Korupsi adalah:
1. perbuatan melawan hukum
2. dengan maksud memperkaya diri sendiri atau orang lain
3. 'dapat' merugikan keuangan atau perekonomian negara

'Secara melawan hukum' artinya suatu perbuatan dapat dipidana, jika:
1. ada aturannya dalam Undang-undang (hukum formil), atau
2. tidak sesuai dengan rasa keadilan atau norma kehidupan masyarakat (hukum materiil).

Kata 'dapat' merugikan keuangan atau perekonomian negara artinya:
tindak pidana korupsi dianggap ada tidak hanya ketika kerugian negara telah terjadi, tapi juga ketika unsur-unsur perbuatan korupsi telah terpenuhi.

O ya, 'jo' dalam judul tulisan ini adalah istilah hukum yang berarti 'sebagaimana telah diubah oleh'.

The most extensive government report to date on whether terrorists can be identified through data mining has yielded an important conclusion: It doesn't really work.

A National Research Council report, years in the making and scheduled to be released Tuesday, concludes that automated identification of terrorists through data mining or any other mechanism "is neither feasible as an objective nor desirable as a goal of technology development efforts." Inevitable false positives will result in "ordinary, law-abiding citizens and businesses" being incorrectly flagged as suspects.

The whopping 352-page report, called "Protecting Individual Privacy in the Struggle Against Terrorists," amounts to at least a partial repudiation of the Defense Department's controversial data-mining program called Total Information Awareness, which was limited by Congress in 2003.

* U.S. government agencies should be required to follow a systematic process to evaluate the effectiveness, lawfulness, and consistency with U.S. values of every information-based program, whether classified or unclassified, for detecting and countering terrorists before it can be deployed, and periodically thereafter.

* Periodically after a program has been operationally deployed, and in particular before a program enters a new phase in its life cycle, policy makers should (carefully review) the program before allowing it to continue operations or to proceed to the next phase.

* To protect the privacy of innocent people, the research and development of any information-based counterterrorism program should be conducted with synthetic population data... At all stages of a phased deployment, data about individuals should be rigorously subjected to the full safeguards of the framework.

* Any information-based counterterrorism program of the U.S. government should be subjected to robust, independent oversight of the operations of that program, a part of which would entail a practice of using the same data mining technologies to "mine the miners and track the trackers."

* Counterterrorism programs should provide meaningful redress to any individuals inappropriately harmed by their operation.

* The U.S. government should periodically review the nation's laws, policies, and procedures that protect individuals' private information for relevance and effectiveness in light of changing technologies and circumstances. In particular, Congress should re-examine existing law to consider how privacy should be protected in the context of information-based programs (e.g., data mining) for counterterrorism.  >>>>>

Dan Ariely is a professor of behavioral economics at Duke University and the author of Predictably Irrational: The Hidden Forces That Shape Our Decisions. I recently talked with him about some hidden forces shaping the current financial crisis.

Mac Greer: You have a lot of Americans seeing this as a Wall Street crisis and not so much as a "Main Street" crisis. What do you think it will take for most Americans to reach some sort of a consensus that this crisis really requires immediate action?

Dan Ariely: Well, one thing is we have been telling a lot of people for a long time that whatever they have in the stock market is about long-term strategy and not any short-term things. So the current change in speak, in some sense, doesn't seem to be very effective. We have been telling people for 20 years the money you have in the stock market is about retirement, it is not about anything urgent. Don't look at it. It is all about long-term strategy. It is very hard to convince people that all of a sudden that it is short term. That is one thing.

The second thing is that nothing has changed much in the short term living of people. In some sense, this is smaller than the effect of the increasing gas prices.

Greer: Yeah.

Ariely: What is happening? Basically the thing is we are creatures of habit, if you think about it. The best predictor of what we will do tomorrow is what we did today. That is it. Habits are good and bad. They are good because they help us save energy. We don't have to think about it. We don't have to contemplate every cup of coffee if it is worth it or not. As a consequence, we get into habits.

Read the full post from Motley Fool.

Tone at the Top
1. Kebijakan dan dukungan dari CEO, direksi dan senior management.
2. Secara konsisten mengkomunikasikan kebijakan dan dukungan atas program anti korupsi.
3. Mengintegrasikan program anti korupsi ke dalam struktur organisasi dan proses pengambilan keputusan.
4. Membuat 'whistleblower hotlines, employee help lines dan topical guidance'. Gunanya untuk menerima laporan tentang korupsi dan memberikan panduan atas dilema yang dihadapi karyawan apakah perbuatannya termasuk korupsi atau tidak.
5. Laporan secara berkala tentang program anti korupsi kepada CEO dan direksi.

Risk Assessment
1. Menyusun tim dari berbagai bidang (keuangan, internal audit, hukum, operasional) dalam menyusun evaluasi resiko atau 'risk assessment'. Tujuannya supaya evaluasinya lebih efektif, komprehensif, dan 'down to earth'/implementatif.
2. Mengidentifikasi bagaimana saja pola korupsi yang mungkin terjadi dalam suatu proses bisnis.
3. Mengidentifikasi kecenderungan dan dampak dari pola-pola korupsi yang mungkin terjadi.
4. Melakukan evaluasi kemungkinan adanya insentif, tekanan, peluang dan perilaku yang mendorong terjadinya korupsi (lihat tulisan tentang 'the fraud triangles').
5. Dari hasil evaluasi resiko korupsi, kemudian disusun apa saja resiko korupsi yang perlu diprioritaskan penanganannya.

Programme Design and Control Activities
1. Membuat desain program dan kontrol untuk meminimalisir resiko korupsi dari hasil 'risk assessment'.
2. Beberapa isu yang perlu dipertimbangkan : facilitation payments, gifts, hospitality, entertainment, political and charitable contributions, acquisition due diligence, joint ventures, record keeping requirements, investigation and sanction procedures.
3. Menyesuaikan kontrol yang akan dibuat dengan situasi dan kondisi lokal sebuah organisasi.

Monitoring
1. Merancang sistem pengawasan dan audit atas resiko-resiko korupsi dan indikator terjadinya korupsi 'red flags'.
2. Mengevaluasi program anti korupsi secara berkala melalui internal audit.
3. Melakukan survey apakah seluruh karyawan memahami kebijakan anti korupsi yang ada di perusahaan.
4. Melakukan penyesuaian dalam desain program anti korupsi sesuai dengan hasil pengawasan/evaluasi program anti korupsi.

Response and remediation
1. Menyusun proses untuk mengajukan, melacak, menyelesaikan, dan mendokumentasikan 'allegation' atau dugaan korupsi.
2. Mengidentifikasi dan memperbaiki kelemahan kontrol yang menyebabkan korupsi dapat terjadi.
3. Mengenakan sanksi atas setiap tindakan korupsi secara konsisten.

Diambil dari sini.

