??
當下，“大數據”獲得了規模十分龐大的價值，這使得我們的商業世界站在了一個新行業的起點上。大量信息本身正在迅速演化成為一種資產類別，如同有著自己的生態系統、競爭動態和創新周期的軟件和硬件一樣。當然，相關法律問題也同樣不可避免。
全球政府和企業都在收集、存儲和利用數據寶藏，并開發了復雜的計算方法，以便從這些數據中提取價值。例如，零售商對我們生活的記錄比我們自己更加詳盡。借助大量的顧客接觸點，以及異常豐富的數據，零售商們甚至比消費者自己更早知道他們想要什么樣的產品和服務。
乍聽起來，這些事實可能有些令人毛骨悚然。雖然零售商們沒有違法，但人們仍在廣泛討論是否需要制定一些政策，以便在隱私、謹慎、社會認可和所有權與不可否認的大量商業機會之間尋求平衡。但是，暫且不論隱私問題，我們需要什么樣的法律制度來確保這個新行業的成長，并提供最大的個人和公共價值呢？我們要讓正在成長的大數據資產類別受制于叢林法則嗎？或者，我們需要新的規則去促進大數據行業的成長，使美國成為世界上最有吸引力的大數據行業基地嗎？這些并不僅僅是抽象的法律問題，而是與我們的專利權、商標權和版權（也就是知識產權）法直接相關的問題。
在初期階段，軟件是隨硬件銷售而免費贈送的。短短幾十年間，一個行業應運而生。隨著這個行業的發展，我們的法律制度做出了相應改變，通過新的、不斷發展的版權、專利權和商業秘密制度來促進這個行業的成長。如今，軟件行業產值達數千億美元，增長速度快、創新性高，并以極快的速度帶來全新的消費者利益和挽救生命的機會。而美國幾乎全面引領著整個軟件行業的發展。
很多人會說，美國的領導地位在很大程度上歸因于美國的支持性知識產權法，因為這部法律在提供激勵措施，促進對創新的投資與向第三方提供使用機會之間，取得了非常好的平衡。
因此，參考軟件行業的發展，可以公平地說，大數據行業風險很高，而且政策十分重要。但是，美國現行的知識產權體系內并不存在為調解大數據問題而量身定制的政策手段。然而，我們或許可以對知識產權法進行解釋或重塑，使其在為數據行業提供最佳保護和激勵措施的同時，實現社會利益的最大化。雖然我們現在還不具備大數據和知識產權之間相互作用的完整路線圖，但是我們的確擁有一些可行的出發點。舉例來說，我們的專利權和版權體系可以繼續發揮其當前的作用——保護利用數據來獲取價值的創造性方法（通過專利權）和數據本身的創造性（通過版權）。當然，還沒有證據表明需要在這些領域實行更高或更低級別的保護措施，而有句老話說得好：如果東西還沒壞，就不要去修。
就加快數據作為一種資產類別的發展而言，商標制度【想一想可口可樂(Coke )和麥當勞(McDonalds)等品牌】可能會發揮尤為重要的作用。特別是，認證標志可能會被證明非常有用。企業和消費者都會從認證機構【比如被廣泛認可和信任的UL（美國保險商實驗室）】實施的審查和標準符合性測試獲益匪淺。
一旦這些機構認證了一種適用產品或服務，它們就允許承辦商在商品或服務上附上認證標志。當你購買燈具或烤面包機時，“UL認證”標志提供了一個保證，它確保該電器可以和你家墻上的插座相匹配，并且兼容你家中的整個電氣系統。
那么，認證標志如何在大數據行業中發揮作用呢？數據認證標志將證明相關數據是準確的、格式正確且完全覆蓋主題。實際上，該標志將證明數據符合分析軟件的“壁式插座”。
我們可以設想，標準制定組織確立規范，并按照商定的質量和準確度水平，允許采集、清理、整理、格式化、存儲、保留、管理和提供數據的人使用適用的認證標志。而這些標準又可以支持對數據的交叉使用（如零售和醫療保健等行業之間）、后續使用（不再局限于最初采集數據時的目的，比如應用土壤成分數據來了解濕度水平）和研究（比如學術、政府或行業研究者的研究），這些應用必將使大數據成為重要的價值創造者。
目前，我們沒有理由認為，必須對知識產權體系進行徹底改革，才能確保知識產權在大數據時代中的安全。我們應該考慮的是，前文所述的情形將給商標制度帶來的新機會。最后，大數據將成為另一個衍生自信息與計算機技術，擁有光明前景的領域，而把促進數據行業成長作為政策重點的國家和地區，必將成為這一領域的領導者。(更多精彩資訊請點擊中國進出口網）
Our business world stands today at the threshold of a new industry, as “big data” gains value on a very big scale. Vast quantities of information are evolving rapidly into an asset class in its own right, akin to software and hardware with their own ecosystems and competitive dynamics and innovation cycles. And of course, legal issues.
