Category: Crowdsourcing

An analyst forecasting contest ala SuperForecasting & 1st #Storage-QoW

Posted on by Ray in Crowdsourcing, Decision making, Forecasting, QoW 2015, R&D measures, Scenario planning

71619318_80d2135743_zI recently read the book SuperForecasting: the art and science of prediction by P. E. Tetlock & D. Gardner. Their Good Judgement Project has been running for years now and the book is the results of their experiments.  I thought it was a great book.

But it also got me to thinking, how can industry analysts do a better job at forecasting storage trends and events?

Impossible to judge most analyst forecasts

One thing the book mentioned was that typically analyst/pundit forecasts are too infrequent, vague and time independent to be judge-able as to their accuracy. I have committed this fault as much as anyone in this blog and on our GreyBeards on Storage podcast (e.g. see our Yearend podcast videos…).

What do we need to do differently?

The experiments documented in the book show us the way. One suggestion is to start putting time durations/limits on all forecasts so that we can better assess analyst accuracy. The other is to start estimating a probability for a forecast and updating your estimate periodically when new information becomes available. Another is to document your rational for making your forecast. Also, do post mortems on both correct and incorrect forecasts to learn how to forecast better.

Finally, make more frequent forecasts so that accuracy can be assessed statistically. The book discusses Brier scores as a way of scoring the accuracy of forecasters.

How to be better forecasters?

In the back of the book the author’s publish a list of helpful hints or guidelines to better forecasting which I will summarize here (read the book for more information):

  1. Triage – focus on questions where your work will pay off.  For example, try not to forecast anything that’s beyond say 5 years out, because there’s just too much randomness that can impact results.
  2. Split intractable problems into tractable ones – the author calls this Fermizing (after the physicist) who loved to ballpark answers to hard questions by breaking them down into easier questions to answer. So decompose problems into simpler (answerable) problems.
  3. Balance inside and outside views – search for comparisons (outside) that can be made to help estimate unique events and balance this against your own knowledge/opinions (inside) on the question.
  4. Balance over- and under-reacting to new evidence – as forecasts are updated periodically, new evidence should impact your forecasts. But a balance has to be struck as to how much new evidence should change forecasts.
  5. Search for clashing forces at work – in storage there are many ways to store data and perform faster IO. Search out all the alternatives, especially ones that can critically impact your forecast.
  6. Distinguish all degrees of uncertainty – there are many degrees of knowability, try to be as nuanced as you can and properly aggregate your uncertainty(ies) across aspects of the question to create a better overall forecast.
  7. Balance under/over confidence, prudence/decisiveness – rushing to judgement can be as bad as dawdling too long. You must get better at both calibration (how accurate multiple forecasts are) and resolution (decisiveness in forecasts). For calibration think weather rain forecasts, if rain tomorrow is 80% probably then over time rain probability estimates should be on average correct. Resolution is no guts no glory, if all your estimates are between 0.4 and 0.6 probable, your probably being to conservative to really be effective.
  8. During post mortems, beware of hindsight bias – e.g., of course we were going to have flash in storage because the price was coming down, controllers were becoming more sophisticated, reliability became good enough, etc., represents hindsight bias. What was known before SSDs came to enterprise storage was much less than this.

There are a few more hints than the above.  In the Good Judgement Project, forecasters were put in teams and there’s one guideline that deals with how to be better forecasters on teams. Then, there’s another that says don’t treat these guidelines as gospel. And a third, on trying to balance between over and under compensating for recent errors (which sounds like #4 above).

Again, I would suggest reading the book if you want to learn more.

Storage analysts forecast contest

I think we all want to be better forecasters. At least I think so. So I propose a multi-year long contest, where someone provides a storage question of the week and analyst,s such as myself, provide forecasts. Over time we can score the forecasts by creating a Brier score for each analysts set of forecasts.

I suggest we run the contest for 1 year to see if there’s any improvements in forecasting and decide again next year to see if we want to continue.

Question(s) of the week

But the first step in better forecasting is to have more frequent and better questions to forecast against.

I suggest that the analysts community come up with a question of the week. Then, everyone would get one week from publication to record their forecast. Over time as the forecasts come out we can then score analysts in their forecasting ability.