Today NASA's space probe MESSENGER made a flyby of the closest planet to the Sun, Mercury.  The probe, whose name is both an acronym for Mercury Surface, Space Environment, Geochemistry and Ranging and a reference to Mercury's role as the messenger of the Roman gods, took photographs of previously unseen areas of the planet's surface and numerous other readings that scientists are now eagerly studying.  This is the second of three flybys of Mercury, each of them serves to slow down the spacecraft to the point that it can enter orbit in 2011; it also got such gravity assists from Venus and from the Earth itself.  Somewhat counter intuitively to a layman, going to Mercury is a lot harder than going to Mars, due to the very large change in velocity needed to enter orbit (or land on the planet, which no spacecraft has ever done and which is not part of MESSENGER's mission).  For more information on the mission, including many more photos, check out their official site.

The Economist has an excellent series of articles covering all aspects of the American presidential election. They also have a non-scientific online poll of their readers to see who would win the election if the electoral college were global and each country allocated its electors on a winner-take-all basis. Currently, Barack Obama is ahead 8375--15. McCain is ahead only in Georgia (the country, not the state), Macedonia, and Andorra. He is probably glad that this is just a poll of Economist.com visitors and not a real poll of public opinion in those countries, but, given that he'd probably still lose a worldwide popularity contest, he is probably very glad that this has no constitutional standing.

Speaking of the Economist, they have a thought-provoking article on "Data mining and the state."  It discusses how all the information that the government collects about us and processes can be used both to increase security and safety and to decrease our privacy and liberties.  They discuss the future of such data mining and don't pretend to offer clear answers as to when and how such technology should be used.

And speaking of the presidential race, linguists have analyzed the candidates' remarks at the vice presidential debate (which I blogged about at some length here). They found that Palin spoke at the level of a 9.5th grader and Biden at that of a 7.8th grader. Palin, who spoke 5235 words, used the passive voice in 8% of her sentences; Biden spoke 5492 words and used the passive voice only 5% of the time. They both averaged 4.4 letters per word and were statistically tied on the length of their paragraphs; Biden's averaged 2.7 sentences and Palin's each had about 2.6 sentences. In his 1858 debates with Stephen Douglas, Abraham Lincoln spoke at an 11th grade level, they report---quite interesting, when you consider how much less education people had back then---though the level on which a person speaks doesn't necessarily make what they say any better or clearer.

In wackier news, Virgin Galactic, Richard Branson's company that will take paying customers into space, has rejected an offer of $1 million to use their spacecraft for filming two people having sex in space. "That was money we had to refuse, I'm afraid," said company president Will Whitehorn (which, now that I've written it, sounds kind of like a male porn star's name). If not for the fact that the company making the offer was unidentified, I would say that this was simply a publicity stunt. Virgin Galactic will probably begin flights in 2009 or 2010 and their spacecraft will carry six passengers in addition to two pilots. Tickets will cost $200,000. Even assuming that the $1 million was in addition to the $1.2 million that Virgin Galactic would pull in on a full flight it wouldn't be worth the likely bad publicity that they would get. Besides, I'm sure a porn company could make much more than $1 million if they were the first to release a porn film of people having sex in zero gravity. Wait... maybe this is a publicity stunt, for Virgin Galactic. If so, it's worked: I'm blogging about it.

The Russian Supreme Court has declared that Tsar Nicholas II and his family were killed illegally and are entitled to rehabilitation by the state. This involves formally exonerating them and declaring them victims of communist repression; over four million Russians have been rehabilitated since the collapse of the Soviet Union; The Tsar's descendants have been trying for years to have him exonerated and were surprised at the ruling. Hopefully this will help Russia's process of coming to terms with its past. However, I somehow don't think that knowing he would be declared a victim of communist repression 90 years later would have been much comfort to Nicholas as he and his family were gunned down and bayoneted.

A Negative Reinforcer is a stimulus or stimulus set that when removed or terminated increases the probability of that same response in the future.

Richard Fuld claims that ‘we’ made him and the others like him that have tetra dollar salaries and Mega stock and bonuses with parachutes the size of which could fund small nations… Well, he may be right. The contingencies that came together were those things that favored him doing what he did.

We did it or at least reinforced it when it happened. We got them there and we gave them the keys to the kingdom and told them all that we wanted order and profit – if not in that order, we still wanted it. Those that could claim [reliably] to be able to bring it were vetted, signed and installed.

Ugly isn’t it. Guess what…??? Fuld and those like him were the instruments of the body that didn’t want to face the clients, other boards, other nations, regulators and the zealots of legislature on the right, down the middle and the left. Fuld said he’d do it if they, the boards of directors, paid him. They did and he did.

Competition says what the compensation will be. In effect he responded. “You want more, pay me more. You want your assets and reserves and exchanges managed? Get a manager! I bring it to new levels by risking my reputation for the good of the investors and clients. Anything short of that you can get someone from GE to sit at the desk…”

That is what the board wanted to hear…

Now he is doing his job to escape aversive stimuli [career ending sanctions, indictments, loss of pensions, bonuses, and parachutes] which is reinforcing to him and his companies... it is as reinforcing to him as it is to you and I only his scale of success makes it seem more gluttonous. Perhaps you nick the IRS a bit, use the corporate cards for discretionary spending, turn in to corporate gas mileage for the trip to see sick Aunt Gert? Same difference…

We hail those who beat the system [– ironically, we’re the system]. Of course he is going to explain the run around that favors his position, just as we explain our positions favorably when it of value to us to do so…

Reinforcement is just one behavioral property that helps explain what is going on. It even explains the behavior of those tinkering to prevent it from happening again as they figure out how to restructure the economy to get our hats out of our butts.

Don’t think that it is possible to use negative reinforcement this way? Whattabet?

Those that consider this or that to be a result of single causes should bite your tongue and go take a “time out” while you consider how contingencies work; antecedents events, current state, shaped past consequences for similar behavior…

Consider this mornings Google News events from today.

FIND THE ARTICLE THAT IS NOT CONTROLLED BY CONSEQUENCES

10/6/08 Auto-generated 10 minutes ago

German Stocks Fall to Lowest Since 2006; Hypo Real Estate Drops
Bloomberg - 2 hours ago
By Michael Patterson Oct. 6 (Bloomberg) -- German stocks fell the most in eight months, sending the DAX Index to the lowest since July 2006, as the deepening credit crunch forced the country's financial industry to double a credit line for Hypo Real ...

Barack Obama accuses Republicans of distracting voters from the ...
Los Angeles Times - 2 hours ago
‘TURN THE PAGE’: Obama in Asheville. His poll ratings have risen recently, even in red states such as North Carolina. John McCain wants to 'distract you with smears rather than talk to you about substance,' the Democrat says in Asheville, NC, ...

Northern California bus crash leaves 10 dead
The Associated Press - 48 minutes ago
WILLIAMS, Calif. (AP) - A casino-bound charter bus flipped over about 10 miles from its destination, ejecting passengers and crushing others as it rolled into a ditch.

UPDATE 1-RESEARCH ALERT-FBR raises Wells Fargo price target
Reuters - 46 minutes ago
Oct 6 (Reuters) - Friedman Billings Ramsey raised its price target on the stock of Wells Fargo & Co (WFC.N: Quote, Profile, Research, Stock Buzz), the fifth-largest US bank, by $5 to $25, saying the proposed merger with Wachovia Corp (WB.

ImClone Announces Merger Agreement with Eli Lilly at $70 Per Share
MarketWatch - 48 minutes ago
, , ) , pursuant to which Lilly has agreed to commence a tender offer for no less than a majority of the issued and outstanding shares of ImClone common stock at a net price per share of $70 in cash.

