Digital Intellectual Property Law Essay: Big Data Patents

Digital Intellectual Property Law Essay: Big Data Patents By Sandro Sandri   1- BIG DATA Big data is a term for data sets that are so large or complex that traditional data  processing applications are inadequate to deal with them. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating  and information privacy. The term big data often refers simply to the use of predictive  analytics, user behaviour analytics, or certain other advanced data analytics methods that  extract value from data, and seldom to a particular size of data set.1 There is little doubt  that the quantities of data now available are indeed large, but thats not the most relevant  characteristic of this new data ecosystem. In another way Big Data is an evolving term that describes any voluminous amount  structured, semistructured and unstructured data that has the potential to be mined for  information. It is often characterized by 3Vs: the extreme Volume of data, the wide Variety  of data types and the Velocity at which the data must be processed. Although big data  doesnt equate to any specific volume of data, the term is often used to  describe terabytes, petabytes and even exabytes of data captured over time.  The need for big data velocity imposes unique demands on the underlying compute  infrastructure. The computing power required to quickly process huge volumes and  varieties of data can overwhelm a single server or server cluster. Organizations must apply  adequate compute power to big data tasks to achieve the desired velocity. This can  potentially demand hundreds or thousands of servers that can distribute the work and  operate collaboratively. Achieving such velocity in a cost-effective manner is also a  headache. Many enterprise leaders are reticent to invest in an extensive server and storage  infrastructure that might only be used occasionally to complete big data tasks. As a  result, public cloud computing has emerged as a primary vehicle for hosting big data  analytics projects. A public cloud provider can store petabytes of data and scale up  thousands of servers just long enough to accomplish the big data project. The business  only pays for the storage and compute time actually used, and the cloud instances can be  turned off until theyre needed again. To improve service levels even further, some public  cloud providers offer big data capabilities, such as highly distributed Hadoop compute  instances, data warehouses, databases and other related cloud services. Amazon Web  Services Elastic MapReduce is one example of big data services in a public cloud. Ultimately, the value and effectiveness of big data depends on the human operators  tasked with understanding the data and formulating the proper queries to direct big data  projects. Some big data tools meet specialized niches and allow less technical users to make  various predictions from everyday business data. Still, other tools are appearing, such as  Hadoop appliances, to help businesses implement a suitable compute infrastructure to  tackle big data projects, while minimizing the need for hardware and distributed compute  software know-how. a) BIG DATA AND THE GDPR The General Data Protection Regulation, which is due to come into force in May  2018, establishes a few areas that have been either drafted with a view to encompass Big  Data-related issues or carry additional weight in the context of Big Data, lets analyse just  two aspects. Data processing impact assessment According to the GDPR, where a type of processing in particular using new  technologies, and taking into account the nature, scope, context and purposes of the  processing, is likely to result in a high risk to the rights and freedoms of natural persons, the  controller shall, prior to the processing, carry out an assessment of the impact of the  envisaged processing operations on the protection of personal data. This criterion is most  likely going to be met in cases of Big Data analytics, IoT or Cloud operations, where the  processing carries high privacy risks due to the properties of either technology or datasets  employed. For example, linking geolocation data to the persons name, surname, photo and  transactions and making it available to an unspecified circle of data users can expose the  individual to a higher than usual personal safety risk. Involving data from connected IoT  home appliances or using a Cloud service to store and process such data is likel y to contribute  to this risk. Pseudonymisation According to the GDPR, pseudonymisation means the processing of personal data  in such a manner that the personal data can no longer be attributed to a specific data subject  without the use of additional information, provided that such additional information is kept  separately and is subject to technical and organisational measures to ensure that the personal  data are not attributed to an identified or identifiable natural person. At least two aspects link  pseudonymisation to Big Data. First, if implemented properly, it may be a way to avoid the  need to obtain individual consent for Big Data operations not foreseen at the time of data  collection. Second, paradoxically, Big Data operations combining potentially unlimited  number of datasets also makes pseudonymisation more difficult to be an effective tool to  safeguard privacy. b) BIG DATA APPLICATIONS Big data has increased the demand of information management specialists so much  so that Software AG, Oracle Corporation, IBM, Microsoft, SAP, EMC, HP and Dell have  spent more than $15 billion on software firms specializing in data management and  analytics. In 2010, this industry was worth more than $100 billion and was growing at  almost 10 percent a year: about twice as fast as the software business as a whole. Developed economies increasingly use data-intensive technologies. There are  4.6 billion mobile-phone subscriptions worldwide, and between 1 billion and 2 billion  people accessing the internet. Between 1990 and 2005, more than 1 billion people  worldwide entered the middle class, which means more people became more literate, which  in turn lead to information growth. The worlds effective capacity to exchange information  through telecommunication networks was 281 petabytes in 1986, 471 petabytes in 1993, 2.2  exabytes in 2000, 65 exabytes in 20073 and predictions put the amount of internet traffic at  667 exabytes annually by 2014. According to one estimate, one third of the globally stored  information is in the form of alphanumeric text and still image data, which is the format  most useful for most big data applications. This also shows the potential of yet unused data  (i.e. in the form of video and audio content). 2 Data, data everywhere. The Economist. 25 February 2010. Retrieved 9 December 2012.   3 Hilbert, Martin; Là ³pez, Priscila (2011). The Worlds Technological Capacity to Store, Communicate, and  Compute Information. Science. 332 (6025): 60-65. doi:10.1126/science.1200970. PMID 21310967.   