I would propose we use some sort of hash tag to track new questions, “#storage-QoW” might suffice and would stand for Question of the week for storage.

Not sure if one question a week is sufficient but that seems reasonable.

(#Storage-QoW 2015-001): Will 3D XPoint be GA’d in  enterprise storage systems within 12 months?

3D XPoint NVM was announced last July by Intel-Micron (wrote a post about here). By enterprise storage I mean enterprise and mid-range class, shared storage systems, that are accessed as block storage via Ethernet or Fibre Channel as SCSI device protocols or as file storage using SMB or NFS file access protocols. By 12 months I mean by EoD 12/8/2016. By GA’d, I mean announced as generally available and sellable in any of the major IT regions of the world (USA, Europe, Asia, or Middle East).

I hope to have my prediction in by next Monday with the next QoW as well.

Anyone interested in participating please email me at Ray [at] SilvertonConsulting <dot> com and put QoW somewhere in the title. I will keep actual names anonymous unless told otherwise. Brier scores will be calculated starting after the 12th forecast.

Please email me your forecasts. Initial forecasts need to be in by one week after the QoW goes live.  You can update your forecasts at any time.

Forecasts should be of the form “[YES|NO] Probability [0.00 to 0.99]”.

Better forecasting demands some documentation of your rational for your forecasts. You don’t have to send me your rational but I suggest you document it someplace you can use to refer back to during post mortems.

Let me know if you have any questions and I will try to answer them here

I could use more storage questions…

Comments?

Photo Credits: Renato Guerreiro, Crystalballer

New Global Learning XPrize opens

Posted on by Ray in Crowdsourcing, Distributed computing, Information economy, Mobile computing, Strategic Inflection Points, Visionary leadershp, Visionary organizations

Read a post this week in Gizmag about the new Global Learning XPrize. Past XPrize contests have dealt with suborbital spaceflight, super-efficient automobiles,  oil cleanup, and  lunar landers.

Current open XPrize contests include: Google Lunar Lander, Qualcomm Tricorder medical diagnosis, Nokia Health Sensing/monitoring and Wendy Schmidt Ocean Health Sensing. So what’s left?

World literacy

There are probably a host of issues that the next XPrize could go after but one that might just change the world is to improve children literacy.  According to UNESCO (2nd Global Report on Adult Learning and Education  [GRALE 2]) there are over 250M children of primary school age that will not reach grade 4 levels of education in the world, these children cannot read, write or do basic arithmetic. Given current teaching methods we would need an additional 1.6M teachers to teach all these children. As such, to teach all these children when we include teacher salaries, classroom spaces, supplies, etc. would be highly expensive. There has to be a better, more scaleable way to do this.

Enter the Global Learning XPrize. The intent of this XPrize is to create a tablet application which can teach children how to read, write and do rudimentary arithmetic in 18 months without access to a teacher or other supervised learning.

Where are they in the XPrize process?

The Global Learning XPrize already has raised $15M for the actual XPrize but they are using a crowd funding approach to fund the last $500K which will be used to field test the  Global Learning XPrize candidates. The crowd funding is being done on Indiegogo.

Registration starts now and runs through March 2015, Software development runs through September 2016, at which time five finalists will be selected, each will receive the $1M finalist XPrize to fund a further round of coding. In May of 2017, the five apps will be loaded onto tablets and field testing commences in June 2017 through December 2018. At which time the winner will be selected and will recieve the $10M XPrize.

What other projects have been tried?

I once read an article about the  Hole in the wall computer, where NIIT and their technologists placed an outside hardened, internet connected computer inside a brick wall  in an Indian underprivileged area. The intent was to show that children could learn how to use computers on their own, without adult supervision. Within days children were able to “browse, play games, create documents and paint pictures” on the computer. So minimally invasive education (MIE) can be made to work.

Whats the hardware environment going to look like

There’s no reason that an Android tablet would be any worse and potentially could be much better than a internet connected computer.

Although the tablets will be internet connected it is assumed that the connection will be not always on so the intent is that the apps run standalone as much as possible. Also, I believe that a child will be given a tablet which will be for their exclusive use during the 18 months. The Global Learning XPrize team will insure that there are charging stations where the tablets can be charged once/day but we shouldn’t assume that they can be charged while they are being used.