European countries ramp up deposit protection
Washington Post - 39 minutes ago
By MATT MOORE AP STOCKHOLM, Sweden -- Nordic countries Denmark and Sweden moved Monday to bolster protection of bank accounts as stock exchanges across Europe opened lower and central banks pumped more money to cash-starved banks.

Sony Expands E-book Reader Range
PC World - 9 hours ago
Sony is introducing a second electronic book reader to its range in the US that comes with upgraded hardware and will go on sale in November.

IBM Expands Cloud Computing Offerings
CRN - 1 hour ago
By Rick Whiting, ChannelWeb IBM expanded its cloud computing efforts Monday, debuting new on-demand services for ISVs and customers the company said would make it easier for businesses to adopt cloud computing practices for improving collaboration, ...

Facebook co-founder Moskovitz leaves to start group collaboration ...
VentureBeat - 5 hours ago
Facebook co-foudner Dustin Moskovitz (left) and colleague Justin Rosenstein (right) said this weekend they are leaving Facebook to start their own company.

McCain, Obama campaigns trade barbs
The Associated Press - 38 minutes ago
WASHINGTON (AP) - Officials with the presidential campaigns of John McCain and Barack Obama are trading fresh accusations of mudslinging a month before voters choose George Bush's successor.

Under Financial Restraints, McCain Drops Michigan
ABC News - 1 hour ago
By RUSSELL GOLDMAN The electoral map shrank for John McCain Thursday as he abandoned his campaign in Michigan, raising the stakes in other battleground states such as Ohio.

‘SNL’ Keeps It Political
New York Times - 7 hours ago
Once again, “Saturday Night Live” led off the weekend’s show with Tina Fey, above, the Emmy Award-winning creator of “30 Rock,” as the Republican vice-presidential candidate Sarah Palin, governor of Alaska.

'Beverly Hills Chihuahua' tops weekend box office
Los Angeles Times - 4 hours ago
A nation of Chihuahua dogs living in the Lost City of Techichi. in the movie "Beverly Hills Chihuahua." The Disney film does better than expected, grossing $29 million and knocking 'Eagle Eye' into second place.

OJ Simpson jury: Tapes did football legend in
New York Daily News - 5 hours ago
BY NANCY DILLON Jurors, including Dora Pettit (with mike), say they set aside personal feelings and based guilty OJ Simpson conviction on facts.

Yes, it is sort of a trick question but it explains all you are seeing in Washington, DC, Wall Street and Main Street...

2. Implementasi
Melakukan sosialisasi kebijakan anti korupsi, pelatihan anti korupsi, dan evaluasi proses bisnis untuk menghindari korupsi.

3. Sanksi
Harus ada sosialisasi kepada seluruh karyawan mengenai sanksi atas korupsi. Sanksi itu dapat berupa pengurangan kompensasi, tidak naik jabatan, atau bahkan pemecatan dan/atau proses hukum.

4. Help lines
Membuat sambungan telepon anonim dimana karyawan dapat mendapatkan saran atas situasi2 yang berpotensi menimbulkan dilema etik (misalnya apakah suatu hadiah yang diterima dari supplier termasuk korupsi atau tidak, dll.)

5. Monitoring
Melakukan evaluasi program anti korupsi secara berkala dan mengambil langkah perbaikan secara terus menerus.

Oleh Jermyn Brooks, diambil dari sini.

Sebelumnya sudah ditulis dikit di sini. Judul aslinya 'Managing the Business Risk of Fraud : A Practical Guide'. Paper ini disponsori oleh AICPA, IIA, dan ACFE, 3 asosiasi profesi yang leading dalam bidang Accounting, Internal Auditing, dan Fraud.

Dalam definisi paper ini, fraud adalah suatu tindakan yang disengaja (untuk berbuat atau tidak berbuat) bertujuan untuk menipu orang lain. Fraud menyebabkan kerugian bagi orang lain dan pelakunya mendapatkan keuntungan.

Akibat fraud atau korupsi:
1. Bangkrutnya perusahaan
2. Kerugian investasi
3. Biaya penyelesaian hukum
4. Pelakunya dimasukkan tahanan
5. Turunnya kepercayaan terutama di pasar saham
6. Hancurnya brand (merek) perusahaan

Beberapa regulasi atau peraturan terkait dengan fraud misalnya:
1. U.S. Foreign Corrupt Practices Act atau FCPA (1997)
2. Oganisation for Economic Co-operation and Development Anti-Bribery Convention (1997)
3. The U.S. Sarbanes-Oxley Act (2002)
4. The U.S. Federal Sentencing Guidelines (2005)

Banyaknya skandal korporasi (corporate scandals) membuat publik dan stakeholders menyuarakan tidak adanya toleransi terhadap fraud (no fraud tolerance).

Menurut prinsip tata kelola yang baik (Good Corporate Governance), jajaran direksi (board of directors) bertanggung jawab untuk menjalankan organisasinya dengan penuh tanggung jawab dan etika.

The Committe of Sponsoring Organizations of the Treadway's Commission (COSO's) di tahun 1999 menganalisa kasus fraud dalam laporan keuangan yang diinvestigasi oleh U.S. Securities and Exchange Commission (SEC). COSO's menemukan bahwa:

Direksi mempunyai peranan penting dalam manajemen resiko fraud karena mayoritas fraud ternyata dilakukan oleh senior management (seperti CEO, CFO, atau yang selevel) yang berkolusi dengan pegawai lainnya.

Menurut Oversights Systems Report on Corporate Fraud (2007), alasan utama yang menyebabkan terjadinya fraud adalah:
1. Adanya tekanan untuk memenuhi kebutuhan (81%)
2. Untuk mendapatkan keuntungan (72%)
3. Tidak menganggap apa yang dilakukannya adalah termasuk fraud (40%)

Beberapa prinsip utama dalam manajemen resiko fraud yaitu:
1. Perusahaan harus memiliki manajemen resiko fraud (fraud risk management).
2. Perusahaan harus mengevaluasi resiko fraud secara periodik untuk mengidentifikasi apa saja potensi fraud dan apa yang harus dilakukan untuk mengantisipasinya.
3. Perusahaan menerapkan teknik pencegahan fraud atas potensi resiko fraud no. (2) di atas.
4. Menerapkan teknik deteksi fraud untuk mengidentifikasi terjadinya fraud sejak dini.
5. Membuat sistem pelaporan fraud dan melakukan tindak lanjut/investigasi atas fraud yang terjadi.

(Cliquer ici pour accéder au site et télécharger le logiciel)

Le matériel pédagogique est disponible dans l'espace du cours sur la plate-forme eValoris (accès réservé aux étudiants inscrits).

During this tumultuous 2008 election year here in the States one hears the cry, "Drill, baby, drill!" with increasing frequency. And while this cry is about drilling for oil, there is another type of drilling that is changing everything from how elections are run to how soap is marketed. Let's call it digital drilling.

In the article entitled, "It Worked For Bush", the story is told of how traditional campaigning was turned upside down by what might be called database marketing...but that term seems inadequately quaint within this context. It's more than database marketing, it is more accurately digital drilling because it drills down from a huge data cloud right to your doorstep.

