First, we had the guy from Harvard try to explain that women aren’t interested in science because there is an intrinsic aptitude for things scientific based on gender. Guess which gender is deemed as more scientific?
Now, we have a new observation brought to us by Wray Herbert (http://www.huffingtonpost.com/wray-herbert/women-science_b_652858.html).
According to Miami University psychological scientist Amanda Dickman, there is a new explanation citing a difference in worthiness or values rather than ability. It seems, according to the new theory, that women reject science, engineering, and math because they view the these fields as too ego and power driven for their tastes.
The unambiguous results for the study found that young women did see science and engineering careers as isolated and individualistic–and what’s more, as obstacles to finding meaning in their lives.
The article goes on to state that it seems to be a perception thing. I would agree that it could very well be the perception thing, but there I think there is a little more to it than that.
A Little Background
My higher education endeavors began with a trip down the road that would merit approval from the study group quoted above. I got an undergraduate degree in Social and Behavioral Sciences and was just a few hours away from a graduate degree when I discovered I was bored to death. Something was missing. There was no challenge.
I tried the MBA path. Nothing doing.
I had taken an intro to computers course as part of my undergraduate course work and a ton of statistics courses but neither appealed. It wasn’t until I ran into my first “micro-computer” (as they were then known), that I realized this little machine was really going to change things. I even got a Heath kit catalog, ordered the H-89 kit, and put it together.
The closest decree to a computer science degree my university offered was a degree in mathematical sciences. I signed up for that.
Believe me, it wasn’t easy. I had already gotten the required courses out of the way, so for three semesters every class I had was either math or computer science. But it was interesting and definitely challenging.
Group Members
The isolated and individualistic scientist, engineer, computer scientist as cited by the study does not exist in the real world.
My first post graduation gig was at the Health Services Division of a major aerospace company as a compiler developer. I was part of the Systems Enhancements and Extensions Group. From there, I transferred to the aircraft company in that same corporation. I was part of the Flight Test Research and Development Group. I went to another aircraft company and the Instrumentation Group. And so on. You were always a member of a group. A group that together designed, developed, and produced things – computer software, digital data acquisition systems, aircraft manufacturing scheduling systems, etc.
When I moved over to biotechnology, it was the same – you were a member of a group. A lab group, a bioinformatics group developing LIMS systems, sequence analysis and imaging recognition software, and so on.
However, I did find that scientists more that engineers were more power/ego driven. I think this is because of funding issues. Although both areas receive the majority of their funds from the government, the basis of the awards is different.
The individual scientist, as P.I., applies for the grant, writes the proposal and receives the funding – almost a personal assessment of that scientist’s capabilities. Furthermore, I feel that the letters - “PhD”, carries a lot of baggage.
For most engineers, the company applies for the grant, writes the proposal (after the engineers have okayed the design), and receives the funding. The engineer is associated with the program for which that proposal was submitted. The engineer isn’t as personally involved.
What I’ve Encountered
In the military industrial complex I encountered bored ex-military who used weekly status reports to declare war on some other part of the division . These attacks were mostly diversions and never amounted to much. These could be construed as power plays, but I list them as “play” period.
Believe me, there were some good ones – stopping just short of an exchange of blows. It’s also amazing how far echoes carry in an aircraft hanger.
The following examples are situations I encountered along the way. They are mostly examples of misdirected intentions, but a few border on outright criminality.
There were approximately 8 databases that all held the same information but for 8 different divisions. The electronics parts – transducers, potentiometers, strain gauges, resistors etc, in each of the databases were exactly the same. However, the nomenclature varied by division. We tried to standardize on one database system with one naming standard, but ran straight into a brick wall. Not one division was willing to cede to another. It was only after word came down from on high that additional funding would not be forthcoming, that everybody finally sat down to talk.
Insane Budgeting Exercises
One division needed to get a new system but was offered an old barely breathing system with exorbitant maintenance costs. The division was instructed to budget for and use the old system for the current fiscal year. For the he next budget cycle, the department was to state that a new system (the one originally requested) would save X amount of dollars over last year’s budget. The new system was then be given the green light.
A director was undercutting his yearly budget to emphasize cost savings. Consequently, his budget was always cut to that amount for the next year. It was pointed out that he should over run this year’s budget by the amount he wanted for next year. Then he would (and did) get the additional funding.
A Simple Name Change can Work Wonders
it was ascertained that for less that the amount the department was paying IT for storage of design data, a new system, software, and personnel could be purchased and hired. Department was notified that requesting a “computer system” would not meet with budgeting approval Only after the system was termed a “data multiplexer” to be administered by “data design personnel” was department able to proceed with system purchase.