How are the entries to be judged

The finalists will be judged against EGRA (early grade reading assessment), EGWA (early grade writing assessment), and EGMA (early grad math assessment). The chosen language is to be English and the intent is to use children in countries which have an expressed interest in using English. The Grand winner will be judged to have succeeded if its 7 to 12 year old students can score twice as as well on the EGRA, EGWA and EGMA as a control group. [Not sure what a control group would look like for this nor what they would be doing during the 18 months]. For more information checkout the XPrize guidelines v1 pdf.

The assumption is that there will be about 30 children per village and enough villages will be found to provide a statistically valid test of the five learning apps against a control group.

At the end of all this the winning entry and the other four finalists will have their solutions be open sourced, for the good of the world.

Registration is open now…

Entry applications are $500. Finalists win $1M and the winner will take home $10M.

I am willing to put up the $500 application fee for the Global Learning XPrize. Having never started an open source project, never worked on developing an Android tablet application, or done anything other than some limited professional training this will be entirely new to me – so it should be great fun.  I am thinking of creating a sort of educational video game  (yet another thing I have no knowledge about, :).

We have until March of 2015 to see if we can put a team together to tackle this. I think if I can find four other (great) persons to take this on, we will give it a shot. I hope to enter an application by February of 2015, if we can put together a team by then to tackle this.

Anyone interested in tackling the Global Learning XPrize as an open source project from the gitgo, please comment on this post to let me know.

Photo Credit(s): Kid iPad outside by Alice Keeler

Replacing the Internet?

Posted on by Ray in Cloud services, Cloud storage, Crowdsourcing, Data availability, Data grid, Data security, Distributed computing, Information economy, Internet traffic, Networking, Object storage, Storage, storage economics, Strategic Inflection Points, Strategy, Systems, Visionary leadershp
safe 'n green by Robert S. Donovan (cc) (from flickr)
safe ‘n green by Robert S. Donovan (cc) (from flickr)

Was reading an article the other day from TechCrunch that said Servers need to die to save the Internet. This article talked about a startup called MaidSafe which is attempting to re-architect/re-implement/replace the Internet into a Peer-2-Peer, mesh network and storage service which they call the SAFE (Secure Access for Everyone) network. By doing so, they hope to eliminate the need for network servers and storage.

Sometime in the past I wrote a blog post about Peer-2-Peer cloud storage (see Free P2P Cloud Storage and Computing if  interested). But it seems MaidSafe has taken this to a more extreme level. By the way the acronym MAID used in their name stands for Massive Array of Internet Disks, sound familiar?

Crypto currency eco-system

The article talks about MaidSafe’s SAFE network ultimately replacing the Internet but at the start it seems more to be a way to deploy secure, P2P cloud storage.  One interesting aspect of the MaidSafe system is that you can dedicate a portion of your Internet connected computers’ storage, computing and bandwidth to the network and get paid for it. Assuming you dedicate more resources than you actually use to the network you will be paid safecoins for this service.

For example, users that wish to participate in the SAFE network’s data storage service run a Vault application and indicate how much internal storage to devote to the service. They will be compensated with safecoins when someone retrieves data from their vault.

Safecoins are a new BitCoin like internet currency. Currently one safecoin is worth about $0.02 but there was a time when BitCoins were worth a similar amount. MaidSafe organization states that there will be a limit to the number of safecoins that can ever be produced (4.3Billion) so there’s obviously a point when they will become more valuable if MaidSafe and their SAFE network becomes successful over time. Also, earned safecoins can be used to pay for other MaidSafe network services as they become available.

Application developers can code their safecoin wallet-ids directly into their apps and have the SAFE network automatically pay them for application/service use.  This should make it much easier for App developers to make money off their creations, as they will no longer have to use advertising support, or provide differenct levels of product such as free-simple user/paid-expert use types of support to make money from Apps.  I suppose in a similar fashion this could apply to information providers on the SAFE network. An information warehouse could charge safecoins for document downloads or online access.