While many vendors offer off-the-shelf solutions for big data, experts recommend  the development of in-house solutions custom-tailored to solve the companys problem at  hand if the company has sufficient technical capabilities. 2- PATENTS A patent is a set of exclusive rights granted by a sovereign state to an inventor or  assignee for a limited period of time in exchange for detailed public disclosure of  an invention. An invention is a solution to a specific technological problem and is a  product or a process. Being so, Patents are a form of intellectual property. A patent does not give a right to make or use or sell an invention.5 Rather, a patent  provides, from a legal standpoint, the right to exclude others from making, using, selling,  offering for sale, or importing the patented invention for the term of the patent, which is  usually 20 years from the filing date6 subject to the payment of maintenance fees. From an  economic and practical standpoint however, a patent is better and perhaps more precisely  regarded as conferring upon its proprietor a right to try to exclude by asserting the patent  in court, for many granted patents turn out to be invalid once their proprietors attempt to  assert them in court.7 A patent is a limited property right the government gives inventors in  exchange for their agreement to share details of their inventions with the public. Like any  other property right, it may be sold, licensed, mortgaged, assigned or transferred, given  away, or simply abandoned. The procedure for granting patents, requirements placed on the patentee, and the  extent of the exclusive rights vary widely between countries according to national laws and  international agreements. Typically, however, a granted patent application must include one  or more claims that define the invention. A patent may include many claims, each of which  defines a specific property right. 4 WIPO Intellectual Property Handbook: Policy, Law and Use. Chapter 2: Fields of Intellectual Property  Protection WIPO 2008 A patent is not the grant of a right to make or use or sell. It does not, directly or indirectly, imply any such  right. It grants only the right to exclude others. The supposition that a right to make is created by the patent  grant is obviously inconsistent with the established distinctions between generic and specific patents, and with  the well-known fact that a very considerable portion of the patents granted are in a field covered by a former  relatively generic or basic patent, are tributary to such earlier patent, and cannot be practiced unless by license   thereunder. Herman v. Youngstown Car Mfg. Co., 191 F. 579, 584-85, 112 CCA 185 (6th Cir. 1911)   6 Article 33 of the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS).   7 Lemley, Mark A.; Shapiro, Carl (2005). Probabilistic Patents. Journal of Economic Perspectives, Stanford Law and   Economics Olin Working Paper No. 288. 19: 75. relevant patentability requirements, such as novelty, usefulness, and non-obviousness. The  exclusive right granted to a patentee in most countries is the right to prevent others, or at  least to try to prevent others, from commercially making, using, selling, importing, or  distributing a patented invention without permission. Under the World Trade Organizations (WTO) Agreement on Trade-Related  Aspects of Intellectual Property Rights, patents should be available in WTO member states  for any invention, in all fields of technology,9 and the term of protection available should  be a minimum of twenty years.10 Nevertheless, there are variations on what is patentable  subject matter from country to country.   a) EUROPEAN PATENT LAW   European patent law covers a wide range of legislations including national patent  laws, the Strasbourg Convention of 1963, the European Patent Convention of 1973, and a  number of European Union directives and regulations in countries which are party to the  European Patent Convention. For certain states in Eastern Europe, the Eurasian Patent  Convention applies.   Patents having effect in most European states may be obtained either nationally, via  national patent offices, or via a centralised patent prosecution process at the European  Patent Office (EPO). The EPO is a public international organisation established by the  European Patent Convention. The EPO is not a European Union or a Council of  Europe institution.[1] A patent granted by the EPO does not lead to a single European  patent enforceable before one single court, but rather to a bundle of essentially  independent national European patents enforceable before national courts according to  different national legislations and procedures.[2] Similarly, Eurasian patents are granted by  the Eurasian Patent Office and become after grant independent national Eurasian patents  enforceable before national courts. 8 Lemley, Mark A.; Shapiro, Carl (2005). Probabilistic Patents. Journal of Economic Perspectives, Stanford Law and  Economics Olin Working Paper No. 288. 19: 75. doi:10.2139/ssrn.567883. 9 Article 27.1. of the TRIPs Agreement. 10 Article 33 of the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS). European patent law is also shaped by international agreements such as the World  Trade Organizations Agreement on Trade-Related Aspects of Intellectual Property  Rights (TRIPs Agreement), the Patent Law Treaty (PLT) and the London Agreement.   3- BIG DATA PATENTS 11 Patent Analytics Solutions That Help Inventors Invent, Outsell Inc, June 3 2016   Patent data is uniquely suited for big data tools and techniques, because of the high  volume, high variety (including related information) and high velocity of changes. In fact,  patents are leading the way with big data and analytics in many ways. The patent space  offers a fascinating insight into the potential of big data analytics, rich visualization tools,  predictive and prescriptive analytics, and artificial intelligence.11 Especially recently, big  data tools and technologies are being used in several ways in the patent world to transform  and improve patent analysis. Patents and Intellectual Property are gradually gaining significance around the  world. This is leading to a bottleneck-large databases and ever growing information. A new  way around the innovation problem is to acquire patents. With examples such as Nokia,  Motorola, Twitter, the patent purchases seem rather straightforward. Nokia sold a large  chunk of its company to Microsoft, but held on to the crucial patents by signing a licensing  deal. They can now earn a revenue using patents licensed to Microsoft. Google bought  Motorola and its patents and later sold the company to Lenovo while holding on to the  patents. There are ample such examples in the industry.   