There are troves of data being collected and stored and used by governments and companies globally. Complex algorithms are being developed to extract value from all this data. Retailers, for example, have a more detailed account of our lives than we ourselves can access. With their massive number of customer touch points, they’re so data-rich that they know what products and services customers want before consumers even know it themselves.
Some of this might sound a bit creepy. While retailers are not breaking any laws, there is much debate about the need for policies to harmonize privacy, prudence, social acceptance, and ownership with an undeniably massive business opportunity. But setting aside the privacy issues, what sort of legal regime do we need to ensure this new industry grows, and provides maximum private and public value? Do we leave the growing big data asset class to the law of the jungle? Or do we need new rules to foster growth and make our country the world’s most attractive home for the business of big data? These aren’t just abstract legal questions; they’re questions going directly to our patent, trademark, and copyright — intellectual property — laws.
When software was in its nascent stages, it was given away for free to sell hardware. Over the course of a few short decades an industry emerged. And along with it our legal system adapted to foster growth through new and evolving copyright, patent, and trade secret regimes. Now, software is a multi-hundred-billion dollar industry enjoying rapid growth and innovation, delivering bright new consumer benefits and life-saving breakthroughs at warp speed. And the U.S. leads the software industry practically across the board.
Many would say our country’s leadership is attributable in no small measure to our supportive intellectual property laws that have struck just the right balance between providing incentives for investment in innovation and providing access to third parties.
So taking software as a guide, it is fair to say the stakes are high, and policy matters. But no existing policy device within our current intellectual property system is tailored to mediate big data. However, it may be possible to interpret or re-fashion our IP laws so that the best protections and incentives are afforded to the data industry and the maximum social good is realized. While we do not yet have a complete roadmap for the interplay between big data and IP, we do have a few viable starting points. For one, our patent and copyright systems can continue to play their current roles – protecting inventive ways to draw value from data (through patents) and the creative aspects of data (through copyrights). There is certainly no evidence that a much greater or lesser level of protection is called for in these areas, and there is wisdom in the old saw: if it ain’t broke, don’t fix it.
The trademark system (think brands like Coke and McDonalds) may have an especially important role to play in accelerating the development of data as an asset class. Certification marks in particular may prove quite useful. Businesses and consumers alike benefit greatly from the vetting and standards compliance testing performed by certification organizations, such as the widely recognized and trusted UL (Underwriters Laboratories).
once these organizations certify compliance by an applicable product or service, they permit the purveyor to affix a certification mark. When you purchase a lamp or a toaster, the “UL Certified” mark provides assurance that the appliance will plug into the socket in your wall and work with your home’s electrical system.
How would this work in the big data industry? A data certification mark would attest that the applicable data is accurate, properly formatted, and thoroughly covers the subject. In effect, the mark would certify that the data’s prongs will fit into the analytical software’s wall socket.
One can envision standards-setting organizations establishing norms and permitting use of applicable certification marks by those who collect, clean, organize, format, store, retain, curate, and provide data according to an agreed-upon level of quality and accuracy. Such standards in turn would enable just the kind of cross-use (between industries like retail and healthcare), follow-on use (beyond the purpose for which the data was originally collected, such as wher soil composition data is used to understand moisture levels), and study (such as by academic, government, or industry researchers) that promise to make big data a huge creator of value.