All data objects are encrypted, split and randomly distributed across the SAFE network

The SAFE network encrypts and splits any data up and then randomly distributes these data splits uniformly across their network of nodes. The data is also encrypted in transit across the Internet using rUDPs (reliable UDPs) and SAFE doesn’t use standard DNS services. Makes me wonder how SAFE or Internet network nodes know where rUDP packets need to go next without DNS but I’m no networking expert. Apparently by encrypting rUDPs and not using DNS, SAFE network traffic should not be prone to deep packet inspection nor be easy to filter out (except of course if you block all rUDP traffic).  The fact that all SAFE network traffic is encrypted also makes it much harder for intelligence agencies to eavesdrop on any conversations that occur.

The SAFE network depends on a decentralized PKI to authenticate and supply encryption keys. All SAFE network data is either encrypted by clients or cryptographically signed by the clients and as such, can be cryptographically validated at network endpoints.

The each data chunk is replicated on, at a minimum, 4 different SAFE network nodes which provides resilience in case a network node goes down/offline. Each data object could potentially be split up into 100s to 1000s of data chunks. Also each data object has it’s own encryption key, dependent on the data itself which is never stored with the data chunks. Again this provides even better security but the question becomes where does all this metadata (data object encryption key, chunk locations, PKI keys, node IP locations, etc.) get stored, how is it secured, and how is it protected from loss. If they are playing the game right, all this is just another data object which is encrypted, split and randomly distributed but some entity needs to know how to get to the meta-data root element to find it all in case of a network outage.

Supposedly, MaidSafe can detect within 20msec. if a node is no longer available and reconfigure the whole network. This probably means that each SAFE network node and endpoint is responsible for some network transaction/activity every 10-20msec, such as a SAFE network heartbeat to say it is still alive.

It’s unclear to me whether the encryption key(s) used for rUDPs and the encryption key used for the data object are one and the same, functionally related, or completely independent? And how a “decentralized PKI”  and “self authentication” works is beyond me but they published a paper on it, if interested.

For-profit open source business model

MaidSafe code is completely Open Source (available at MaidSafe GitHub) and their APIs are freely available to anyone and require no API key. They also have multiple approved and pending patents which have been provided free to the world for use, which they use in a defensive capacity.

MaidSafe says it will take a 5% cut of all safecoin transactions over the SAFE network. And as the network grows their revenue should grow commensurately. The money will be used to maintain the core network software and  MaidSafe said that their 5% cut will be shared with developers that help develop/fix the core SAFE network code.

They are hoping to have multiple development groups maintaining the code. They currently have some across Europe and in California in the US. But this is just a start.

They are just now coming out of stealth, have recently received $6M USD investment (by auctioning off MaidSafeCoins a progenitor of safecoins) but have been in operation now, architecting/designing/developing the core code now for 8+ years now, which probably qualifies them for the longest running startup on the planet.

Replacing the Internet

MaidSafe believes that the Internet as currently designed is too dependent on server farms to hold pages and other data. By having a single place where network data is held, it’s inherently less secure than by having data spread out, uniformly/randomly across a multiple nodes. Also the fact that most network traffic is in plain text (un-encrypted) means anyone in the network data path can examine and potentially filter out data packets.

I am not sure how the SAFE network can be used to replace the Internet but then I’m no networking expert. For example, from my perspective, SAFE is dependent on current Internet infrastructure to store and forward rUDPs on along its trunk lines and network end-paths. I don’t see how SAFE can replace this current Internet infrastructure especially with nodes only present at the endpoints of the network.

I suppose as applications and other services start to make use of SAFE network core capabilities, maybe the SAFE network can become more like a mesh network and less dependent on the current hub and spoke current Internet we have today.  As a mesh network, node endpoints can store and forward packets themselves to locally accessed neighbors and only go out on Internet hubs/trunk lines when they have to go beyond the local network link.

Moreover, the SAFE can make any Internet infrastructure less vulnerable to filtering and spying. Also, it’s clear that SAFE applications are no longer executing in data center servers somewhere but rather are actually executing on end-point nodes of the SAFE network. This has a number of advantages, namely:

  • SAFE applications are less susceptible to denial of service attacks because they can execute on many nodes.
  • SAFE applications are inherently more resilient because the operate across multiple nodes all the time.
  • SAFE applications support faster execution because the applications could potentially be executing closer to the user and could potentially have many more instances running throughout the SAFE network.