Transactions of Intellectual Property (IP) are rather complex. Per example, a basic  component to be verified before a patent is granted, is novelty. In other words, if a priorart  describing the invention is found, the application stands to be rejected. A prior-art  could be in the form of a publication, a blog post, a lecture, a video, or a book. With a  massive amount of information generated, that doubles every 18 months, it is extremely  difficult to found prior-art. One way, some organizations follow, is crowdsourcing the  prior art search. Details about the patent are published on a website asking IP professionals  from around the world to find a prior-art. The emergence of Big Data analytics, on the other hand, has provided a clear solution. In addition, the outcomes through this method  get better and precise with each operation. Since Big Data analytics is still not commonly used by most government authorities,  prior-art gets overlooked and many false patents are granted. This comes out when-in  litigation-the opposing parties put all their efforts in looking for a prior-art to invalidate  each others patents. More often than not, a prior-art is found or there is an out of court  settlement. Hence, a concept called patent wall has gained traction. It is very common for  companies to file as well as acquire a number of patents around the technology they are  working on. This serves as a defence against litigators and allows the companies to market  and sell their products/services without any fear of litigation. The core value of patents is that the invention must be publicly disclosed in  exchange for a time-limited monopoly on the invention. Patents are not only a legal asset  that can block competitors, they are potentially a business and financial asset. For market  participants, patents can provide direct insight into where competitors are headed  strategically. Big Data is the key to unlocking this inherent value. Patent information is  comprised of vast data sets of textual data structures involving terabytes of information.  When unlocked through Big Data techniques and analysis, the insights are compelling,  revealing the direction a technology is headed and even uncovering the roadmap for a  specific companys product plans. But, deriving these insights from the proliferation of  information requires truly sophisticated Big Data analysis.   While Big Data is quickly growing as a trend, whats delivering more value these  days are Big Data services that optimize specific data sets and create specialized analysis  tools for that data. Technology teams that are dedicated to certain data sets will curate and  improve the data, learn the specifics of that data and how best to analyze it, and create selfservice  tools that are far more useful than generic Big Data technologies.   A key part of the Big Data service is a specialized analysis engine tailored to  particular data. For example, a patent analysis engine must understand the dozens of  metadata items on each patent in order to group patents correctly and traverse the  references. To be most effective, Big Data services need to automatically keep up with the  data updates, as patents are living documents that change over time. Even after the patent  Big Data Patents  is finalized and issued, it can be reclassified, assigned to a new owner, reexamined and  updated, attached to a patent family or abandoned. Most importantly, Big Data services are only as good as the insights they deliver a  Big Data service should provide a specialized user interface that allows real-time, userdriven  analysis with search, correlations and groupings, visualizations, drill down and  zooms. The patent data analysis must be presented in a manner that is compelling and  consistent. There are more than 22,000 published patent applications between 2004 and 2013  relating to big data and efficient computing technologies, resulting in almost 10,000 patent  families. Patenting activity in this field has grown steadily over the last decade and has seen  its highest increases in annual patenting over the last two years (2011-2012 and 2012-2013)  of the present data set. The growth has continually been above the general worldwide  increase in patenting, showing a small increase of 0.4% over worldwide patenting for the  2005-2006 period and showing a maximum increase of 39% for 2012-13.~ Using a patent effectively means suing a competitor to have them blocked access  to market, or charge them a license for allowing them to sell. When a patent holder wishes  to enforce a patent, the defendant often can invoke that the patent should not have been  granted, because there was prior art at the time the patent was granted. And, while patent  offices do not seem to have a clear incentive to take into account actual reality, including  the exponentially available information created by Big Data, when reviewing the  application, the situation is very different for a defendant in a patent lawsuit. They will have  every incentive to establish that the patent should never have been granted, because there  was pre-existing prior art, and the information in the patent was not new at the time of  application. And one important consequence of Big Data will be that the information  available to defendants in this respect, will also grow exponentially. This means t hat, the  probability of being able to defend against a patent claim on the basis of prior art, will grow  significantly. Because of the lag of time between patent applications and their use in court,  the effect of the recent explosion of information as a result of Big Data is not very visible  in the patent courts yet. A patent is, of itself, an algorithm. It describes the process of a technical invention   how it works (at least, thats what a patent is theoretically supposed to be doing). It is  therefore quite possible that a lot of algorithms around analysis of Big Data will become  patented themselves. It could be argued that this will act as a counterweight against the  declining value and potential of patents. Many of these algorithms are, in fact, not technical inventions. They are theoretical  structures or methods, and could therefore easily fall into the area of non-patentable  matter. Algorithmic patents are particularly vulnerable to the ability by others to innovate  around them. It is quite unlikely that a data analysis algorithm would be unique, or even  necessary from a technical point of view. Most data analysis algorithms are a particular way  of doing similar things, such as search, clever search, and pattern recognition. There is, in actual fact, a commoditization process going on in respect of search and analytical  algorithms. Patents are frozen algorithms. The elements of the algorithm described in a  patent are fixed. In order to have a new version of the algorithm also protected, the patent  will either have to be written very vague (which seriously increases the risk of rejection or  invalidity) or will have to be followed up by a new patent, every tim e the algorithm is  adapted. And the key observation around Big Data algorithms is that, in order to have  continued business value, they must be adapted continuously. This is because the data,  their volume, sources and behaviour, change continuously. The consequence is that, even if a business manages to successfully patent Big Data  analytical algorithms, such patent will lose its value very quickly. The reason is simple: the  actual algorithms used in the product or service will quickly evolve away from the ones  described in the patent. Again, the only potential answer to this is writing very broad, vague  claims an approach that does not work very well at all.   80% of all big data and efficient computing patent families (inventions) are filed by  US and Chinese applicants, with UK applicants accounting for just 1.2% of the dataset and  filing slightly fewer big data and efficient computing patents than expected given the  overall level of patenting activity from UK applicants across all areas of technology.   