At present, there is no reason to believe radical changes are needed in the IP system to render it safe for the advent of the data era. New opportunities for the trademark regime along the lines described above should be considered. In the end, the nations and regions that maintain a policy focus on fostering the growth of the data industry will be well positioned to lead into another promising field spinning out from information and computer technology.
全球政府和企業都在收集、存儲和利用數據寶藏，并開發了復雜的計算方法，以便從這些數據中提取價值。例如，零售商對我們生活的記錄比我們自己更加詳盡。借助大量的顧客接觸點，以及異常豐富的數據，零售商們甚至比消費者自己更早知道他們想要什么樣的產品和服務。
乍聽起來，這些事實可能有些令人毛骨悚然。雖然零售商們沒有違法，但人們仍在廣泛討論是否需要制定一些政策，以便在隱私、謹慎、社會認可和所有權與不可否認的大量商業機會之間尋求平衡。但是，暫且不論隱私問題，我們需要什么樣的法律制度來確保這個新行業的成長，并提供最大的個人和公共價值呢？我們要讓正在成長的大數據資產類別受制于叢林法則嗎？或者，我們需要新的規則去促進大數據行業的成長，使美國成為世界上最有吸引力的大數據行業基地嗎？這些并不僅僅是抽象的法律問題，而是與我們的專利權、商標權和版權（也就是知識產權）法直接相關的問題。
在初期階段，軟件是隨硬件銷售而免費贈送的。短短幾十年間，一個行業應運而生。隨著這個行業的發展，我們的法律制度做出了相應改變，通過新的、不斷發展的版權、專利權和商業秘密制度來促進這個行業的成長。如今，軟件行業產值達數千億美元，增長速度快、創新性高，并以極快的速度帶來全新的消費者利益和挽救生命的機會。而美國幾乎全面引領著整個軟件行業的發展。
很多人會說，美國的領導地位在很大程度上歸因于美國的支持性知識產權法，因為這部法律在提供激勵措施，促進對創新的投資與向第三方提供使用機會之間，取得了非常好的平衡。
因此，參考軟件行業的發展，可以公平地說，大數據行業風險很高，而且政策十分重要。但是，美國現行的知識產權體系內并不存在為調解大數據問題而量身定制的政策手段。然而，我們或許可以對知識產權法進行解釋或重塑，使其在為數據行業提供最佳保護和激勵措施的同時，實現社會利益的最大化。雖然我們現在還不具備大數據和知識產權之間相互作用的完整路線圖，但是我們的確擁有一些可行的出發點。舉例來說，我們的專利權和版權體系可以繼續發揮其當前的作用——保護利用數據來獲取價值的創造性方法（通過專利權）和數據本身的創造性（通過版權）。當然，還沒有證據表明需要在這些領域實行更高或更低級別的保護措施，而有句老話說得好：如果東西還沒壞，就不要去修。
就加快數據作為一種資產類別的發展而言，商標制度【想一想可口可樂(Coke )和麥當勞(McDonalds)等品牌】可能會發揮尤為重要的作用。特別是，認證標志可能會被證明非常有用。企業和消費者都會從認證機構【比如被廣泛認可和信任的UL（美國保險商實驗室）】實施的審查和標準符合性測試獲益匪淺。
一旦這些機構認證了一種適用產品或服務，它們就允許承辦商在商品或服務上附上認證標志。當你購買燈具或烤面包機時，“UL認證”標志提供了一個保證，它確保該電器可以和你家墻上的插座相匹配，并且兼容你家中的整個電氣系統。
那么，認證標志如何在大數據行業中發揮作用呢？數據認證標志將證明相關數據是準確的、格式正確且完全覆蓋主題。實際上，該標志將證明數據符合分析軟件的“壁式插座”。
我們可以設想，標準制定組織確立規范，并按照商定的質量和準確度水平，允許采集、清理、整理、格式化、存儲、保留、管理和提供數據的人使用適用的認證標志。而這些標準又可以支持對數據的交叉使用（如零售和醫療保健等行業之間）、后續使用（不再局限于最初采集數據時的目的，比如應用土壤成分數據來了解濕度水平）和研究（比如學術、政府或行業研究者的研究），這些應用必將使大數據成為重要的價值創造者。
目前，我們沒有理由認為，必須對知識產權體系進行徹底改革，才能確保知識產權在大數據時代中的安全。我們應該考慮的是，前文所述的情形將給商標制度帶來的新機會。最后，大數據將成為另一個衍生自信息與計算機技術，擁有光明前景的領域，而把促進數據行業成長作為政策重點的國家和地區，必將成為這一領域的領導者。(更多精彩資訊請點擊中國進出口網）
Our business world stands today at the threshold of a new industry, as “big data” gains value on a very big scale. Vast quantities of information are evolving rapidly into an asset class in its own right, akin to software and hardware with their own ecosystems and competitive dynamics and innovation cycles. And of course, legal issues.