One Size Does Not Fit All
IT sends down list of “acceptable” software. So-called software was specifically IT oriented and would not work in an engineering environment. Division engineers take up collection and purchase needed software themselves.
Almost Criminal
Vast amounts of money, time, manpower were spent developing a manufacturing scheduling system for aircraft manufacture. System rated manufacturing personnel in terms of ability. System was deemed a major success – avoiding bottlenecks, completion times, etc. System was never deployed due to union demands that manufacturing personnel could not be rated in terms of ability.
Decode system purchased for data acquisition decode and analysis ($150K) was purchased without installed hard drive for data storage ($15K). It was determined system could use in-house data farm to store data. Decode system required confirmation that contiguous data storage space was available to go ahead and store data.
Transfer mechanism did not provide this info, so decode system would not store data on data farm. Contractor told department officials that the system software on the decode system and in-house data farm were incompatible. Contractor sold department customized software for $750K to replace decode system.
A Meaningful Life
I’ve never considered my career in engineering and biotechnology as isolated and individualistic. Sure, you have individual work, but it is as part of a team.
As far as letting the ego and power driven become obstacles, I have to admit that my behavioral sciences background provided one of the most important career tools I have yet to encounter. My “Advanced Abnormal Psychology” course taught me how to observe and analyze people.
To find meaning in one’s life entails one heck of a lot more than a career. Perhaps by observing and analyzing one’s misconceptions about one area will enhance our conceptions of life in general.
Cloud computing is the current IT rage, said to cure all information management skills.
Cloud computing is just a new name for timeshare, a system in which various entities shared a centralized computing facility. A giant piece or two of big iron and floors of tape decks provided information processing and storage capabilities for a price.
The user was connected to the mainframe by a dumb terminal and later on by PC’s. The advantage (said the sales jargon), was that the user didn’t need to buy any additional hardware, worry about software upgrades or data backup and recovery. They would only pay for the time and space their processes required. Resources would be pooled and connected by a high speed network and could be accessed as demanded. The user wouldn’t really know what computing resources were in use, they just got results. Everything depended on the network communications between the use and centralized computing source.
What is New
Cloud computing is more powerful today because the communications network is the Internet. Some Cloud platforms also offer Web access to the tools – programming language, database, web utilities needed to create the cloud application.
The most important aspect I believer the Cloud offers is instant elasticity. A process can be upgraded almost instantaneously to use more nodes and obtain more computing power.
There are quite a few blog entries out there concerning the “elastic” cloud. For thoughts on “spin up” and “spin down” elasticity see http://timothyfitz.wordpress.com/2009/02/14/cloud-elasticity/. For thoughts on “how elasticity could make you go broke, or On-demand IT overspending” see http://blogs.gartner.com/daryl_plummer/2009/03/11/cloud-elasticity-could-make-you-go-broke/.
And finally, an article that spawned the “elasticity is a myth” connotation or “over-subscriptionand over-capacity are two different things, see – http://www.rationalsurvivability.com/blog/?p=1672&cpage=1#comment-35881.
A good article that covers elasticity, hypervisors, and cloud security in general is located at http://queue.acm.org/detail.cfm?id=1794516. The queue.acm.org site is maintained by the Association for Computing Machinery. There are lots of articles on all sorts of computing topics including, “Why Cloud Computing Will Never Be Free” (http://queue.acm.org/detail.cfm?id=1772130).
The Clouds
The most notable Clouds are Amazon’s Elastic Cloud, Google’s App Engine, and Microsoft’s Azure.
The three Cloud delivery models include:
-
-
Software as a service (SaaS), applications running on a cloud are accessed via a web browser
-
Platform as a service (PaaS), cloud-developed user applications such as databases
-
Infrastructure as a service (IaaS), provides computing resources to users on an as-needed basis
Pros and Cons
There are pros and cons for Cloud Computing. Microsoft’s Bill Ballmer is a proponent of Cloud computing.
In a recent email (http://blog.seattlepi.com/microsoft/archives/196793.asp) to Microsoft’s employees, Ballmer make the following case for Cloud Computing. He advises his employees to watch a video (http://www.microsoft.com/presspass/presskits/cloud/videogallery.aspx) in which he makes the following points.
In my speech, I outlined the five dimensions that define the way people use and realize value in the cloud:
-
The cloud creates opportunities and responsibilities
-
The cloud learns and helps you learn, decide and take action
-
The cloud enhances your social and professional interactions
-
The cloud wants smarter devices
- The cloud drives server advances that drive the cloud
Some very notable people are anti-cloud.
