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SHAPE-ID Literature Review query strings for Web of Science and Scopus

Wciślik, Piotr; Maryl, Maciej; Vienni Baptista, Bianca; Schriber, Lucien


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    <subfield code="a">&lt;p&gt;&lt;strong&gt;Background and methodology:&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;The document contains query strings which were used to generate bibliographic datasets in Scopus&amp;nbsp;and Web of Science (WoS) databases for the qualitative and quantitative literature review in the framework of the &lt;a href="https://www.shapeid.eu/"&gt;SHAPE-ID project&lt;/a&gt;.&lt;/p&gt;

&lt;p&gt;Given that WoS and Scopus offer homologous search and filtering functionalities, same method was used to query both databases. The method consisted in four steps, each consisting of defining constraints that enabled to filter-down the resources in order to arrive at an optimal data set.&amp;nbsp;&lt;/p&gt;

&lt;p&gt;STEP 1. First, we created the long list of literature. To do that, we combined project-relevant sets of keywords (Sets A-D) into doubles and triplets using proximity search operators in both databases and searching in title, abstract and keyword fields, according to the following schema:&lt;/p&gt;

&lt;p&gt;DOUBLES:&amp;nbsp; &amp;nbsp; &amp;nbsp; TRIPLETS:&lt;/p&gt;

&lt;p&gt;B NEAR/1 A&amp;nbsp; &amp;nbsp; &amp;nbsp; (B NEAR/3 C) NEAR/3 A&lt;/p&gt;

&lt;p&gt;C NEAR/1 A&amp;nbsp; &amp;nbsp; &amp;nbsp; (D NEAR/3 C) NEAR/3 A&lt;/p&gt;

&lt;p&gt;D NEAR/1 A&amp;nbsp; &amp;nbsp; &amp;nbsp; (B NEAR/3 D) NEAR/3 A&lt;/p&gt;

&lt;p&gt;This method enabled us to query the databases in a more precise way, using key-phrases consisting of two interrelated words or &amp;ldquo;doubles&amp;rdquo; (e.g. &amp;ldquo;transdisciplinary approach&amp;rdquo;) , and three interrelated words or &amp;ldquo;triplets&amp;rdquo; (e.g. &amp;ldquo;interdisciplinary research policy &amp;rdquo;),&amp;nbsp; instead of keywords that can appear without specific interrelation (e.g. when using boolean operator AND instead of proximity operator, we would get results even if words &amp;ldquo;interdisciplinary&amp;rdquo;, &amp;ldquo;research&amp;rdquo; and &amp;ldquo;policy&amp;rdquo; appear in random places in the same abstract, title and keywords).&amp;nbsp;&lt;/p&gt;

&lt;p&gt;STEP 2. Next, within that long list, we looked (again in title, abstract and keywords) for items that either discuss understandings of interdisciplinarity and transdisciplinarity (keyword set E), or relate to factors or indicators of success or failure (sets E and G correlated through proximity search), according to the following schema:&lt;/p&gt;

&lt;p&gt;E OR (F NEAR/1 G).&lt;/p&gt;

&lt;p&gt;STEP 3. We further limited the dataset to only those items that have keywords from set A (interdisciplinarity and transdisciplinarity in different variants) in the title - considered as a marker of strong relationship to the subject matter.&amp;nbsp;&lt;/p&gt;

&lt;p&gt;STEP 4. Finally, we added the he following constraints:&lt;/p&gt;

&lt;p&gt;Temporal scope: 1990-present&lt;/p&gt;

&lt;p&gt;Document Language: English&lt;/p&gt;

&lt;p&gt;Document Type: Articles, Books and Book Chapters, Editorials&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Description of the file:&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;This is a text file containing keyword strings used to query WoS and Scopus databases.&lt;/p&gt;</subfield>
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