Against this, however, it should be borne in mind that many of the potential improvements  in data processing, particularly with regard to pure business methods and computer  software routines, are not necessarily protectable by patents and therefore will not be  captured by this report. UK patenting activity in big data and efficient computing has, on the whole, increased over recent years and the year-on-year changes are comparable to the  growth seen in Germany, France and Japan.12 12 Intellectual Property Office, Eight Great Technologies Big Data A patent overview   BIBLIOGRAPHY à ¯Ã¢â‚¬Å¡Ã‚ · Herman v. Youngstown Car Mfg. Co., 191 F. 579, 112 CCA 185 (6th Cir. 1911) à ¯Ã¢â‚¬Å¡Ã‚ · Hilbert, Martin; Là ³pez, Priscila (2011). The Worlds Technological Capacity to Store, Communicate, and Compute Information. Science. (6025). à ¯Ã¢â‚¬Å¡Ã‚ · Lemley, Mark A.; Shapiro, Carl (2005). Probabilistic Patents. Journal of Economic Perspectives, Stanford Law and Economics Olin Working Paper No. 288. à ¯Ã¢â‚¬Å¡Ã‚ · Springer, New Horizons for a Data-Driven Economy à ¯Ã¢â‚¬Å¡Ã‚ · Data, data everywhere. The Economist. 25 February 2010. Retrieved 9 December 2012. à ¯Ã¢â‚¬Å¡Ã‚ · Eight Great Technologies Big Data A patent overview, Intellectual Property Office, à ¯Ã¢â‚¬Å¡Ã‚ · Patent Analytics Solutions That Help Inventors Invent, Outsell Inc, June 3 2016 à ¯Ã¢â‚¬Å¡Ã‚ · Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS). à ¯Ã¢â‚¬Å¡Ã‚ · Article 33 of the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS). à ¯Ã¢â‚¬Å¡Ã‚ · 75. doi:10.2139/ssrn.567883. à ¯Ã¢â‚¬Å¡Ã‚ · TRIPs Agreement. à ¯Ã¢â‚¬Å¡Ã‚ · WIPO Intellectual Property Handbook: Policy, Law and Use. Chapter 2: Fields of Intellectual Property Protection WIPO 2008 Google Chrome: A Freeware Web Browser Google Chrome: A Freeware Web Browser Google Chrome is a freeware web browser developed by Google that uses the WebKit layout engine. It was released as a beta version for Microsoft Windows on September 2, 2008, and as a stable public release on December 11, 2008. As of September 2012, according to StatCounter, Google Chrome had 34% worldwide usage share of web browsers making it the most widely used web browser. (wikipedia) An Internet browser developed by Google, that combines a minimal design with sophisticated technology to make the Web faster, safer and easier. The Google Chrome browser offers features including access to favourite pages instantly with thumbnails, desktop shortcuts to launch Web applications, and independently run tabs within the browser to prevent browser crashing. Chrome is known for is simplicity and speed, and people use it because it gets the job down, fast. But it doesnt end there, while being simple it is also very customizable allowing users to make it their own, some people get rather sceptical due to that, as they think, if its highly customizable, how can it be simple? Chromes UI is flawless; its simple yet effective that your mind just knows where to go without having to think. This is one of the main goals for any browser, to achieve this, the design and icons that the browser uses have to be recognisable straight away, for instance, the button to get back to chromes homepage is shaped as a house, this way our brain quickly realises it. Pros. 1. It wont crash. Perhaps Chromes largest feature is its multiprocess design, which helps the user a lot, protects you from having a bad Web page or application take your browser down. Every tab, window, and plug-in runs in its own environment, so one faulty/broken site wont affect anything else that you have opened. This approach also adds another layer of security by isolating each site and application within a limited environment. 2. Its really fast. Again because of the multiprocess design, one slow site wont drag down the rest of your browsing. Instead, you can effortlessly click to another tab or window. With plug-ins, the arrangement works similarly: If you open a site that has a slow-loading Java ad, for example, the Java itself will be isolated and the rest of the page wont be affected. The program itself opens within seconds of when you click the icon, tooa distinct advantage over some slower-loading alternatives. This gives users great control over their browsers and also developers of websites, as they can isolate problems quicker and easier. 3. You barely notice its there. Calling the design of Chromes interface efficient is an understatement. The program barely looks like a program, and the vast majority of your screen space is devoted to the site youre visitingwith no buttons or logos hogging space. Chromes designers say that they wanted people to forget they were even using a browser, and it comes pretty close to achieving that goal. 4. It makes searching simpler. One of Chromes signature features is its Omnibox, an integrated all-purpose bar at the top of the browser. You can type in a URL or a search termor bothand Chrome takes you to the right place without asking any questions. Omnibox can learn what you like, tooa talent that goes beyond the obvious automatic completion function. Say that you want to use the PCWorld.com search function, for example. Once youve visited the site once, Chrome will remember that PCWorld.com has its own search box and will give you the option of using it right from Omnibox. The function thus automates keyword searches. 5. It gives you more control over tabs. Chrome gives the idea of tabbed browsing new power. You can grab a tab and drag it out into its own individual window. Or you can drag and drop tabs into existing windows to combine them. Chrome also gives you the option of starting up in any tab configuration you wantwhether a custom setup or the set of tabs you had open in your previous session. Other browsers require third-party add-ons to provide this capability. 6. It opens new doors on your home page. Chrome comes with a default dynamic home page. As you use it, the program remembers the sites that you visit most often. The top nine of those appear in snapshots on your home page, along with your most commonly used search engines and bookmarks. Theres no force-feeding here, though: You can override the dynamic home page with any home page you want, just as you can set the default search engine to any service you prefer. 