"The pollsters also looked in the wrong places. On election day, every exit poll showed a clear Kerry lead. Yet the polls were wrong, because they were wrong in the weightings they gave to different socioeconomic groups and in the assumptions they made about who would turn out to vote. The Bush team had, in effect, destroyed all the methodology on which polling and electoral analysis had been based for the past 50 years."

Let's take a look at how this was done,
STAGE ONE:
The ability to digitally store and archive massive amounts of raw data.
STAGE TWO:
The growth in the quantity and quality of multi-sourced consumer information.
STAGE THREE:
The ability to link multiple data islands.
STAGE FOUR:
The analytical power to search and discover new, meaningful patterns and relationships of strategic and tactical value.

This begs the question who did this and how did they do it? TargetPoint Consulting was the company that did this work for the Bush campaign and they describe how, what they call MicroTargeting, completely changes the game:

Why Now?
"In a word: technology. Campaigns have always collected data on their voters, and there have always been mounds of census data, polling crosstabs and voter registration files. Unfortunately, that data was in most cases wholly insufficient to get the job done, or too large and complex for anything more than rough approximations, oversimplified target lists, and statistically insignificant intuition. Technological developments have brought desperately needed depth and clarity to our formerly flat and hazy perception of individual voters.

By using hundreds of data points, comprised of voter information, life cycle information, life style information, financial data, consumer behavior, geographic data, and political attitudes and preferences, MicroTargeting can be used to segment each of your voters into one of a number of mutually exclusive groups, each defined by a unique combination of a host of data points."

Irrespective of your political inclinations, the issue of digital drilling is an interesting one. And if you are a marketer, the interest is more than a passing one because in a post-broadcast world there is a difference between shouting to a group and speaking intimately with an individual. And motivating them to action.

Digital drilling may help you do that.

Data mining (also known as pattern recognition) is an anti-terrorist intelligence strategy. Data mining means bringing together different kinds of databases, linking them, and trying to identify suspicious patterns of individual behavior. The purpose is to prevent terrorist attacks. Suspicious behavior may indicate that such an attack is imminent, and data mining has been defended as the most important prevention tool.

If a Muslim chemistry graduate takes an ill-paid job at a farm-supplies store what does it signify? Is he just earning extra cash, or getting closer to a supply of potassium nitrate (used in fertilizer and explosives)? What if apparent strangers with Arabic names have wired him money? What if he has taken air flights with one of those men, with separate reservations and different seats, paid in cash? What if his credit-card records show purchases of gadgets such as timing devices? (source)

Intelligence services are routinely bringing together different data-bases such as

• credit card and payment data
• travel data, flight reservations, hotel reservations
• census data such as race, religion, occupation
• data on internet use, email and phone use
• police information such as convictions, known associates, fines for illegal photography
• CCTV data (e.g. from cameras situated close to extremist mosques)
• etc.

When all these data bases are linked, the value of the information they contain increases significantly. When intelligence services learn that someone travels to Afghanistan or Pakistan, it may not ring a bell. And anyway, there are too many people travelling to these places. But if they filter on those people who also read extremist websites, visit extremist mosques, have extremists associates, travel in the plane as other suspicious persons, have suspicious payments etc., then they may be on to something.

(source)

However, data mining may lose some of its benefits to the extent that terrorists are aware that this is happening and fine-tune their behavior. They know that much of this data mining is, by necessity, automated in computer programs which assign a "suspicion value" to certain activities or combinations of activities (the data bases are too big to do it any other way). So they can lower their suspicion score by regularly visiting very non-Muslim websites such as porn sites, or call telephone numbers of brothels.

Data mining may lose it effectiveness and has also been criticized as an invasion of privacy and a criminalization of behavior that is perfectly legal even if sometimes somewhat strange. Normally, invasions of privacy such as phone-tapping require a prior suspicion. Data mining means spying on people without such as prior suspicion, because suspicion can only be established as a result of mining, not beforehand.

It means spying on people in two different ways:

• The data bases used contain individual data that were not intended for use by intelligence services and that were often handed over by individuals on the assumption that the data would be treated confidentially.
• When a suspicion is established on the basis of data mining, more traditional means of surveillance come into play (phone tapping, observation etc.), which also violate people's right to privacy.

Of course, privacy is not an absolute value and different types of rights need to be balanced – in this case the right to privacy of some and the right to physical integrity and security of others. And an assessment has to be made of the priority of one right compared to another. But it seems to me that treating every citizen as a possible terrorist, and looking at his or her individual and private data as a matter of routine, is way over the top. I would like to see some information of the number of terrorist plots foiled by data mining.

But privacy is not the only victim. If someone is labeled "suspicious" as a result of data mining, he or she may end up on a "watch-list" and may find it difficult to travel or find a job in certain places deemed risky (hospitals, fertilizer producers, government agencies etc.).

"Electronic snooping by the state may safeguard liberty—and also threaten it" Link here.

Most of the information about us is created and maintained not in the Government sector, but in the private sector.  Commercial transactions (grocery store purchases, credit cards, travel bookings, etc.) are collected, mined, and often sold to 3rd parties.  It's a good and healthy exercise to ensure our Gov't is following the rules when collecting information, but shouldn't we hold commercial companies accountable too?

En annan sak som gör programmet speciellt är dess synkronitet, att kunna hålla sig (nästan) konstant uppdaterad med information. Det tror jag kan förändra vårt beteende, genom att gränser rivs ner på så sätt att ännu ett steg mot att integrera "sociala tjänster" i vår verksamhet vid datorn och att på sätt och viss närma sig synkron kommunikation (något som sker nästan samtidigt). Även om något sådant som synkron kommunikation sällan förekommer medierat, över internet, utan är något som är mer förknippat med ansikte-mot-ansikte-möten.  Dock är det väl en fråga om tolkning, då vi eventuellt kan hållas uppdaterade av andra människors beteende i en ganska strid ström (finns nog inga sådana applikationer som övervakar den andra personens datoraktivitet på en sådant sätt, men kommunikation med hjälp av webbkameror existerar). Viktigt att poängtera är att synkroniteten också kan leda till stress, som i så många andra områden där gränser bryts ner (som mellan arbete och fritid) kan detta bli till en del av att människor ska hålla sig uppkopplade och tillgängliga. Det kan gå så långt att det blir en förväntan, att du ska använda programmet och att svara snabbt när du kallas, det vill säga att du fått en notis om att någon har skrivit till dig.

Det handlar inte om att du blir övervakad, utan att du övervakar dig själv. För det är ju så att det är dig det handlar om där ute, hålla koll på vad andra människor gör med dig och att hålla sig á jour om vem du är och blir till.

Toda empresa se transforma y va creciendo. A medida que se va consolidando, ve la necesidad de contar con información de manera  más rápida, pertinente y eficaz. En la actualidad esto es posible gracias al Data Warehouse.

El Data warehouse provee de la información necesaria para analizar la realidad de la empresa y, por tanto, definir políticas de acción tendentes a mejorar su quehacer.

Un Data Warehouse provee el medio de integración en un mundo de sistemas de aplicaciones no integrados, haciendo posible recuperar información, además, proporciona una plataforma sólida de datos históricos e integrados, para posteriormente realizar análisis sobre ellos.