Still all of this doesn’t replace the Internet hub and spoke architecture we have today but it does replace application server farms, CDNs, cloud storage data centers and probably another half dozen Internet infrastructure/services I don’t know anything about.

Yes, I can see how MaidSafe and its SAFE network can change the Internet as we know and love it today and make it much more secure and resilient.

Not sure how having all SAFE data being encrypted will work with search engines and other web-crawlers but maybe if you want the data searchable, you just cryptographically sign it. This could be both a good and a bad thing for the world.

Nonetheless, you have to give the MaidSafe group a lot of kudos/congrats for taking on securing the Internet and making it much more resilient. They have an active blog and forum that discusses the technology and what’s happening to it and I encourage anyone interested more in the technology to visit their website to learn more

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Comments?

Data of the world, lay down your chains

Posted on by Ray in Crowdsourcing, Data availability, Data readability, data services, Information economy
Prison Planet by AZRainman (cc) (from Flickr)
Prison Planet by AZRainman (cc) (from Flickr)

GitHub, that open source free repository of software, is taking on a new role, this time as a repository for municipal data sets. At least that’s what a recent article on the Atlantic.com website (see Catch my Diff: GitHub’s New Feature Means Big Things for Open Data) after GitHub announced new changes in its .GeoJSON support (see Diffable, more customizable maps)

The article talks about the fact that maps in Github (using .GeoJSON data) can be now DIFFed, that is see at a glance what changes have been made to it. In the one example in the article (easier to see in GitHub) you can see how one Chicago congressional district has changed over time.

Unbeknownst to me, GitHub started becoming a repository for geographical data. That is any .GeoJson data file can be now be saved as a repository on GitHub and can be rendered as a map using desktop or web based tools. With the latest changes at GitHub, now one can see changes that are made to a .GeoJSON file as two or more views of a map or properties of map elements.

Of course all the other things one can do with GitHub repositories are also available, such as FORK, PULL, PUSH, etc. All this functionality was developed to support software coding but can apply equally well to .GeoJSON data files. Because .GeoJSON data files look just like source code (really more like .XML, but close enough).

So why maps as source code data?

Municipalities have started to use GitHub to host their Open Data initiatives. For example Digital Chicago has started converting some of their internal datasets into .GeoJSON data files and loading them up on GitHub for anyone to see, fork, modify, etc.

I was easily able to login and fork one of the data sets. But there’s a little matter of pushing your committed changes to the project owner that needs to happen before you can modify the original dataset.

Also I was able to render the .GeoJSON data into a viewable map by just clicking on a commit file (I suppose this is a web service). The ReadME file has instructions for doing this on your desktop outside of a web browser for R, Ruby and Python.

In any case, having the data online, editable and commitable would allow anyone with GitHub account to augment the data to make it better and more comprehensive. Of course with the data now online, any application could make use of it to offer services based on the data.

I guess that’s what Open Data movement is all about, make government, previously proprietary data freely available in a standardized format, and add tools to view and modify it, in the hope that businesses see a way to make use of it in new ways. As such, In  the data should become more visible and more useful to the world and the cities that are supporting it.

If you want to learn more about Project Open Data see the blog post from last year on Whitehouse.gov or the GitHub Project [wiki] pages.

Comments?

Fall SNWUSA 2013

Posted on by Ray in Cloud services, Crowdsourcing, Data grid, File Storage, Object storage, Software Defined Network, Storage, Storage architecture, Strategic Inflection Points, Strategy, System effectiveness, Systems, Visionary leadershp

Here’s my thoughts on SNWUSA which occurred this past week in the Long Beach Convention Center.

First, it was a great location. I saw a number of users I haven’t seen at SNWUSA ever before, some of which I have known for years from other (non-storage) venues.