7. It lets you stay incognito. Like  Internet Explorer 8s recent beta release, Chrome offers a private browsing optionone it calls Incognito. You can open a special type of new window and rest easy knowing nothing you do in it will be logged or saved on your computer. And unlike Internet Explorers, Chromes Incognito window is isolated from the rest of your browsing experience, so you can have your private window open alongside your regular windows, and each will operate independently. http://www.neowin.net/forum/uploads/monthly_12_2010/post-261952-12913175021568.png RockMelt RockMelt is a proprietary social media web browser developed by Tim Howes and Eric Vishria. The project is backed by Netscape founder Marc Andreessen. RockMelt integrates a technique for surfing the web that focuses on Google Search and social media, in particular Facebook and Twitter. (wikipedia) RockMelt is Very Similar to Chrome, it uses an older engine than what chrome uses but otherwise the same, the only thing that is different is the UI, RockMelts UI is built for the people who use online social sites a lot, like Facebook and Twitter. The Left and Right sides of the browser are where the main social features are, it displays your friends that are online on the right (Facebook) and links displaying how many messages you have on Facebook, Twitter etc. on the left. Other social features can be found in the title bar and the menu dropdown. Pros The Facebook chat integration. The pop-out instant messaging windows enable you chat without needing to keep Facebook open. Plus, by adding friends the favourites list, you can easily see if the people you chat with the most are online. Another feature is the drag and drop ability. If you are on a website that I want to share with friends, simply grab the link and drag it over their photo on the left side bar. Then you have the option to share it with them via Facebook Chat, Facebook Message, or by posting it on their Facebook Wall. Additionally, you can easily share it with all of my Facebook friends or Twitter followers by dragging to the Share button next to the address bar. Cons There are a lot of Distractions! With everything from Facebook to the favourite blog feeds integrated right into the browser, theres almost too much going on. This is definitely not a browser to be used in the office. While its a really useful tool for social media integration, it definitely lowers peoples productivity Social Entrepreneurs: Traits And Limitations Social Entrepreneurs: Traits And Limitations This article is oriented to through a light and argues that social entrepreneurs do not give adequate consideration to gender and emphasise that there was a lack of research on womens contribution as social entrepreneurs; this article suggests other possible areas of study to advance this field of research. It brings out the extensive literature on social entrepreneurs and female entrepreneurs, while also drawing on the gender/diversity literature. This article creates interest to researchers who wish to examine aspects related to women as social entrepreneurs. It is also relevant to government agencies and social enterprise organisations those are looking to gain a more understanding of social entrepreneurs, their characteristics and the issues they face. It provides key avenues of further work to better understand the way in which sex and gender interact with the practices of social entrepreneurs. Though there is a tremendous increase in research on social entrepreneurs in recent years, a little consideration has been given to the womens contribution make as social entrepreneurs. Some work in academic research has started to profile social entrepreneurs, describe why they choose to become social entrepreneurs, the hurdles they face and the strategies they adopt. Although the research on the topic of social entrepreneurs is increasing, it is still largely based on an idealised vision of which the social entrepreneur is, often restricting the concept to a narrow pool of individuals and not taking into account the actual diversity within this category. Teasdale et al., 2011 says one such category which has been largely ignored in the literature consists of the contribution that women make as social entrepreneur. For the purpose of this paper, we will discuss the concept of social entrepreneurs independently of social entrepreneurship. This will avoid difficulties linked to the fact that not all social enterprises may be entrepreneurial or that not all social entrepreneurship comprises social enterprises. The premise of this paper is that much of the literature on social entrepreneurs is heavily influenced by mainstream literature on management and entrepreneurship, and as such the work on female social entrepreneurs may follow the same trend. Much of the work in the field of sex/gender and management/entrepreneurship has changed focus over the past two to three decades, moving from a largely descriptive field of research to a much more analytical one. One of the key characteristics has been the progressive move from sex to gender, going from looking at if sex makes a difference, to how gender makes a difference (see Carter and Shaw, 2006 for a fuller account). The literature on women entrepr eneurs has adopted an increasingly critical stance, denouncing the implicit maleness of the entrepreneur as a construct. One of its main criticisms is the androcentricity inherent in much of the entrepreneurship literature, which often relies on very gendered and stereotypical assumptions as to the role of men and women. The mainstream literature has given much attention to the topic of traits, looking for the actual social or psychological attributes possessed by successful entrepreneurs. However, the gendered nature of these very traits has been heavily criticised by scholars in the field of gender and entrepreneurs (Ahl, 2006; Marlow et al., 2009). In opposition to trait theory, which relies on a social-psychological approach, a more sociological approach has been proposed to look at identity construction rather than traits. This gives a voice to alternative groups (e.g. women), for example in the male-dominated Science, Engineering and Technology (SET) incubators (McAdam and Marlow, 2010) or among ethnic female entrepreneurs (Essers and Benschop, 2007; Humbert and Essers, 2012). This paper builds upon this body of work to provide a critical view of existing work on (female) social entrepreneurs and to shape a future research agenda. In particular, it aims to provide a brief account of current res earch on social entrepreneurs, followed by some of the findings directly related to the contribution of women. Because of the limited amount of material on women as social entrepreneurs, the paper also draws on literature on women within the social entrepreneurship, with applications to the case of social entrepreneurs where feasible. This review is informed by a focus group organised in June 2009 in London that brought together key informants such as policy makers, female social entrepreneurs and academics. Finally, the paper aims to provide a reflective gendered account of how these bodies of literature can be combined to inform further research on women as social entrepreneurs, before suggesting some possible avenues for research on the topic in the future. Social entrepreneurs: traits and limitations Some of the traits attached to social entrepreneurs are starting to be well documented. Some studies like