But what is interesting is the knock-on effects social networks had in the vacuum left by the DNS blocking. Within hours the DNS was replaced by it’s immediate pre-cursors. That’s right, folks were sending the IP addresses of available MegaUpload hosts by plain text in Tweet messages the world ’round. And given the announcement today that Twitter will be closing in on it’s 500 Million’th account being created I’m not too worried about a technical solution to DNS blocking. That too is already moot, by virtue of the the fact of social networking and simple numeric IP addresses. Long live IPv4 and the quadruple octets 255.255.255.xxx
The number of U.S. government requests for data on Google users for use in criminal investigations rose 29 percent in the last six months, according to data released by the search giant Monday.
Not good news in imho. The reason being is the mission creep and abuses that come with absolute power in the form of a National Security Letter. The other part of the equation is Google’s business model runs opposite to the idea of protecting people’s information. If you disagree, I ask that you read this blog post from Christopher Soghoian, where he details just what exactly it is Google does when it keeps all your data unencrypted in its data centers. In order to sell AdWords and serve advertisements to you, Google needs to keep everything open and unencrypted. At the same time they aren’t too casual in their stewardship of your data, but they do respond to law enforcement requests for customer data. To quote Seghoian at the end of his blog entry:
“The end result is that law enforcement agencies can, and regularly do request user data from the company — requests that would lead to nothing if the company put user security and privacy first.”
And that indeed is the moral of the story. Which leaves everyone asking what’s the alternative? Earlier in the same story the blame is placed square on the end-user for not protecting themselves. Encryption tools for email and personal documents have been around for a long time. And often there are commercial products available to help accomplish some level of privacy even for so-called Cloud hosted data. But the friction point is always going to be the level of familiarity, ease of use and cost of the product before it is as widely used and adopted as Webmail has been since the advent of desktop email clients like Eudora.
So if you really have concerns, take action, don’t wait for Google to act to defend your rights. Encrypt your email, your documents and make Google one bit less culpable for any law enforcement requests that may or may not include your personal data.
- Google Reports Surge in Government Requests for User Data (blogs.wsj.com)
- Government requests to Google for information on users has spiked. (ritcyberselfdefense.wordpress.com)
- Pioneering Campus CIOs Say Necessity Drives Shift to Cloud – Campus Technology (carpetbomberz.com)
Cameron said in an interview posted on the ID conferences website last month that he was disappointed about the lack of an industry advocate championing what he has dubbed “user-centric identity”, which is about keeping various bits of an individuals online life totally separated.
CRM meet VRM, we want our Identity separated. This is one of the goals of Vendor Relationship Management as opposed to “Customer Relationship”. I want to share a set of very well defined details with Windows Live!, Facebook, Twitter, Google. But instead I exist as separate entities that they then try to aggregate and profile to learn more outside what I do on their respective WebApps. So if someone can champion my ability to control what I share with which online service all the better. If Microsoft understands this it is possible someone like Kim Cameron will be able to accomplish some big things with Windows Live! ID logins and profiles. Otherwise, this is just another attempt to capture web traffic into a commercial private Intraweb. I count Apple, Facebook and Google as Private Intraweb competitors.
In short, big data simply means data sets that are large enough to be difficult to work with. Exactly how big is big is a matter of debate. Data sets that are multiple petabytes in size are generally considered big data (a petabye is 1,024 terabytes). But the debate over the term doesn’t stop there.
There’s big doin’s inside and outside the data center theses days. You cannot spend a day without a cool new article about some new project that’s just been open sourced from one of the departments inside the social networking giants. Hadoop being the biggest example. What you ask is Hadoop? It is a project Yahoo started after Google started spilling the beans on it’s two huge technological leaps in massively parallel databases and processing real time data streams. The first one was called BigTable. It is a huge distributed database that could be brought up on an inordinately large number of commodity servers and then ingest all the indexing data sent by Google’s web bots as they found new websites. That’s the database and ingestion point. The second point is the way in which the rankings and ‘pertinence’ of the indexed websites would be calculated through PageRank. The invention for the realtime processing of this data being collected is called MapReduce. It was a way of pulling in, processing and quickly sorting out the important highly ranked websites. Yahoo read the white papers put out by Google and subsequently created a version of those technologies which today power the Yahoo! search engine. Having put this into production and realizing the benefits of it, Yahoo turned it into an open source project to lower the threshold of people wanting to get into the Big Data industry. Similarly, they wanted to get many eyes of programmers looking at the source code and adding features, packaging it, and all importantly debugging what was already there. Hadoop was the name given to the Yahoo bag of software and this is what a lot of people initially adopt if they are trying to do large scale collection and real-time analysis of Big Data.
Another discovery along the way towards the Big Data movement was a parallel attempt to overcome the limitations of extending the schema of a typical database holding all the incoming indexed websites. Tables and Rows and Structured Query Language (SQL) have ruled the day since about 1977 or so, and for many kinds of tabbed data there is no substitute. However, the kinds of data being stored now fall into the big amorphous mass of binary large objects (BLOBs) that can slow down a traditional database. So a non-SQL approach was adopted and there are parts of the BigTable database and Hadoop that dump the unique key values and relational tables of SQL to just get the data in and characterize it as quickly as possible, or better yet to re-characterize it by adding elements to the schema after the fact. Whatever you are doing, what you collect might not be structured or easily structured so you’re going to need to play fast and loose with it and you need a database of some sort equal to that task. Enter the NoSQL movement to collect and analyze Big Data in its least structured form. So my recommendation to anyone trying to get the square peg of Relational Databases to fit the round hole of their unstructured data is to give up. Go NoSQL and get to work.
This first article from Read Write Web is good in that it lays the foundation for what a relational database universe looks like and how you can manipulate it. Having established what IS, future articles will be looking at what quick, dirty workarounds and one off projects people have come up with to fit their needs. And subsequently which ‘Works for Me’ type solutions have been turned into bigger open source projects that will ‘Work for Others’, as that is where each of these technologies will really differentiate themselves. Ease of use and lowering the threshold will be deciding factors for many people’s adoption of a NoSQL database I’m sure.