En palabras simples, un Data Warehouse es un almacén de información, que proviene de distintas aplicaciones en la organización.

A continuación, citare uno de los conceptos del Data Warehouse más populares; la minería de datos.

¿Minería de Datos o Data Mining? La minería de datos o Data Mining es un proceso que, a través del descubrimiento y de la cuantificación de relaciones predictivas en los datos, permite transformar la información disponible en conocimiento útil de negocio. La idea es bucear en los datos buscando patrones estadísticos significativos, relaciones entre datos ocultos, segmentaciones, etc.

Esto se debe a que no es suficiente navegar por los datos para resolver los problemas de negocio, sino que se hace necesario seguir una metodología ordenada que permita obtener rendimientos tangibles de este conjunto de herramientas y técnicas de las que dispone el usuario. Constituye por tanto una de las vías clave de explotación del Data Warehouse, dado que es éste su entorno natural de trabajo.

Alguna de las aplicaciones comerciales de Data mining, son las siguientes

SPSS Clementine Data Mining System
Web: http://www.isl.co.uk
Enterprise Miner, de SAS Institute Inc.
Web: http://www.sas.com
GainSmarts, de Urban Science
Web: http://www.urbanscience.com

Pero, me referire esta vez a una aplicación totalmente libre y de código abierto; se trata de Weka 3, que trabaja en base a algoritmos y bajo una plataforma java. Sus mayores potenciales están orientados a proveer de las herramientas necesarias para el procesamiento de datos, clasificación, asociación, entre otras más funciones.

Para utilizar Weka 3, deberemos de tener instalado la consola java en el ordenador. Quizás uno de los inconvenientes de esta aplicación es que se encuentra en idioma inglés, pero las cualidades y resultados que ofrece lo convierten en muy eficaz en las tareas que realiza.

Esta disponible para Windows, MacOs y Linux; y su descarga se puede realizar desde el sitio web oficial de Weka 3.

I often wonder if I'm becoming too paranoid.

I've asked several people that question and haven't really gotten a response. Although when I told my estranged wife I had just purchased 1984, she said I should lay off that type of stuff.

But, after reading the first two chapters of George Orwell's classic novel, it seems apparent that the world of "Big Brother" is fast approaching. Truth is stranger than fiction, but what is stranger is when fiction becomes truth.

A few things that are frightening to me:

Satelite imaging-Anyone in the world can go to Google and view satelite images of your area from as close as a few hundred feet. If anyone can see that, what can "Big Brother" see?

Data mining-Done by corporations to figure out how to market to you...and by the government to figure out if you're a terrorist, thanks to the Patriot Act. Every carded transaction, cell phone call and Internet search becomes a matter of "national security."

Technological Advancements-Now this is the big one. There are several things to fear from technology and the exponential rate of advancement.

Last night, Coast to Coast A.M. featured guest Richard Dooling, whose book Rapture For the Geeks has been recently released. During the interview, Dooling discussed the evoloution of artificial intelligence and the possibility of it, one day, outsmarting humans.

Also, while talking about technology, host George Noory mentioned heat-detecting sensors in place at airports to help pick out potential terrorists. Talk about the "Thought Police." As Noory asked, what if you're just nervous? You could be pulled aside, strip-searched and interrorgated for hours just because your face was flushed.

Another disheartening aspect of technology is that although advancements have made life easier, in turn, things have also become more complicated and we are being dumbed down. 

Cell phones allow us to call from nearly everywhere...yet we no longer remember phone numbers. Video games are becoming even more complex and creating a virtual reality. There may soon come a time when we don't know when virutal reality ends and real reality begins.

We are becoming connected to the network and disconnected from life, friends, family. Although the network does allow us to stay in touch with friends and family. As Dooling mentioned, computers are already making decisions for us. Netflix picks out your movies; Amazon picks out your books; and MySpace places ads on your page, based on your interests, that you should click.

Am I a technophobe? Not entirely.

Am I paranoid? Maybe.

Is an Orwellian future on the horizon?

• Productos  DW / BI, Plataformas y Arquitectura
• BI Operacional y BI estratégica
• BICC, calidad de los datos y el Movimiento de MDM

[link]

Korupsi berawal dari bahasa latin corruptio atau corruptus. Corruptio berasal dari kata corrumpere, suatu kata latin yang lebih tua. Dari bahasa latin itulah turun ke banyak bahasa Eropa seperti Inggris yaitu corruption, corrupt; Prancis yaitu corruption; dan Belanda yaitu corruptie, korruptie. Dari Bahasa Belanda inilah kata itu turun ke Bahasa Indonesia yaitu korupsi.
(Andi Hamzah, 2005, Pemberantasan Korupsi)

Arti kata Korupsi

Korup : busuk; palsu; suap
(Kamus Bahasa Indonesia, 1991)

buruk; rusak; suka menerima uang sogok; menyelewengkan uang/barang milik perusahaan atau negara; menerima uang dengan menggunakan jabatannya untuk kepentingan pribadi
(Kamus Hukum, 2002)

Korupsi : kebejatan; ketidakjujuran; tidak bermoral; penyimpangan dari kesucian
(The Lexicon Webster Dictionary, 1978)

penyuapan; pemalsuan
(Kamus Bahasa Indonesia, 1991)

penyelewengan atau penggelapan uang negara atau perusahaan sebagai tempat seseorang bekerja untuk keuntungan pribadi atau orang lain
(Kamus Hukum, 2002)

Diambil dari buku KPK 'Mengenali dan Memberantas Korupsi'

What is Data Warehousing?
A data warehouse is the main repository of an organization’s historical data, its corporate memory. It contains the raw material for management’s decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems (Ref:Wikipedia). Data warehousing collection of data designed to support management decision making. Data warehouses contain a wide variety of data that present a coherent picture of business conditions at a single point in time. It is a repository of integrated information, available for queries and analysis.

What are fundamental stages of Data Warehousing?
Offline Operational Databases - Data warehouses in this initial stage are developed by simply copying the database of an operational system to an off-line server where the processing load of reporting does not impact on the operational system’s performance.
Offline Data Warehouse - Data warehouses in this stage of evolution are updated on a regular time cycle (usually daily, weekly or monthly) from the operational systems and the data is stored in an integrated reporting-oriented data structure.
Real Time Data Warehouse - Data warehouses at this stage are updated on a transaction or event basis, every time an operational system performs a transaction (e.g. an order or a delivery or a booking etc.)
Integrated Data Warehouse - Data warehouses at this stage are used to generate activity or transactions that are passed back into the operational systems for use in the daily activity of the organization.

What is Dimensional Modeling?
Dimensional data model concept involves two types of tables and it is different from the 3rd normal form. This concepts uses Facts table which contains the measurements of the business and Dimension table which contains the context(dimension of calculation) of the measurements.

What is Fact table?
Fact table contains measurements of business processes also fact table contains the foreign keys for the dimension tables. For example, if your business process is “paper production” then “average production of paper by one machine” or “weekly production of paper” would be considered as measurement of business process.

What is Dimension table?
Dimensional table contains textual attributes of measurements stored in the facts tables. Dimensional table is a collection of hierarchies, categories and logic which can be used for user to traverse in hierarchy nodes.

