Geför­dert durch:

Abstract

Abs­tract: Bren­tel, I., & Win­ters, K. (2018, 01.03.). A Case Stu­dy in Lar­ge Sca­le Varia­ble Har­mo­niz­a­ti­on. Gene­ral Online Rese­arch 2018 (GOR18), Ger­man Socie­ty for Online-Rese­arch. TH Köln, Köln. [Tan­dem 1]

Rele­van­ce & Rese­arch Ques­ti­on: One of the NRW-Inno­va­tiv pro­jects is an attempt to fill a lacu­na in com­mu­ni­ca­ti­ons stu­dies by crea­ting a har­mo­ni­zed data­set for lon­gi­tu­di­nal data (sin­ce 1954) about media use in Ger­ma­ny explo­i­t­ing the Media-Ana­ly­sis-Data. In making lar­ge sca­le media use data acces­si­ble for aca­de­mic rese­arch in high qua­li­ty stan­dards of data docu­men­ta­ti­on lies the rele­van­ce of this pro­ject. The rese­arch ques­ti­on, the­re­fo­re, is: how to make the Media-Ana­ly­sis-Data – as a big data – acces­si­ble for aca­de­mic rese­arch while being transparent.

Methods & Data: This paper will pre­sent the various theo­re­ti­cal, prac­ti­cal and the use of a digi­tal har­mo­niz­a­ti­on soft­ware, Charm­Stats, uti­li­zed over the cour­se of this pro­ject. Goal of the har­mo­niz­a­ti­on was to crea­te a sci­en­ti­fic use file set­ting excel­lent docu­men­ta­ti­on stan­dards with the help of Charm­Stats and to con­ti­nue the har­mo­niz­a­ti­on alrea­dy done until 2009. Using a new har­mo­niz­a­ti­on soft­ware, Charm­Stats, we review the chal­len­ges and solu­ti­ons deve­lo­ped as a case stu­dy in lar­ge-sca­le data har­mo­niz­a­ti­on. With more than 1.5 mil­li­on cases per data­set – in total the­re are two har­mo­ni­zed data­sets –, each with almost 30.000 varia­bles for over 60 years for press­me­dia and almost 40 years for radio, the Media-Ana­ly­sis data can be coun­ted as the big­gest data­set of media use in Ger­ma­ny being avail­ab­le for academics.

Results: Tar­get of the pro­ject is to make the com­plex pro­cess of data har­mo­niz­a­ti­on with lar­ge-sca­le data most trans­pa­rent and repli­ca­ble. Charm­Stats offers the pos­si­bi­li­ty to ful­fil the project´s goals as it pro­du­ces syn­ta­xes for data har­mo­niz­a­ti­on plus a report for docu­men­ta­ti­on. For the pre­sen­ta­ti­on we would por­trait the dif­fe­rent levels to reach the pro­jects´ goals to ans­wer the rese­arch question:

  1. Find a struc­tu­re to work with
  2. Set­ting stan­dards for data docu­men­ta­ti­on with CharmStats
  3. Pro­du­cing a har­mo­ni­zed dataset
  4. Making the data­set repli­ca­ble, moreo­ver, making it an acces­si­ble and sus­tainab­le source for aca­de­mic rese­arch throughout the Libra­ry of Online Har­mo­niz­a­ti­on (sche­du­led for release in 2019)

Added Value: The metho­do­lo­gi­cal approach of this pro­ject can be coun­ted as a user case for docu­men­ting and har­mo­ni­zing big data for aca­de­mic research.