Introduction
“According to Forrester Research, American workers spend $404 billion annually, or 11% of all U.S. wages, looking for the information they need to do their jobs. Giving employees the right tools to stay afloat in a data and knowledge-driven workplace is imperative across the board.”[1]
With the world of digital data growing exponentially year on year, the above quote could just represent a mere drop in the ocean when accounting for the time workers spend looking for information. The next question is, once the information has been found, can it then actually be interpreted and understood within its original context and in the context required? Without adequate systems to deal with the data deluge, and efficient working
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However metadata can also be costly and time consuming, especially if the human element of inputting the information is the primary way of getting the data into the files. Automation of the population of metadata fields is desirable, and with new technologies this is achievable, however it should be ensured that the right information is going into an asset. If a user is searching for a specific thing, then the system should know that the result it returns is the right one, and often this can only be done by human intervention when adding metadata. To aid with this, certain machine readable metadata fields, such as technical information about a file, can be automated upon
ingestion to a DAM, however descriptive information can be much more subjective. This conceptual thought around the description of a file can limit its discovery, as can a lack of knowledge about it in terms of the individual populating any descriptive metadata fields. This is where prescribing to the thoughts of writers such as Bearman [5] around allowing users to describe records as they are the ones with the relevant knowledge, can be very useful, but depending upon the institutions workflow it may also be impractical. Whatever metadata scheme is used, it must be properly structured to ensure it aids discovery, and displays all the information relevant to both the file and the
According to Lisa Arthur, big data is as powerful as a tsunami, but it’s a deluge that can be controlled. In a positive way it provides business insights and value. Big data is data that exceeds the processing capacity of conventional database systems. It is a collection of data from traditional and digital sources inside and outside a company that represents a source of ongoing discovery and analysis. The data is too big, moves to fast, or doesn’t fit the structures of the database architecture. Daily, we create 2.5 quintillion bytes of data. In the last couple years we have created 90% of data we have in the world. This data comes from many places like climate information, social media sites, pictures or videos, purchase transaction records, cell phone GPS signals, and many more places. From the beginning of recorded time through 2003 users created 5 billion gigabytes of data. 2011, the same amount was created every couple days. 2013, we created that same amount every ten minutes. Some users prefer to constrain big data into digital inputs like web behavior and social network interactions. The data doesn’t exclude traditional data that is from product transaction information, financial records and interaction channels.
* A powerful search engine where you can search on metadata such as media type, category, performer, product name and more. Search results are grouped together so the same file will only be displayed once.
Key Internet Cases (2002) Significant Internet Jurisdiction Cases. Online at http://www.unc.edu Referecned on November 22nd, 2004
This strategy successfully persuaded older employees to adopt Box, a cloud-based storage platform for the company’s architectural drawings and financial documents. The organization’s adoption of the Box software grew out of a trial at one job site and just took off, caught fire, adoption-wise... And soon, what had started as a small group test grew intoalmost one hundred Box users within a few weeks. The reason for this growth was word-of-mouth testimonials that employees gave after using the software within the company. In addition to his cheerleader approach, Sarrubi also makes sure that working with the new technology is “as easy as using Amazon.” Cost, scalability, and return-on-investment are important factors the company considers when making IT decisions, but end-user preference is also a big factor in what technologies the company
Automated is transform the materials or records into digital form. As the era of the technology present, the demanding of digital records is drastically increased. Automated records may present archivists their greatest challenge in identifying, selecting, and preserving records of enduring value. Since the introduction of the computer, archivists have been concerned about its impact on their profession's mission. Based on report by the National Archives of Canada on machine-readable data stated that "if one were to take the traditional archival approach of waiting for whatever recorded information came out of the system, then the archivist in the electronic age will undoubtedly die of information starvation."23 Over the past decade archivists have tried to redefine their role in the modern information age, 24 but many seem to have been merely paying lip service to society's major shift to an "information" era. At present one can count on one hand the number of major programs established to deal with automated records, and these are only located at some of the largest archival institutions - The National Archives of Canada, the U.S. National Archives, and the New York, Utah, and Kentucky state archives. Contrast this with the facts: computers have been used for three decades, personal computers have become an ubiquitous feature of society in just the past decade, and a major portion of all information presently being created is going into automated systems of some variety. Nevertheless, there is overwhelming evidence that archivists are not effectively appraising such information nor using the helpful findings of previous research. 25 Current research is, however, both innovative and promising. Archivists have made substantial pro...
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As the Big Data era advances, the significance of data is changing. In addition to supporting business decisions and transactions, data is often now the good being traded, as companies begin to grasp the seemingly boundless potential value inherent in the data itself. Decreasing storage costs combined with the ability to collect data passively (through technological progress) mean that many companies are finding it easier to justify preserving the data rather than discarding it once its primary function h...
Kasdorf, B. (2014). Welcome to the metadata millenium. Book Business, 17(1), 18-23. Retrieved from http://search.proquest.com/docview/1500945974?accountid=10043
Digital asset management systems (DAMS) include computer software and hardware systems that aid in the process of digital asset management. (Beal,2015). The Key to Social Media Success Within Organizations, Is always the right answer .
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"Although fully searchable text could, in theory, be retrieved without much metadata in the future, it is hard to imagine how a complex or multimedia digital object that goes into storage of any kind could ever survive, let alone be discovered and used, if it were not accompanied by good metadata" (Abby Smith). Discuss Smith's assertion in the context of the contemporary information environment
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