Second, the exhibit hall was scantly populated. There were no major storage vendors at the show at all. Gold sponsors included NEC, Riverbed, & Sepaton, representing the largest exhibiters presenn. Making up the next (Contributing) tier were Western Digital, Toshiba, Active Archive Alliance, and LTO consortium with a smattering of smaller companies.  Finally, there were another 12 vendors with kiosks around the floor, with the largest there being Veeam Software.

I suspect VMWorld Europe happening the same time in Barcelona might have had something to do with the sparse exhibit floor but the trend has been present for the past few shows.

That being said there were still a few surprises in store, at least for me.  Two of the most interesting ones were:

  • Coho Data who came out of stealth with a scale out, RAIN (Redundant array of independent nodes) based storage cluster, with distributed, mirrored customer data across nodes and software defined networking. They currently support NFS for VMware with a management UI reminiscent of IOS 7 sans touch support. The product comes as a series of nodes with SSDs, disk storage and SDN. The SDN allows Coho Data to relocate front-end (client) connections to where the customer data lies. The distributed, mirrored backend storage provides redundancy in the case of a node/disk failure, at which time the system understands what data is now at risk and rebuilds the now-mirorless data onto other nodes. It reminds me a lot of Bycast/Archivas like architectures, with SDN and NFS support. I suppose the reason they are supporting VMware VMDKs is that the files are fairly large and thus easier to supply.
  • Cloud Physics was not exhibiting but they sponsored a break. As such, they were there talking with analysts and the press about their product. Their product installs as a VMware VM service and propagates VMware management agents to ESX servers which then pipe information back to their app about how your VMware environment is running, how VMs are performing, how your network and storage are performing for the VMs running, etc. This data is then sent to the cloud, where it’s anonymized. In the cloud, customers can use apps (called Cards) to analyze this data in the cloud, which can help them understand problem areas, predict what configuration changes can do for them, show them how VMs are performing, etc. It essentially is logging all this information to the cloud and providing ways to analyze the data to optimize your VMware environment.

Coming in just behind these two was Jeda Networks with their Software Defined Storage Network (SDSN). They use commodity (OpenFlow compatible) 10GbE switches to support a software FCoE storage SAN. Jeda Networks say that over the past two years,  most 10GbE switch hardware have started to support DCB in hardware and with that in place, plus OpenFlow compatibility, they can provide a SDSN on top of them just by emulating a control layer for FCoE switches. Of course one would still need FCoE storage and CNAs but with that in place one could use much cheaper switches to support FCoE.

CloudPhysics has a subscription based pricing model which offers three tiers:

  • Free where you get their Vapp, the management agents and a defined set of Free Card Apps for no cost;
  • Standard level where you get all the above plus a set of Card Apps which provide more VMware managability for $50/ESX server/Month; and
  • Enterprise level where you get all the above plus all the Card Apps presently available for $150/ESX server/Month.

Jeda networks and Coho Data are still developing their pricing and had none they were willing to disclose.

One of the CloudPhysics Card apps could predict how certain VMs would benefit from host based (PCIe or SSD) IO caching. They had a chart which showed working set inflection points for (I think) one VM running an OLTP application.  I have asked for this chart to discuss further in a future post.  But although CloudPhysics has the data to produce such a chart, the application shows three potential break points where say adding 500MB, 2000MB or 10000MB of SSD cache can speed up application performance by 10%, 30% or 50% (numbers here made up for example purposes and not off the chart they showed me).

A few other companies made announcements at the show. For example, Sepaton announced their new VirtuoSO, scale out hybrid reduplication appliance.

That’s about it. I would have to say that SNW needs to rethink their business model, frequency of stows or what they are trying to do at their conferences. However, on the plust side, most of the users I talked with came away with a lot of information and thought the show was worthwhile and I came away with a few surprises.

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Comments?

Cheap phones + big data = better world

Posted on by Ray in Crowdsourcing, Data analytics, Data availability, Data science, Information economy, Strategic Inflection Points, Visionary organizations
Big data visualization, Facebook friend connections, Data science
Facebook friend carrousel by antjeverena (cc) (from flickr)

Read an article today in MIT Technical Review website (Big data from cheap phones) that shows how cheap phones, call detail records (CDRs) and other phone logs can be used to help fight disease and help understand disaster impacts.

