Innovation and research are at the top of the political agenda in developed and developing countries. This has been especially true in these times of crisis and restructuring. Global competition puts pressure on companies and regions to improve their competitiveness through knowledge, high skills and research. The way people share intimate details and complete tasks such as dating, shopping, and job applications is very different from previous generations. Now, one’s preferences, opinions and activities are usually shared with a group of friends with whom they may or may not meet if it were not for the social network. In particular, there are three key areas of rapid change that are likely to lead to systemic change in science, with the associated opportunities and threats. The growth of authorship, the explosion of publication, and the availability of data are these three prominent areas.
Science 2.0 and Research
The three trends described above, and how they could affect the rules of the game, can be seen as three dimensions of change. They in turn have a great impact on the quantity and nature of science. Reliable filters and services should help readers make sense of overwhelming content. Filtering will depend on reputation management systems that will help readers browse the content.
A new model will be based on actual references and links to contributions. Reputation will become the most precious resource, generating attention, power and financing. Reputation management systems will be crucial: New, more open, flexible and transparent approaches are emerging, based on implicit and explicit data. They contain inbound links, page views or ratings.
However, no clear model is already in sight. In fact, current systems are playable. It will undoubtedly be an “evolving model” for reputation management, based on qualitative and quantitative data, highlighting a contrast to the existing “impact factor” model. It is quite possible that a third-party reputation management system will be developed, which dynamically evaluates and qualifies researchers. This includes qualitative and quantitative contributions, emphasis on network analysis, implicit and explicit data. Existing indexes will continue to be important, but will be more open and transparent, thanks to diversification of the publication and access to reader comments.
Data growth and processing
The data landscape is transformed due to major interrelated trends. The cost to access the data has been drastically reduced. Much of the useful statistics and more general research data are now published and freely available in plain format on the Web. The new availability of large amounts of data, along with statistical tools to analyze these numbers, offers a completely new way of understanding the world. Correlation replaces causality, and science can move forward even without coherent models, unified theories, or really no mechanistic explanation at all. Truly, the nature of science is affected by new possibilities.
Social features added to non-social sites
These customer reviews provide valuable information that people search for, and are written by users for free simply out of a desire to share their experiences with a product or service with others. The quality and value of each review are determined by other users, who rate them based on whether or not they found the comments useful, ignoring useless or irrelevant information, taking them to the bottom of the page. Non-retail special interest websites have also implemented social media features to broaden their appeal – an example is Allrecipes.com. This is a community of 10 million cooks who share ideas and recipes with each other. In addition to exchanging recipes with others through the website, users can rate and post reviews of recipes they have tried, and provide suggestions on how to improve or alter them.
According to the website, “Ratings and reviews are a valuable resource for our community because they show how members and their families feel about a recipe. Does the recipe excite people, or conversely, is it never made again? Your opinion counts. ”This feedback is used to evaluate and rank recipes based on how successfully they went through the site’s” editorial process “and to what extent they were approved by site members, which could result in them receiving status “Kitchen Approved” which is comparable to Wikipedia’s “good article” naming system.
Social art
Artists use the social web to share their art, be it visual art on sites like deviantART, video art on YouTube, musical art on YouTube or iTunes, or physical art, such as posting and selling handmade items on Craigslist. Artists choose to publish their art online so that they can get criticism of their work, as well as have the satisfaction of knowing that others can experience and enjoy their work. These tools allow to easily share art and broaden the discussion between artists and the public and obtain relevant data.
Crowdsourcing as a form of Research
Crowdsourcing has become one of the ways in which the social Web can be used in collaborative efforts, particularly in recent years, with the start of the semantic web and Web 2.0. Modern web applications have the capabilities for crowdsourcing techniques, and consequently the term is now used exclusively for web-based activities. Examples include sites like SurveyMonkey.com and SurveyU.com; for example, SurveyMonkey allows users to manage surveys to a list of contacts they manage, then collect and analyze response data using the basic tools provided on the website, and finally export these results once they are finished.
The researchers use crowdsourcing to emulate a traditional focus group, but in a less expensive and less intimate atmosphere. Due to the nature of the social web, people feel more open to expressing what their thoughts are on the topic of discussion without feeling that the rest of the group will examine them with as much attention compared to a traditional setting. The Internet serves as a sort of screen, helping to evoke the purest comments from participants in the group, as it removes much of the crowd mentality.
Community-based software projects
Web-based software projects Through the use of the social Web, many software developers choose to participate in community-based open source software projects, as well as proprietary software piracy projects, kernel modifications, and freeware ports. games and software. Linux iterations are perfect examples of how effective and efficient this type of research collaboration can be. Google’s Android operating system is another example, as many encoders are working on modifying existing hardware and ROM cores to create custom shapes from a released version of Android. These collaborative efforts for Android typically take place through xda-developers on the Android forums (androidforums.com)
Mobile application development
Most modern mobile apps, and even browser apps, come from software development kits released for developers. Developers create their applications and share them with users through “application markets”. Users can comment on their experiences with the applications, allowing all users to see the comments of others, and thus have a better understanding of what is expected of the application. Usually there is also a rating of a system in addition to the comments. Social web applications for mobile devices are created using various APIs (Application Programming Interface). These APIs allow the interaction and interconnection of data in a social database, be it Facebook, Twitter or Google account, thus creating a literal network of data connections. These applications add to the specific user experience of the application itself. Examples include TweetDeck and Blogger.
The real world and new forms of research
Many social websites use online social interaction to create a bridge to interaction in real life. Relationships are formed between individuals through the Internet and then become more personal through other forms of communication. An example of this type of interaction is found on eBay: With more than 94 million active users worldwide, eBay is the world’s largest online marketplace, where anyone can buy and sell pretty much anything. This website allows people to sell items and others to bid on these items. At the end of the auction, the buyer pays the seller; the buyer then sends the purchased product to the auction winner. The relationship begins on the Internet, but extends to real-life interaction. And you can get very interesting data.
Conclusions
In several scientific domains, including the “hard” sciences, a new type of scientific evidence is emerging that competes with traditional experimental methodologies that science has been supporting and developing for centuries. Current competencies in data mining, database bridging, and mathematical algorithmic analysis seem to allow for a competitive model of scientific research, based rather on correlations and probabilistic outcomes developed through the use of heterogeneous macro databases, rather than experimentation. traditional. This seems to be a new way of creating science and promoting research. At Online-tesis.com, we widely promote Science 2.0. Basically, there is a wealth of official and unofficial data, as well as data processing tools. Both will provide new opportunities for various actors in the processes of production and publication of science.
Bibliographic References
Mooney and S. Kirshenbaum, 2009. Unscientific America: How scientific illiteracy threatens our future. New York: Basic Books.
Nielsen, 2008. “The future of science,” at http://michaelnielsen.org/blog/the-future-of-science-2/.
Osimo, 2009. “A short history of eGovernment: From cool projects to policy impact,” In: J. Gøtze and C.B. Pedersen. State of the eUnion: Government 2.0 and onwards, at http://gotze.eu/writings/book20.
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Nuevas Formas de Investigación