What are the Different methods of loading Dimension tables?
There are two different ways to load data in dimension tables.
Conventional (Slow) :
All the constraints and keys are validated against the data before, it is loaded, this way data integrity is maintained.
Direct (Fast) :
All the constraints and keys are disabled before the data is loaded. Once data is loaded, it is validated against all the constraints and keys. If data is found invalid or dirty it is not included in index and all future processes are skipped on this data.

What is OLTP?
OLTP is abbreviation of On-Line Transaction Processing. This system is an application that modifies data the instance it receives and has a large number of concurrent users.

What is OLAP?
OLAP is abbreviation of Online Analytical Processing. This system is an application that collects, manages, processes and presents multidimensional data for analysis and management purposes.

What is the difference between OLTP and OLAP?
Data Source
OLTP: Operational data is from original data source of the data
OLAP: Consolidation data is from various source.

Process Goal
OLTP: Snapshot of business processes which does fundamental business tasks
OLAP: Multi-dimensional views of business activities of planning and decision making

Queries and Process Scripts
OLTP: Simple quick running queries ran by users.
OLAP: Complex long running queries by system to update the aggregated data.

Database Design
OLTP: Normalized small database. Speed will be not an issue due to smaller database and normalization will not degrade performance. This adopts entity relationship(ER) model and an application-oriented database design.
OLAP: De-normalized large database. Speed is issue due to larger database and de-normalizing will improve performance as there will be lesser tables to scan while performing tasks. This adopts star, snowflake or fact constellation mode of subject-oriented database design.

Describes the foreign key columns in fact table and dimension table?
Foreign keys of dimension tables are primary keys of entity tables.
Foreign keys of facts tables are primary keys of Dimension tables.

What is Data Mining?
Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information.

What is the difference between view and materialized view?
A view takes the output of a query and makes it appear like a virtual table and it can be used in place of tables.
A materialized view provides indirect access to table data by storing the results of a query in a separate schema object.

What is ER Diagram?
Entity Relationship Diagrams are a major data modelling tool and will help organize the data in your project into entities and define the relationships between the entities. This process has proved to enable the analyst to produce a good database structure so that the data can be stored and retrieved in a most efficient manner.
An entity-relationship (ER) diagram is a specialized graphic that illustrates the interrelationships between entities in a database. A type of diagram used in data modeling for relational data bases. These diagrams show the structure of each table and the links between tables.

What is ODS?
ODS is abbreviation of Operational Data Store. A database structure that is a repository for near real-time operational data rather than long term trend data. The ODS may further become the enterprise shared operational database, allowing operational systems that are being re-engineered to use the ODS as there operation databases.

What is ETL?
ETL is abbreviation of extract, transform, and load. ETL is software that enables businesses to consolidate their disparate data while moving it from place to place, and it doesn’t really matter that that data is in different forms or formats. The data can come from any source.ETL is powerful enough to handle such data disparities. First, the extract function reads data from a specified source database and extracts a desired subset of data. Next, the transform function works with the acquired data - using rules orlookup tables, or creating combinations with other data - to convert it to the desired state. Finally, the load function is used to write the resulting data to a target database.

What is VLDB?
VLDB is abbreviation of Very Large DataBase. A one terabyte database would normally be considered to be a VLDB. Typically, these are decision support systems or transaction processing applications serving large numbers of users.

Is OLTP database is design optimal for Data Warehouse?
No. OLTP database tables are normalized and it will add additional time to queries to return results. Additionally OLTP database is smaller and it does not contain longer period (many years) data, which needs to be analyzed. A OLTP system is basically ER model and not Dimensional Model. If a complex query is executed on a OLTP system, it may cause a heavy overhead on the OLTP server that will affect the normal business processes.

If de-normalized is improves data warehouse processes, why fact table is in normal form?
Foreign keys of facts tables are primary keys of Dimension tables. It is clear that fact table contains columns which are primary key to other table that itself make normal form table.

What are lookup tables?
A lookup table is the table placed on the target table based upon the primary key of the target, it just updates the table by allowing only modified (new or updated) records based on thelookup condition.

What are Aggregate tables?
Aggregate table contains the summary of existing warehouse data which is grouped to certain levels of dimensions. It is always easy to retrieve data from aggregated tables than visiting original table which has million records. Aggregate tables reduces the load in the database server and increases the performance of the query and can retrieve the result quickly.

What is real time data-warehousing?
Data warehousing captures business activity data. Real-time data warehousing captures business activity data as it occurs. As soon as the business activity is complete and there is data about it, the completed activity data flows into the data warehouse and becomes available instantly.

What are conformed dimensions?
Conformed dimensions mean the exact same thing with every possible fact table to which they are joined. They are common to the cubes.

What is conformed fact?
Conformed dimensions are the dimensions which can be used across multiple Data Marts in combination with multiple facts tables accordingly.

How do you load the time dimension?
Time dimensions are usually loaded by a program that loops through all possible dates that may appear in the data. 100 years may be represented in a time dimension, with one row per day.

What is a level of Granularity of a fact table?
Level of granularity means level of detail that you put into the fact table in a data warehouse. Level of granularity would mean what detail are you willing to put for each transactional fact.

What are non-additive facts?
Non-additive facts are facts that cannot be summed up for any of the dimensions present in the fact table. However they are not considered as useless. If there is changes in dimensions the same facts can be useful.

What is factless facts table?
A fact table which does not contain numeric fact columns it is called factless facts table.

What are slowly changing dimensions (SCD)?
SCD is abbreviation of Slowly changing dimensions. SCD applies to cases where the attribute for a record varies over time.
There are three different types of SCD.
1) SCD1 : The new record replaces the original record. Only one record exist in database - current data.
2) SCD2 : A new record is added into the customer dimension table. Two records exist in database - current data and previous history data.
3) SCD3 : The original data is modified to include new data. One record exist in database - new information are attached with old information in same row.

What is hybrid slowly changing dimension?
Hybrid SCDs are combination of both SCD 1 and SCD 2. It may happen that in a table, some columns are important and we need to track changes for them i.e capture the historical data for them whereas in some columns even if the data changes, we don’t care.

What is BUS Schema?
BUS Schema is composed of a master suite of confirmed dimension and standardized definition if facts.

What is a Star Schema?
Star schema is a type of organizing the tables such that we can retrieve the result from the database quickly in the warehouse environment.

What Snow Flake Schema?
Snowflake Schema, each dimension has a primary dimension table, to which one or more additional dimensions can join. The primary dimension table is the only table that can join to the fact table.

Differences between star and snowflake schema?
Star schema - A single fact table with N number of Dimension, all dimensions will be linked directly with a fact table. This schema is de-normalized and results in simple join and less complex query as well as faster results.
Snow schema - Any dimensions with extended dimensions are know as snowflake schema, dimensions maybe interlinked or may have one to many relationship with other tables. This schema is normalized and results in complex join and very complex query as well as slower results.

What is Difference between ER Modeling and Dimensional Modeling?
ER modeling is used for normalizing the OLTP database design. Dimensional modeling is used for de-normalizing the ROLAP/MOLAP design.

What is degenerate dimension table?
If a table contains the values, which are neither dimension nor measures is called degenerate dimensions.

