3 QUESTIONS TO ASK YOURSELF BEFORE INVESTING IN AN ENTERPRISE SCIENTIFIC SEARCH ENGINE
Everyone knows about search engines like Google. They allow you to search through a set of contents indexed by an algorithm.
On the other hand, a scientific search engine is dedicated to the search of scientific content to meet the needs of scientists. In other words, a scientific search engine indexes specific data sources in one or more research areas.
To help you determine if you need a scientific search engine, ask yourself the right questions!
1- DOES THE DATA OR INFORMATION I AM LOOKING FOR EXIST?
This question may seem basic, but it is nevertheless essential. Indeed, how can I find scientific information or data if it does not exist or if I am looking for it in the wrong place?
At Dexstr, we have observed several types of behavior in this regard.
The meticulous ones: they search, dig, move heaven and earth and… find… or not!
The workers: they redo the (often expensive) experiment that will give them the results they hope for… or not!
The timekeepers : they set a time limit beyond which they stop searching… Too bad because maybe a minute or two more would have allowed them to find.
The assisted : they resort to the famous “call to a friend” to get providential help. But how many “friends” do they have? How many of them will succeed in being embarked in the quest without guarantee of results?
In short, so many strategies specific to each one, with results as uncertain as they are tedious! All the more tedious since my favorite search engine only searches the web, but it is highly likely that the data I am hoping for is hidden in the depths of my company’s information system.
2- SHOULD MY SEARCHES BE CONTEXTUALIZED?
The scientific domain, like all other business domains, has its own specificities. Your search engine must be able to contextualize your search to allow you to obtain the best results.
Where a simple enterprise search engine facilitates access to information and offers sorting and filtering systems, the scientific search engine uses ontologies and machine learning mechanisms that refine the relevance of the results displayed.
Within the same structure, the types of searches and contexts can vary from one service to another. A scientific search engine can be configured to adapt to all environments and use cases.
3- WHAT WILL I GAIN BY INVESTING IN AN ENTERPRISE SCIENTIFIC SEARCH ENGINE?
Time, efficiency, money! (sources: IDC, CIO-online.com)
Time: 73% of the work of data analysts is spent on research and preparation of results, while only 27% is spent on analysis and ultimately on adding value to the data.
Efficiency: in the detail of wasted hours, the report notes that a data analyst spends 14 hours per week on non-value added tasks. He spends 3.9 hours on research, 4.6 hours on protection and 5.5 hours on preparation. The study points out that as the volume of data increases, this wasted time will grow. In addition to this waste of time, managers lose 10 hours recreating existing data due to poor internal communication. (Source: CIO-online.com)
Money: Research and result preparation costs $1.7 million per year for US companies with more than 100 employees. In Europe, the annual revenue loss is estimated at $1.1 million for the same size company.
If you can answer these 3 questions, even partially, you certainly have a lot to gain by investing in a scientific search engine.