Prabhu, 1999 suggest that social entrepreneurs are younger, possibly due to a higher risk propensity related to lower levels of family responsibilities. Ramsay and Danton, 2010 found that evidence from the UK suggests however those very young individuals are not very well represented among social entrepreneurs. It is important to consider the effect of age as there may also be potential links with the type of social enterprise being set up: younger social entrepreneurs may work on transformational actions while older social entrepreneurs may tend to focus more on charitable organisations. It might also be alternative forms of organisations that are adopted by younger social entrepreneurs. Leadbeater, 1997 focused on the development of social capital which is seen as important in the creation and subsequent development of social enterprises. Research into the potential importance of social capital among social entrepreneurs shows some evidence that personal/family history of (social) entrepreneurship may have a positive influence on the creation of social ventures but overall remains inconclusive. In the entrepreneurship literature, women are portrayed as being particularly influenced by this personal/family history (Marlow et al., 2009). This raises the question of to what extent this is also a factor among women social entrepreneurs. Shaw and Carter, 2007 stated that social entrepreneurs are able to show drive, determination, ambition, charisma, leadership, the ability to communicate vision and inspire others and their maximum use of resources. In order to do so, as Alvord et al. (2004) suggest, a characteristic associated with successful social entrepreneurs is that of a bridging capacity. This capacity is shaped by a social entrepreneurs background and experience which in turn is shaped by gender relations. Some authors have focused on developing a universal definition of social entrepreneurs, one which is heavily linked to, and directly derived from, the definition of an entrepreneur. One of the definitions adopted by Nicholls (2006:224) draws on Dees (2001) and bears some similarities with Chell (2008). It is worded in the following terms: Social entrepreneurs play the role of change agents in the social sector, by: à ¯Ã¢â‚¬Å¡Ã‚ · adopting a mission to create and sustain social value (not just private value); à ¯Ã¢â‚¬Å¡Ã‚ · recognising and relentlessly pursuing new opportunities to serve that mission; à ¯Ã¢â‚¬Å¡Ã‚ · engaging in a process of continuous innovation, adaptation and learning; à ¯Ã¢â‚¬Å¡Ã‚ · acting boldly without being limited by resources currently in hand; à ¯Ã¢â‚¬Å¡Ã‚ · exhibiting a heightened sense of accountability to the constituencies served and for the outcomes created. This definition assumes that there are fundamental differences between mainstream entrepreneurs and social entrepreneurs. Chell (2007:18) has worked on reconciling the two definitions and concludes that the differences can be eliminated by adopting the following: (social) entrepreneurship is the process of recognizing and pursuing opportunities with regard to the alienable and inalienable resources currently controlled with a view to value creation. This definition, while providing a platform for renegotiating theoretical differences between entrepreneurs and social entrepreneurs is still proving to be a very polarised stringent definition. This problem is in part resolved by adopting an alternative viewpoint where the ideal social entrepreneur should not necessarily fulfil all criteria in the above definition fully, but that there are different degrees of fulfilment for each and that a social entrepreneur does not necessarily need to meet all of them (Dees, 2001). If there are many commonalities between mainstream and social entrepreneurs, academic discourse bestows social entrepreneurs with extra, special, traits which underline the importance of their commitment and dedication to social aims. Not only are social entrepreneurs largely described as different in the literature, they are also often described as extraordinary individuals. Dees (2001:2) for instance describes entrepreneurs in the following terms: their reach exceeds their grasp. Entrepreneurs mobilize the resources of others to achieve their entrepreneurial objectives. Chell (2007:5) portrays a similar vision of the entrepreneur as a household name with a personality that is larger than life'. These quotes present a view of the entrepreneur as both metaphorically and literally uncontainable. Further research needs to explore how this discourse relates differently to men and women. It is also important to examine the role of women in the governance of social enterprises, The Social Enterprise Coalitions State of Social Enterprise Survey (Social Enterprise Coalition, 2009) show that the social enterprise sector provides a more egalitarian environment for women, as can be seen in terms of presence on boards; 41% of social enterprise board members in the SEC Survey 2009 are women (Humbert, 2011). However, this differs considerably between sectors. There is a strong need to recognise diversity among social entrepreneurs. Indeed mainstream entrepreneurship studies have often been criticised for failing to address heterogeneity (Ahl, 2006; Essers and Benschop, 2007) and it appears that these issues are at least as pronounced with regards to social entrepreneurship. An emphasis on entrepreneurial traits can therefore be criticised as being overly reductionist in that it discursively creates a hegemonic model of the social entrepreneur as s/he ought to be. Furthermore, it embeds the characteristics of social entrepreneurs into individualistic and economic settings, while disregarding the impact of the socially interactive and emotional settings (Goss, 2005). Social entrepreneurs: motivations, obstacles and strategies In addition to work focusing on who social entrepreneurs are, other studies analysed why they choose to become social entrepreneurs, the obstacles they face in doing so, as well as some of the strategies they employ to overcome these. This approach departs from attempting to describe successful social entrepreneurs in that it does not solely rely on natural characteristics but also recognises the importance of the environment, for instance through cultural or social influences. As such, social entrepreneurial awakening can be seen as a multiplicity of trigger factors in individual, personal, familial and professional backgrounds. Becoming a social entrepreneur can be seen as the end result of a more or less long maturing journey, characterised by a range of positive and negative inputs which are interpreted in a time-dependent cultural, societal and personal context. Amin (2009) talks about two main routes that lead to becoming a social entrepreneur. One is about being nurtured with the social economy and using the skills and resources acquired within that setting. The other is to come from the public or private sector and apply skills gathered there in the context of the social entrepreneurship. Motivations for social entrepreneurs are extremely complex, with evidence that