There are troves of data being collected and stored and used by governments and companies globally. Complex algorithms are being developed to extract value from all this data. Retailers, for example, have a more detailed account of our lives than we ourselves can access. With their massive number of customer touch points, they’re so data-rich that they know what products and services customers want before consumers even know it themselves.
Some of this might sound a bit creepy. While retailers are not breaking any laws, there is much debate about the need for policies to harmonize privacy, prudence, social acceptance, and ownership with an undeniably massive business opportunity. But setting aside the privacy issues, what sort of legal regime do we need to ensure this new industry grows, and provides maximum private and public value? Do we leave the growing big data asset class to the law of the jungle? Or do we need new rules to foster growth and make our country the world’s most attractive home for the business of big data? These aren’t just abstract legal questions; they’re questions going directly to our patent, trademark, and copyright — intellectual property — laws.
When software was in its nascent stages, it was given away for free to sell hardware. Over the course of a few short decades an industry emerged. And along with it our legal system adapted to foster growth through new and evolving copyright, patent, and trade secret regimes. Now, software is a multi-hundred-billion dollar industry enjoying rapid growth and innovation, delivering bright new consumer benefits and life-saving breakthroughs at warp speed. And the U.S. leads the software industry practically across the board.
Many would say our country’s leadership is attributable in no small measure to our supportive intellectual property laws that have struck just the right balance between providing incentives for investment in innovation and providing access to third parties.
So taking software as a guide, it is fair to say the stakes are high, and policy matters. But no existing policy device within our current intellectual property system is tailored to mediate big data. However, it may be possible to interpret or re-fashion our IP laws so that the best protections and incentives are afforded to the data industry and the maximum social good is realized. While we do not yet have a complete roadmap for the interplay between big data and IP, we do have a few viable starting points. For one, our patent and copyright systems can continue to play their current roles – protecting inventive ways to draw value from data (through patents) and the creative aspects of data (through copyrights). There is certainly no evidence that a much greater or lesser level of protection is called for in these areas, and there is wisdom in the old saw: if it ain’t broke, don’t fix it.
The trademark system (think brands like Coke and McDonalds) may have an especially important role to play in accelerating the development of data as an asset class. Certification marks in particular may prove quite useful. Businesses and consumers alike benefit greatly from the vetting and standards compliance testing performed by certification organizations, such as the widely recognized and trusted UL (Underwriters Laboratories).
once these organizations certify compliance by an applicable product or service, they permit the purveyor to affix a certification mark. When you purchase a lamp or a toaster, the “UL Certified” mark provides assurance that the appliance will plug into the socket in your wall and work with your home’s electrical system.
How would this work in the big data industry? A data certification mark would attest that the applicable data is accurate, properly formatted, and thoroughly covers the subject. In effect, the mark would certify that the data’s prongs will fit into the analytical software’s wall socket.
One can envision standards-setting organizations establishing norms and permitting use of applicable certification marks by those who collect, clean, organize, format, store, retain, curate, and provide data according to an agreed-upon level of quality and accuracy. Such standards in turn would enable just the kind of cross-use (between industries like retail and healthcare), follow-on use (beyond the purpose for which the data was originally collected, such as wher soil composition data is used to understand moisture levels), and study (such as by academic, government, or industry researchers) that promise to make big data a huge creator of value.
At present, there is no reason to believe radical changes are needed in the IP system to render it safe for the advent of the data era. New opportunities for the trademark regime along the lines described above should be considered. In the end, the nations and regions that maintain a policy focus on fostering the growth of the data industry will be well positioned to lead into another promising field spinning out from information and computer technology.