Richard Stallman, GNU software founder, said in recent interview for the London Guardian (http://www.guardian.co.uk/technology/2008/sep/29/cloud.computing.richard.stallman) that Cloud computing is a trap.
The Web-based programs like Google’s Gmail will force people to buy into locked, proprietary systems that will cost more and more over time, according to the free software campaigner.
‘It’s stupidity. It’s worse than stupidity: it’s a marketing hype campaign,’ he told The Guardian. ‘Somebody is saying this is inevitable — and whenever you hear somebody saying that, it’s very likely to be a set of businesses campaigning to make it true.’”
Aside from all that, what should a potential user be wary of in the Cloud? I’ll try to answer that below.
Security in the Cloud
Security in the cloud is a major concern. Hackers are salivating because everything – applications, data, are all in the same place.
How do you know the node your process is accessing is real or virtual? The Hypervisor (in Linux, a special version of the kernel) owns the hardware and spawns virtual nodes. If the Hypervisor is hacked, the hacker owns all the nodes created by it. http://www.linux-kvm. org has further explanations and discussions of virtual node creators/creations.
Data separation is a big concern. Could your data become contaminated by data in other environments in the cloud.? What access restrictions are in place to protect sensitive data?
Can a user in another cloud environment inadvertently or intentionally get access to your data?
Data interoperability is another question mark. A company cannot transfer data from a public cloud provider, such as Amazon, Microsoft, or Google, put it in a private IaasP that a private cloud provider develops for a company, and then copy that data from its private cloud to another cloud provider, public or private. This is difficult because there are no standards for operating in this hybrid environment.
Data Ownership
Who is the custodian and who controls data if your company uses cloud providers, public and private?
Ownership concerns have no been resolved by the cloud computing industry. At the same time, the industry has no idea when a standard will emerge to handle information exchanges.
W3C – http://www.w3.org/, is sponsoring workshops and publishing proposals concerning standards for the Cloud. You can subscribe to their weekly newsletter and stay up on all sorts of web-based technologies.
Also, the Distributed Management Task Force Inc.(http://www.dmtf.org/home) is a consortium ofof IT companies focusing on, “Developing management standards & promoting
interoperability for enterprise & Internet environments”.
The DMTF Open Cloud Standards Incubator was launched to address management interoperability for Cloud Systems (http://www.dmtf.org/about/cloud-incubator). The DMTF leadership board currently includes AMD, CA Technologies, Cisco, Citrix Systems, EMC, Fujitsu, HP, Hitachi, IBM, Intel, Microsoft, Novell, Rack Space, RedHat, Savvis, Sun Guard, Sun Microsystems, and VMWare.
Working with the Cloud
Working with the Cloud can be intimidating. One suggestion is to build a private cloud in-house before moving on to the public cloud.
However, even that has its difficulties. Not to worry, there are several tools available to ease the transition.
There is a Cloud programming language – Bloom, developed at UC Berkeley by Dr. Joseph Hellerstein. HPC In The Cloud has published an interview with Dr. Hellerstein at http://www.hpcinthecloud.com/features/Clouds-New-Language-Set-to-Bloom-92130384.html?viewAll=y
Bloom is based on Hadoop (http://hadoop.apache.org) which is open source software for High Performace Computing (HPC) from Apache..
For ease of inter connectivity, Apache has released Apache libcloud, a standard client library written in python for many popular cloud providers – http://incubator.apache.org/libcloud/index.html. But libcloud doesn’t cover data standards, just connectivity.
MIT StarCluster– http://web.mit.edu/stardev/cluster , is an open source utility for creating and managing general purpose computing clusters hosted on Amazon’s Elastic Compute Cloud (EC2). StarCluster minimizes the administrative overhead associated with obtaining, configuring, and managing a traditional computing cluster used in research labs or for general distributed computing applications.
All that’s needed to get started with your own personal computing cluster on EC2 is an Amazon AWS account and StarCluster.
HPC presents use cases as a means to understanding cloud computing. http://www.hpcinthecloud.com/features/25-Sources-for-In-Depth-HPC-Cloud-Use-Cases-93886489.html.
BCM Bioinformatics has a new methodology article – Cloud Computing for Comparative Genomics that includes a cost analysis of using the cloud. Download the .pdf at http://www.biomedcentral.com/1471-2105/11/259/abstract.
I hope this will get you started. Once again, a big thanks to Bill for his assistance.