rational choice theories are inappropriate due to the complexity and range of different inputs and their interpretations (Spear, 2006). Most studies find that there are usually many similarities between the motivations of mainstream and social entrepreneurs. Social entrepreneurs may not rate independence and income security highly, but give a lot of importance to their social objectives (Shaw and Carter, 2007). These social objectives are often portrayed as additional factors (Prabhu, 1999; Spear, 2006; Hudson, 2009) and include factors such as altruism, ethical/social concerns or ideological aims. While there is a significant degree of overlap among these categories, all of these extra motivations rely heavily on an individualistic identity construction, without considering the collective identitys role. Furthermore, social entrepreneurs motivations remain conceptualised using the entrepreneurs model, albeit with some added elements. This approach of adding extra elements is replicated when looking at the obstacles faced by social entrepreneurs. These are presented as being quite similar to those faced by mainstream entrepreneurs (Thompson, 2002). Future research will need to consider how some factors such as ethnicity and gender affect the magnitude of the obstacles encountered. Very little work has looked at issues of diversity among social entrepreneurs. The UK Government Equalities Office (2008) examined the motivations and obstacles associated with women social entrepreneurs within BAME (Black, Asian and Minority Ethnic) communities. This work identifies a tendency to get involved with ones community as a motivating factor while at the same time experiencing multi-disadvantage and discrimination. Multiple, and interacting, layers of identity can therefore be seen both positively and negatively. Generally social entrepreneurs report experiencing difficulties in accessing finance, as do mainstream entrepreneurs. Alternate sources of funding are used with little reliance on the three Fs (family, friends and fools), but instead finance is sought from charitable trusts or the public sector (regional, national, and European) (Shaw and Carter, 2007). This differs from the situation among mainstream entrepreneurs, who are more likely to rely on bootstrapping methods of financing their business (relying on internal funds rather than raising money externally). Women entrepreneurs are themselves more likely to rely on bootstrapping, raising the question of whether this is also the case among women social entrepreneurs. Another characteristic of social entrepreneurs is that they tend to operate in locations and sectors where they have experience (Shaw and Carter, 2007). Although this could be presented as caused by lack of experience, it could also be explained by the fact that they use available resources in a way that maximises their experiential capital. Alternatively, it could also be a strategy to minimise risk. As Shaw and Carter (2007) stress, in the context of social entrepreneurship, social and personal risk are more prevalent as opposed to financial risk. No discussion of the concept and experience of risk among women social entrepreneurs exist in the literature to the authors knowledge. Women in the Social Entrepreneurship To understand the area of female social entrepreneurs, and given the paucity of material available, this paper will therefore take a broader view by examining research on gender more broadly defined before discussing how the findings in those fields may apply to social entrepreneurs. Labour can be subdivided into at least three categories: self-employed, domestic and community work. While the experiences of women in both self-employment and domestic work have been well documented, less work has been undertaken on their community work and volunteering. This section aims to present some of the key findings in the literature on womens paid and voluntary labour. Mailloux et al., 2012 says women have had a positive impact on society through their involvement in the social entrepreneurship, by putting some topics such as children, family, womens health, violence and discrimination towards certain groups of population on the social agenda. Research also suggests that women may use the voluntary sector to counteract negative attributes such as re-entry to the labour force or building up skills. Generally, the involvement of marginalised groups is they women, ethnic-minority groups, are associated with greater levels of change. This can be seen through the involvement of women in supporting womens issues, sometimes within particular communities which may otherwise not benefit from the services or products provided. Caputo (1997) for example finds a link in the US between black women volunteering and changing social conditions. Research on women in the social entrepreneurship, whether in paid work or volunteering, attempts to generate a profile of these women and what they do. The proportion of women involved in the social entrepreneurship is greater than other parts of the labour market, as shown by example by Mailloux et al. (2002) and Teasdale et al. (2011) in Canada and the UK respectively. Their activities are contrasted to that of men and studies show that there are differences apparent in the type of work performed by women, the type of organisations they are involved with, as well as the nature of their involvement within these organisations. Women perform extra volunteer work on a regular basis (e.g. care work) without recognising it as such in the formal voluntary sector (Mailloux et al., 2002). In addition, the link between lower earnings and women seems to also apply in the social entrepreneurship, with lower salaries and benefits than in the private sector in a Canadian context (Mailloux et al., 2002). The popular misconception that involvement in volunteering is a way of occupying free or leisure time, particularly among privileged groups, needs to be challenged given that, in fact, much (less formalised) volunteer work is being undertaken by members of marginalised groups in order to counteract negative circumstances (Neysmith and Reitsma-Street, 2000). The motivations of women in the social entrepreneurship do not appear to be specific to women. They can consist of wanting to make a difference, to act, to help; belong to a group; build links with the community (Mailloux et al., 2002), thereby suggesting that there is a strong community embeddedness in the voluntary sector. Neysmith and Reitsma-Street (2000:336) emphasise that what they call the participatory component should not be underplayed and that volunteers attach importance to being part of something that [à ¢Ã¢â€š ¬Ã‚ ¦] is ours, not mine or theirs'. The motivations for volunteering are therefore seen as wanting to build relationships with others, developing life and work skills, getting ownership of the fruit of ones labour and combating negative social stereotypes. However, volunteer work is devalued in contrast to paid work. One aspect of this devaluation is through the invisibility of volunteer work. Volunteering has been theorized as an