{"id":49,"date":"2024-04-04T04:36:12","date_gmt":"2024-04-04T01:36:12","guid":{"rendered":"https:\/\/sisu.ut.ee\/andmehaldus\/avaandmete-otsing\/"},"modified":"2024-04-04T04:37:02","modified_gmt":"2024-04-04T01:37:02","slug":"avaandmete-otsing","status":"publish","type":"page","link":"https:\/\/sisu.ut.ee\/andmehaldus\/avaandmete-otsing\/?lang=en","title":{"rendered":"Open Data Search"},"content":{"rendered":"

\n\tThe final stage and probably the first stage of a new project in the research\u00a0data lifecycle is data re-use. This means that data already published by someone should\u00a0be found, accessed and understood in order to be used in secondary research.<\/strong> Once machine-readable FAIR data is found, it can be integrated with your systems.\n<\/p>\n

\n\tWhere and how to search for open data depends very much on the users, their\u00a0specialty and information needs.<\/strong> The main search fields in data registers are author, keywords and data type.\n<\/p>\n

\n\tFor example, an astronomer needs data from long-term observations<\/strong>, which are downloaded directly from instruments to a disciplinary repository, and the data is dynamic and large-scale.<\/strong>
Developers of artificial intelligence need big data for machine learning<\/strong>.
In medicine, for example, diagnostic imaging\u00a0 files and 3D images<\/strong> are needed, not to mention patients\u2019 health data<\/strong>.
In archeology, field work diaries, photographs, artifacts <\/strong>and questionnaires<\/strong> in social sciences, survey data, interviews, video material<\/strong> are of interest.
In the humanities, research is often based on previous\u00a0 publications and manuscripts<\/strong>.\n<\/p>\n

\n\tFirst of all, you should think about what and how to search, plan a strategy.<\/strong>\n<\/p>\n

\n\t1. The easiest way is to\u00a0 check whether the data has been published or linked with the article<\/strong> and then move on to the repository to download the data if it is necessary.
Data, methods and code can be found in the article as supplemental material or\u00a0supporting information.\n<\/p>\n

\n\t2. However, the publication of data is a relatively recent practice, so in the case of older articles, the data may not be available or the underlying data is not\u00a0mentioned at all, only the analyzed data and results are described in the article.\u00a0
In this case, it is possible to use networks of researchers and contact the authors directly to request data.<\/strong> Several studies have shown that researchers have long been willing to share their data, but they know that data is not properly managed, so they do not want to publish it.\n<\/p>\n

\n\t3. Data repositories.<\/strong> In the previous study material, we considered repositories like archives, where researchers can store\u00a0scientific data for a long time.
Here we count on\u00a0repositories as sources of open data<\/strong>.\n<\/p>\n

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\n\tEffective data search<\/span>
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\n\tIf the search has led to some datasets\u00a0of interest, these must be thoroughly examined and the quality and reusability of the database assessed.
The README.txt file and all metadata are helpful. If you start to delve into them, you can find a lot of good and bad examples from which to learn how to publish your own data in good way.
Metadata should provide so much information that you don\u2019t need to download it until you\u2019re absolutely sure you want to explore or use it.\n<\/p>\n

\n\tThe following article provides some tips for effective data retrieval<\/strong>; you can delve into each point when you open the article:
Gregory K, Khalsa SJ, Michener WK, Psomopoulos FE, de Waard A, Wu M (2018) Eleven quick tips for finding research data. PLoS Comput Biol 14(4): e1006038.\u00a0https:\/\/doi.org\/10.1371\/journal.pcbi.1006038<\/a>\n<\/p>\n

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