Why is Data Modeling Important?
Data modeling is probably the most labor intensive and time consuming part of the development process. The goal of the data model is to make sure that the all data objects required by the database are completely and accurately represented. Because the data model uses easily understood notations and natural language , it can be reviewed and verified as correct by the end-users.
In computer science, data modeling is the process of creating a data model by applying a data model theory to create a data model instance. A data model theory is a formal data model description. When data modelling, we are structuring and organizing data. These data structures are then typically implemented in a database management system. In addition to defining and organizing the data, data modeling will impose (implicitly or explicitly) constraints or limitations on the data placed within the structure.

Managing large quantities of structured and unstructured data is a primary function of information systems. Data models describe structured data for storage in data management systems such as relational databases. They typically do not describe unstructured data, such as word processing documents, email messages, pictures, digital audio, and video. (Reference : Wikipedia)

What is surrogate key?
Surrogate key is a substitution for the natural primary key. It is just a unique identifier or number for each row that can be used for the primary key to the table. The only requirement for a surrogate primary key is that it is unique for each row in the table. It is useful because the natural primary key can change and this makes updates more difficult.Surrogated keys are always integer or numeric.

What is Data Mart?
A data mart (DM) is a specialized version of a data warehouse (DW). Like data warehouses, data marts contain a snapshot of operational data that helps business people to strategize based on analyses of past trends and experiences. The key difference is that the creation of a data mart is predicated on a specific, predefined need for a certain grouping and configuration of select data. A data mart configuration emphasizes easy access to relevant information (Reference : Wiki). Data Marts are designed to help manager make strategic decisions about their business.

What is the difference between OLAP and data warehouse?
Datawarehouse is the place where the data is stored for analyzing where as OLAP is the process of analyzing the data,managing aggregations, partitioning information into cubes for in depth visualization.

What is a Cube and Linked Cube with reference to data warehouse?
Cubes are logical representation of multidimensional data.The edge of the cube contains dimension members and the body of the cube contains data values. The linking in cube ensures that the data in the cubes remain consistent.

What is junk dimension?
A number of very small dimensions might be lumped together to form a single dimension, a junk dimension - the attributes are not closely related. Grouping of Random flags and text Attributes in a dimension and moving them to a separate sub dimension is known as junk dimension.

What is snapshot with reference to data warehouse?
You can disconnect the report from the catalog to which it is attached by saving the report with a snapshot of the data.

What is active data warehousing?
An active data warehouse provides information that enables decision-makers within an organization to manage customer relationships nimbly, efficiently and proactively.

What is the difference between data warehousing and business intelligence?
Data warehousing deals with all aspects of managing the development, implementation and operation of a data warehouse or data mart including meta data management, data acquisition, data cleansing, data transformation, storage management, data distribution, data archiving, operational reporting, analytical reporting, security management, backup/recovery planning, etc. Business intelligence, on the other hand, is a set of software tools that enable an organization to analyze measurable aspects of their business such as sales performance, profitability, operational efficiency, effectiveness of marketing campaigns, market penetration among certain customer groups, cost trends, anomalies and exceptions, etc. Typically, the term “business intelligence” is used to encompass OLAP, data visualization, data mining and query/reporting tools.

Although I'm sometimes shocked by the level of ambivalence that friends, family and students exhibit toward protecting their privacy when using cell phones, Internet search engines and other new communication technologies, not all have let the issue fade. News today in the Washington Post that AT&T and Verizon, two of the biggest ISPs in the U.S., have responded to consumer concerns by agreeing to refrain from tracking customer Web behaviour unless they receive explicit permission to do so. This is a voluntary, not a legislated measure, no doubt designed to forestall government regulation and to challenge other big ISPs to do the same.

According to the Post report: "The announcement, made at a Senate committee hearing, represents a challenge to the rest of the Web world, where advertising is commonly delivered by companies that record a consumer's visits across multiple Web sites. The practice, known as "behavioral targeting," is largely invisible to customers and generally done without their consent."

Under the new regime of practice, the default won't be that consumers automatically "opt in" to participate in online tracking, but that they must configure their web browser if they want their Internet practices monitored. This is good news to consumers and privacy advocates, although some say it has the potential to radically affect industry-wide online advertising practices. Critics like the Interactive Advertising Bureau, an association representing the economic interests of ISPs (Google is a member) suggest that forcing users to "opt in" could undermine the Internet economy because advertising revenues underwrite so much of the content that appears online.

For the backstory on the involvement of senior figures in the Bush administration in the surveillance of American citizens, see this story from The Atlantic Monthly and this one from the LA Times.

In his 5,000 word article, a manifesto of sorts, he describes a form of marketing that is far beyond the traditional definition of marketing:
___________________________________________________________________________________

“"Now we have the ability to automate serendipity," says Dave Morgan, founder of Tacoda, the behavioral-marketing firm sold to AOL in 2007 for a reported $275 million. "Consumers may know things they think they want, but they don't know for sure what they might want. They're not spending all their time hunting for those things."

Take, for instance, flat-panel TVs. In 2006 Tacoda did a project for Panasonic in which it scrutinized the online behavior of millions of internet users -- not a sample of 1,200 subjects to project a result against the whole population within a statistical margin of error; this was actual millions. Then it broke down that population's surfing behavior according to 400-some criteria: media choices, last site visited, search terms, etc. It then ranked all of those behaviors according to correlation with flat-screen-TV purchase.

In that list, "shopping online for flat-panel TVs" ranked 22nd -- 18 places below "consumed 'Miami travel' content." Miami travel?

"Not Chicago travel," Morgan says. "Not Europe travel. Not business travel. Don't ask me why. But here's the incredible thing: No. 1 -- and significantly above the others -- was people looking at military content. It made no sense. Then I talked to a friend of mine who had been an officer in the first Iraq war. I said, 'What's going on?' He said, 'That's easy. The kids in the military are huge video-gamers. They get big, fat signing bonuses, and their housing is free. They don't need cars. So they buy big TVs.'"

Morgan followed up because he was curious and felt the need for this counterintuitive association to have an explanation. But he needn't have. Why ask why? The whole point is that data mining takes us to a realm beyond obviousness and common sense. The data speak for themselves.

This message was hammered home in research the same year for Budget Rent A Car's weekend-rental promotion. "Shopping for a rental car" was the No. 4 correlation. No. 1 was "recently read an online obituary." Try to connect the dots if you wish; meantime, go read some online obits and see what ads show up on the page.

"We no longer have to rely on old cultural prophecies as to who is the right consumer for the right message," Morgan says. "It no longer has to be microsample-based [à la Nielsen or Simmons]. We now have [total-population] data, and that changes everything. With [those] data, you can know essentially everything. You can find out all the things that are nonintuitive or counterintuitive that are excellent predictors. ...

There's a lot of power in that."

Analysis: Several Microsoft Research people are preparing papers based on their current research, and I'm considering attending myself (I've written before about MSR's work in analyzing large social networks). There are three Microsoft scientists on the Committee (Dou Shen, Haizheng Zhang, and Rina Panigrahy - check out Rina's publications on hashing and sketching algorithms).  It should be a top-notch conference, co-hosted by ACM and IEEE.