Cheap phones generate big data

In one example, researchers took cell phone data from Kenya and used it to plot people movements throughout the country. What they were looking for is people who frequented malaria disease hot spots so that they could try to intervene in the transmission of this disease. Researchers discovered one region (cell tower) that had many people that were frequenting a particular bad location for malaria.  It turned out the region they identified had a large plantation with many migrant workers. These workers moved around a lot.  In order to reduce the transmission of the disease public health authorities could target this region to use more bed nets or try to reduce infestation at source of the disease.  In either case, people mobility was easier to see with cell phone data than actually putting people on the ground and counting where people go or come from.

In another example, researchers took cell phone data from Haiti before and after the earthquake and were able to calculate how many people were in the region hardest hit by the earthquake.  They were also able to identify how many people left the region and where the went to.  As a follow on to this, researchers were able to in real time show how many people had fled the cholera epidemic.

Gaining access to cheap phone data

Most of this call detail record data is limited to specific researchers for very specialized activities requested by the host countries. But recently  Orange released 2.5 billion cell phone call and text data records for five million customers they have in Ivory Coast that occurred during five months time.  They released the data to the public under some specific restrictions in order to see what data scientists could do with it. The papers detailing their activities will be published at a MIT Data for Development conference.

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Big data’s contribution to a better world is just beginning but from what we see here there’s real value in data that already exists, if only the data were made more widely available.

Comments?

Upverter, electronic design-as-a-service

Posted on by Ray in Cloud services, Crowdsourcing, Information economy, Strategic Inflection Points, Strategy, System effectiveness, Systems, Visionary organizations

Read a recent article on TechCrunch about Upverter a cloud based service supporting electronic hardware design and development.  The ultimate intent is to provide a electronic design as a service  (EDaaS) offering that’s almost equivalent to electronic design automation (EDA) tools available on the market today.

EDA tools available

I am no EDA expert but currently, they have some basic electronic design, simulation and build tools available.  These allow a person or an organization to design, simulate and build real electronic circuits, boards etc. They even provided tools for motherboard routing and layout as well as services to have a circuit manufactured.  But this all came with a cloud oriented electronic design versioning system which seemed pretty slick.

The TechCrunch article had a video of a tour of the service (also available on their website).  I was especially impressed with the rollback-undo options on the electronic circuit design pallet.  Seeing an electronic circuit being designed in almost a line by line build was interesting to say the least.

Not sure if we are talking ASICs or FPGA design yet but they certainly have the platform to support these tools if and when they develop it.  However, simulation time and cost might go off the charts for circuits including custom designed ASICs and FPGAs.

Everything seems to execute in the cloud and any EDA specifications reside in the cloud under their control as well. However, they do offer some tools to import EDA information from other tools and provide a JSON file format export of the EDA information you provide.

EDA service pricing

Pricing seemed pretty reasonable $7/month for an individual part timer, $99/month for full time user and both these include 10 CPU hrs of simulation time and can work on public and private projects.  Other pricing options are available for bigger teams and/or more part and full timers on a project.  I didn’t see any information on more simulation time but I am sure these would be available.

And if you are just interested in working on public projects the price is FREE.

Open source electronic design

Now, I am no hardware design expert but having such a cloud based service and essentially free for public projects opens up a whole new dimension in hardware design. Open source electronic hardware wouldn’t be as easy to support/perform as open source software but the advantages seem similar.  Such as, open sourced PCIe card instrumentation, an open sourced X86 CPU, perhaps even an open sourced server.

For instance in data storage alone I could foresee open sourced circuitry to perform NAND wear leveling, data compression and/or protocol handling to name just a few.  Any of these might make it easier for companies and even individuals to create their own, hardware accelerated storage systems.

Unclear what IP licensing requirements would be for open sourced hardware. I am certainly no lawyer but something akin to GPL might be required to help create the ecosystem of open sourced electronic design.

A new renaissance of hardware innovation?

Innovation in hardware design has always been harder mostly because of the cost and time involved.  Now Upverter doesn’t seem to do much about the time involved but it can have a bearing on the cost’s associated with electronic design if they can scale up their service to provide more sophisticated EDA tools.