extension of womens family work, reinforcing separate spheres of ideology where mens work is defined and rewarded, as a public contribution but womens work, even though done in the community, is defined essentially as an extension of their private responsibilities to family (Neysmith and Reitsma-Street, 2000: 342). Further research should examine the extent to which expectations of such gendered roles are present in the social entrepreneurship. In terms of paid work, Gibelmans (2000) research suggests that the glass ceiling is still prevalent in the US nonprofit sector, along with evidence of a gender pay gap. An analysis of HR policies revealed a set of anti-discrimination affirmations with usually no plans for implementation. Furthermore, policies related to facilitating access to management for women (i.e. flexitime or help with caring arrangements) were seldom addressed. The study however fails to examine the role these policies play in (dis)advantaging (wo)men. Indeed, Moore and Whitts (2000) findings indicate that men are disproportionately more present on voluntary organisations boards, more likely to occupy multiple seats and to be involved in a various number of sectors compared with their female counterparts. As they state, nonprofit boards in the United States remain bastions of white, male privilege (2000: 324). Overall, the authors conclude that attention needs to be given to the lack of access to boards to pro mote greater gender equality rather than on how individuals fare within the boards once they get in. The notion of conflict for women between traditional and modern gender roles is an important one to draw upon. Very little work has been done on this topic, but some US and Canadian evidence suggests that even though women hold a desire to break away from traditional gender roles, there are advantages in using these along with punishment for moving to a more modern structure (Mailloux et al., 2002). However, this move to more modern gender roles may have a detrimental effect, particularly on volunteering, with lower participation from women (Caputo, 1997). The extent to which these patterns of inequality are found amongst social entrepreneurs is largely under-researched. In addition, since many of the sources quoted above are based in North America, the degree to which these findings could be extrapolated to Europe, or the rest of the world, remains a serious concern. Current European studies (e.g. Teasdale et al., 2011; Humbert, 2011) infer that there are many similarities, but their number and scope remains limited. In their study, Teasdale et al. (2011), support many of the findings highlighted in this section, and are not able to examine social entrepreneurs operating in either the public or private sector. While there is a dearth of research into gender effects in the social entrepreneurship, patterns of inequities present in the private sector may be largely replicated in the social entrepreneurship, albeit on a smaller scale. The extent to which these patterns are similar, or different, remain critically under-researched. Furthermore, none of this work to date has been applied to social entrepreneurs. In the next section, a gendered reflection on these areas of research is provided, along with some possible topics of research into this field. Conclusion Research on social entrepreneurs remains largely dependent on the assumption that a common set of characteristics inherent to social entrepreneurs exists. In effect, this has led to attempts to produce a universal definition of the social entrepreneur. This approach, which replicates the development of research on entrepreneurs, is problematic in the context of female social entrepreneurs since it relies on individual characteristics and may ignore the collective nature of entrepreneurship and may not address the real diversity of social entrepreneurs. This tendency towards the reification of the social entrepreneur requires further research particularly in terms of how it affects men and women differently and whether it excludes particular groups. This tension replicates the long-running argument in mainstream entrepreneurship as to the degree of inclusiveness that should be bestowed to the definition of an entrepreneur. Indeed, this area of research remains highly centred on previous research on entrepreneurs, and merely adds in extra elements, such as the social or the female, often ignoring the contribution of the intersection of these two concepts. It is the lack of attention given to the interaction between these two concepts, coupled with a lack of questioning of their stereotypical underpinning, that constitute one of the major drawbacks of this field of research. The stereotypical position is often evident through studies undertaken on women in the social entrepreneurship. Women are portrayed as doing different types of jobs, in different types of organisations, at a lower level and for less money. The rhetoric of difference (with men?) prevails. Moreover, women are portrayed as not motivated by pecuniary reasons but more by a desire to act as what can only be described as mothers of the community: women are there to help, to build, for others but never for themselves, and are seldom valued or rewarded for their work. Research undertaken on social entrepreneurs has often consisted of examining them in contrast with mainstream entrepreneurs (Nicholls, 2006). There is a lurking danger in any comparative stance in that it can easily position one party as the deviant other, often implying an inferior position. This is certainly the case with female entrepreneurs (Ogbor, 2000; Bruni et al., 2004; Hytti, 2005; Ahl, 2006). Indeed, previous research has shown that in the case of female entrepreneurs, it might be inadequate to use theories derived from an essentially male experience to describe women entrepreneurs (Stevenson, 1990; Greene et al., 2003). This argument has much deeper implications in that it shows that existing models of entrepreneurs based on the so-called mainstream entrepreneur are models based on what Ogbor (2000) terms the white male hero. These models assume that the entrepreneur does not have caring and/or domestic responsibilities (Ahl, 2006). The challenge resides in creating new models or adapting these to the area of the social and the female simultaneously. Adapting models in entrepreneurship research such as the family embeddedness perspective advocated by Aldrich and Cliff (2003) or the socio-economic context presented by Brush et al (2009) would be beneficial. The difficulty in conducting research on women as social entrepreneurs lies in paying attention to the discourses briefly outlined in this paper. It is important to depart from these discourses, as discourse and perspectives about, and for, the nature of entrepreneurialism are fundamental to both theory (how we think about, conceptualize and define terms) and practice (what capabilities and behaviours we believe apply to people whom we refer to as entrepreneurs) and moreover, to how the terms are used in a wider socio-political arena to serve particular ends (Chell, 2007:7).