But that's way off in the future - what if you want to look at some research stuff right now? Well, I've been going through the related "Socio-Digital Systems" work of MSR Cambridge (UK), and they've just added more information to their section here of the main MSR site.  That's some neat stuff, more on the side of the actual social uses of digital data and the effects on our (still-human?) everyday lives.

Here's something else very cool: an MSR prototype called Research Desktop, "a project aimed to demonstrate Microsoft innovation in the area of content management and analysis and design of personal information management environments," in the words of the background literature.

On the Research Desktop site, check out the videos listed on the right hand side as "Video Demos." You can view them one-by-one, each describing different facets of the Research Desktop design and capabilities, but if you want to just watch one, check out the 3-minute "Research Desktop in Action" demo.  

Researchers, from historians and sociologists to market specialists and financial analysts, engage in a range of activities in order to accomplish their tasks. This often involves gathering relevant sources of information and reading through the material to find important aspects of a topic. After analyzing the material they communicate their findings to their colleagues and the rest of the community in form of publications or online discussions."

"In contrast to workflows of well structured business processes, researchers conduct their work in different ways depending on their experience, style, and preferences... Research Desktop provides dedicated information spaces: personal Library to collect books, manuscripts, relevant articles and media, and Notes to enable simple storage and access to content snippets, URLs, and other bits of information that can easily be misplaced or can be difficult to find."

"Research Desktop is powered by a selection of tools and services that can be used in various contexts. Users can easily analyze individual books or collections of publications, create a co-author network, and discover trends in data. It revolutionizes the way we work by providing easy access to functionalities that are typically hidden within applications or not commonly found in the desktop environment."

Let me know if you find the prototype of interest; we've already had some government people who've expressed interest in access to it. 

Work like this takes smart people, and MSR is lucky to have a great collection of them. We've just added another: Danah Boyd, the well-known Web 2.0 researcher (she prefers just "2.0" to ensure the social elements are emphasized) just announced this week on her blog that "I will be joining Microsoft Research in January."  She has a great way of describing her attraction to MSR and the types of things she intends to work on, at the new MSR lab in the "other" Cambridge (Mass).  Since that lab is focusing on the social sciences (the softest of all sciences, and therefore naturally where I did doctoral work), I'm really looking forward to working with her.

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In his line of work - forensic and special investigations technology - the amount of data he works with can be immense. He has to sift through hundreds of depositions involved with these investigations and find key concepts, as well as major differences in recollections in the depositions.

When he was first introduced to Leximancer, he saw the potential. He first used Leximancer in his previous position as group general manager at Telstra, but he also engaged with Leximancer himself with his own company, Forensic Technology Pty Ltd. After working with nearly every text analytics platform rolled out in the last decade, Roger Levy has found Leximancer to be the best for his work.

"Leximancer's key benefits are identifying the focal points and key elements of large text documents and identifying trends and differences," Levy said. "Currently we use Leximancer to analyze depositions during investigations and legal proceedings, looking for key focuses, differences in recollections and summarizing experiences. We also are evaluating the platform in several other areas including evidence analysis."

Forensic investigations often involve the services of a medical examiner, crime laboratory analyst, crime scene examiner, forensic engineer, psychological profiler, statistician, computer analyst and a polygraph expert.   The amount of written reports and depositions accompanying a forensic investigation can be massive, and an automated data analysis platform like Leximancer serves to bring speed and interactive visual mapping tools to the laborious process of analyzing the body of collected data.

Roger feels he can definitely recommend Leximancer to others working in the forensic sciences and feels that this is the beginning of a long-term relationship in a highly technical industry that can benefit from the rapid, thorough analysis of complex documents.

Leximancer's powerful technology has many applications across a variety of industries from rapid analysis of commentary on social networks to bringing speed to forensic and eDiscovery investigations to providing "hidden" customer insight to marketers.

Karena itu, sebaiknya seorang investigator (atau 'interviewer') membangun 'rapport' terlebih dahulu dengan subject dalam sebuah interview. Rapport tu artinya kurang lebih adanya hubungan atau keterkaitan antara 2 orang ato lebih.

Beberapa indikasi yang menunjukkan bahwa rapport telah terbangun misalnya tangan subject tidak bersedekap, posisi subject mendekat ke arah interviewer, posisi duduk subject yang nyaman, subject merespons dengan anggukan kepala dalam menerima pertanyaan, dan jawaban subject yang cenderung lebih panjang dan detail.

Menyebutkan Tujuan Interview

"Karena dalam kasus ini diduga ada korupsi atau fraud yang telah terjadi, kami mau bertanya apakah Anda terlibat di dalamnya."

Ini bukan contoh kalimat pembuka yang baik, karena akan membuat tersinggung subject yang sebenarnya tidak berbuat kesalahan. Di lain pihak, bagi subject yang sebenarnya berbuat kesalahan, pertanyaan semacam ini akan membuat mereka lebih berhati-hati atas jawabannya atau berkata tidak jujur.

Kalimat pembuka yang baik biasanya (1) tidak menyebut secara langsung adanya kecurigaan terhadap subject, (2) menyebutkan bahwa interview dilakukan untuk mengklarifikasi apa yang sebenarnya terjadi, (3) bahwa interview dilakukan atas permintaan pihak selain interviewer. Contohnya seperti ini:

"Kami membantu perusahaan Bapak/Ibu untuk mengklarifikasi apa sebenarnya masalah yang terjadi dalam transaksi ini. Karena itu kami akan melakukan interview dengan beberapa orang yang mungkin mengetahui transaksi ini, termasuk Bapak/Ibu."

Hal yang penting juga, sebaiknya subject ditanyakan apakah merasa nyaman untuk melakukan interview pada saat itu. Tujuannya (1) subject yang menolak tanpa alasan yang jelas sebaiknya diperiksa lebih lanjut (2) membangun rapport dimana subject lebih merasa nyaman dengan memiliki kebebasan dalam memilih waktu interview.

Mengawali Interview

Dalam interview sebaiknya ditanyakan pertanyaan pembuka dengan tujuan (1) agar subject terbiasa dengan format tanya/jawab yang akan dilakukan, (2) subject dapat memberikan penilaian atas sikap interviewer.

Biasanya subject akan merasa paling nyaman ketika berbicara dengan interviewer yang orangnya menyenangkan, sistematis dan tidak menunjukkan sikap ancaman (non-threatening).

Pertanyaan pembuka yang diajukan harus yang relevan dengan tujuan interview, misalnya tentang data pribadi.

"Bapak bekerja di mana sekarang?"
"Apa saja tugas Bapak di kantor?"
"Bapak tinggal di mana?"
"Sudah mempunyai istri/anak?"

Pertanyaan2 dasar itu bisa lebih dikembangkan lagi dan dilakukan 1-2 menit sampai subject merasa nyaman untuk diwawancarai.

Satu hal yang penting, sebaiknya dihindari mengajukan pertanyaan2 yang kurang relevan sebagai pembuka interview, seperti:

"Bapak suka lihat film apa?"
"Apa Bapak hobi nonton Liga Inggris?"

Dengan mengajukan pertanyaan yang kurang relevan, bisa jadi (1) subject merasa curiga karena terkesan interviewer memaksakan adanya rapport, (2) membingungkan subject dari tujuan interview.