Nonetheless, the advantages of hardware innovation are many and include speeding up processing by orders of magnitude over what can often be done in software alone. (For more please see our posts on Better storage through hardware, Commodity hardware always loses and Commodity hardware debates heat up again). So anything which can make hardware innovation easier to accomplish is a good thing in my book.

Also having these sorts of tools available in the cloud opens up a whole array of educational opportunities never before available.  EDA tools were never cheap and if schools had access to some of these they were often limited to only a few select students.  So with cloud based service that’s essentially free for open sourced circuit design this should no longer be a problem.

Finally, I firmly believe having more hardware designers is a good thing, having the ability to contribute and collaborate on hardware design for free is a great thing and anything that makes it easier to innovate in electronic hardware design is an important step and deserves our support.

It appears that electronic design is undergoing a radical shift from an enterprise/organizational based endeavor back to something a single person can do from anywhere connected to the internet.  Some would say this is back to the roots of electronic design when this could all be done in a garage, with a soldering iron and some electronic componentry.

Comments?

Photo Credit: 439 – Circuit Board Texture by Patrick Hoesly

Big open data leads to citizen science

Posted on by Ray in Crowdsourcing, Data, Data availability, Data discovery, data logistics, Visionary organizations

Read an article the other day in ScienceLine about the Astronomical Data Explosion.  It appears that as international observatories start to open up their archives and their astronomical data to anyone and anybody, people are starting to do useful science with it.

Hunting for planets

The story talked about a pair of amateur astronomers who were looking through Kepler telescope data which had recently been put online (see PlanetHunters.org) to find anomalies that signal the possibility of a planet.  They saw a diming of a particular star’s brightness and then saw it again 132 days later. At that point they brought it to the attention of real scientists who later discovered that what they found was a 4 star solar system which they labeled Tatooine.

It seems with all the latest astronomical observations coming in from Kepler, the Sloan Digital Sky Survey and Hubble observatories are generating a deluge of data. And although all this data is being subjected to intense scrutiny by professional astronomers, they can’t do everything they want to do with it.

Consequently, in astronomy today we now have come to a new world of abundant data but not enough resources to do all the science that can be done.  This is where the citizen or amateur scientist enters the picture. Using standard web accessible tools they are able to subject the data to many more eyes each looking for whatever interest spurs them on and as such, can often contribute real science from their efforts.

Citizen science platforms

It turns out PlanetHunters.org is one of a number of similar websites put up by Zooniverse to support citizen science in astronomy, biology, nature, climate and humanities. Their latest project is to classify animal found in snapshots taken on the Serengheti (see SnapshotSerengeti.org).

Of course crowdsourced scientific activity like this has been going on for a long time now with Boinc projects like SETI@Home screen savers that sifted through radio signals searching for extra-terestial signals. But that made use of the extra desktop compute cycles people were waisting with screen savers.

 

In contrast, Zooniverse started with the GalaxyZoo project (original retired site here). They put Hubble telescope images online and asked for amateur astronomers to classify the type of galaxies found in the images.

GalaxyZoo had modest aspirations at first but when they put the Hubble images online their servers were overwhelmed with the response and had to be beefed up considerably to deal with the traffic.  Overtime, they were able to get literally millions of galaxy classifications. Now they want more, and the recent incarnation of GalaxyZoo has put the brightest 250K galaxies online and they are asking for even finer, more detailed classifications of them.

Today’s Zooniverse projects are taking advantage of recent large and expanding data repositories plus newer data visualization tools to help employ human analysis to their data.  Automated tools are not yet sophisticated enough to classify images as well as a human can.

One criteria for Zooniverse projects is to have a massive amount of data which needs to be classified.  In this way, science is once again returning to it’s amateur roots but this time guided by professionals.  Together we can do more than what either could do apart.

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I suppose it was only a matter of time before science got inundated with more data than they could process effectively.  Having the ability to put all this data online, parcel it out to concerned citizens and ask them to help understand/classify it has brought a new dawn to citizen science.

Comments?

Photo credits:
Twin Suns on Mos Espa by Stéfan
BONIC running SETI@Home by Keng Susumpow
Galaxy Group Stephan’s Quintet by HubbleColor {Zolt}